General news from the MIT - Massachusetts Institute of Technology University

MIT News
MIT News is dedicated to communicating to the media and the public the news and achievements of the students, faculty, staff and the greater MIT community.
Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.

Launched in February of this year, the MIT Generative AI Impact Consortium (MGAIC), a presidential initiative led by MIT’s Office of Innovation and Strategy and administered by the MIT Stephen A. Schwarzman College of Computing, issued a call for proposals, inviting researchers from across MIT to submit ideas for innovative projects studying high-impact uses of generative AI models.

The call received 180 submissions from nearly 250 faculty members, spanning all of MIT’s five schools and the college. The overwhelming response across the Institute exemplifies the growing interest in AI and follows in the wake of MIT’s Generative AI Week and call for impact papers. Fifty-five proposals were selected for MGAIC’s inaugural seed grants, with several more selected to be funded by the consortium’s founding company members.

Over 30 funding recipients presented their proposals to the greater MIT community at a kickoff event on May 13. Anantha P. Chandrakasan, chief innovation and strategy officer and dean of the School of Engineering who is head of the consortium, welcomed the attendees and thanked the consortium’s founding industry members.

“The amazing response to our call for proposals is an incredible testament to the energy and creativity that MGAIC has sparked at MIT. We are especially grateful to our founding members, whose support and vision helped bring this endeavor to life,” adds Chandrakasan. “One of the things that has been most remarkable about MGAIC is that this is a truly cross-Institute initiative. Deans from all five schools and the college collaborated in shaping and implementing it.”

Vivek F. Farias, the Patrick J. McGovern (1959) Professor at the MIT Sloan School of Management and co-faculty director of the consortium with Tim Kraska, associate professor of electrical engineering and computer science in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), emceed the afternoon of five-minute lightning presentations.

Presentation highlights include:

“AI-Driven Tutors and Open Datasets for Early Literacy Education,” presented by Ola Ozernov-Palchik, a research scientist at the McGovern Institute for Brain Research, proposed a refinement for AI-tutors for pK-7 students to potentially decrease literacy disparities.

“Developing jam_bots: Real-Time Collaborative Agents for Live Human-AI Musical Improvisation,” presented by Anna Huang, assistant professor of music and assistant professor of electrical engineering and computer science, and Joe Paradiso, the Alexander W. Dreyfoos (1954) Professor in Media Arts and Sciences at the MIT Media Lab, aims to enhance human-AI musical collaboration in real-time for live concert improvisation.

“GENIUS: GENerative Intelligence for Urban Sustainability,” presented by Norhan Bayomi, a postdoc at the MIT Environmental Solutions Initiative and a research assistant in the Urban Metabolism Group, which aims to address the critical gap of a standardized approach in evaluating and benchmarking cities’ climate policies.

Georgia Perakis, the John C Head III Dean (Interim) of the MIT Sloan School of Management and professor of operations management, operations research, and statistics, who serves as co-chair of the GenAI Dean’s oversight group with Dan Huttenlocher, dean of the MIT Schwarzman College of Computing, ended the event with closing remarks that emphasized “the readiness and eagerness of our community to lead in this space.”

“This is only the beginning,” he continued. “We are at the front edge of a historic moment — one where MIT has the opportunity, and the responsibility, to shape the future of generative AI with purpose, with excellence, and with care.”

Introducing the L. Rafael Reif Innovation Corridor

“A channel for people and ideas to flow freely through the heart of MIT,” the walkway between buildings 12, 13, 24, and 31 has been named in honor of MIT’s 17th president.

The open space connecting Hockfield Court with Massachusetts Avenue, in the heart of MIT’s campus, is now the L. Rafael Reif Innovation Corridor, in honor of the Institute’s 17th president. At a dedication ceremony Monday, Reif’s colleagues, friends, and family gathered to honor his legacy and unveil a marker for the walkway that was previously known as North Corridor or “the Outfinite.”

“It’s no accident that the space we dedicate today is not a courtyard, but a corridor — a channel for people and ideas to flow freely through the heart of MIT, and to carry us outward, to limits of our aspirations,” said Sally Kornbluth, who succeeded Reif as MIT president in 2023.

“With his signature combination of new-world thinking and old-world charm, and as a grand thinker and doer, Rafael left an indelible mark on MIT,” Kornbluth said. “As a permanent testament to his service and his achievements in service to MIT, the nation, and the world, we now dedicate this space as the L. Rafael Reif Innovation Corridor.”

Reif served as president for more than 10 years, following seven years as provost. He has been at MIT since 1980, when he joined the faculty as an assistant professor of electrical engineering.

“Through all those roles, what stood out most was his humility, his curiosity, and his remarkable ability to speak with clarity and conviction,” said Corporation Chair Mark Gorenberg, who opened the ceremony. “Under his leadership, MIT not only stayed true to its mission, it thrived, expanding its impact and strengthening its global voice.”

Gorenberg introduced Abraham J. Siegel Professor of Management and professor of operations research Cindy Barnhart, who served as chancellor, then provost, during Reif’s term as president. Barnhart, who will be stepping down as provost on July 1, summarized the many highlights from Reif’s presidency, such as the establishment of MIT Schwarzman College of Computing, the revitalization of Kendall Square, and the launch of The Engine, as well as the construction or modernization of many buildings, from the Wright Brothers Wind Tunnel to the new Edward and Joyce Linde Music Building, among other accomplishments.

“Beyond space, Rafael’s bold thinking and passion extends to MIT’s approach to education,” Barnhart continued, describing how Reif championed the building of OpenCourseWare, MITx, and edX. She also noted his support for the health and well-being of the MIT community, through efforts such as addressing student sexual misconduct and forming the MindHandHeart initiative. He also hosted dance parties and socials, joined students in the dining halls for dinner, chatted with faculty and staff over breakfasts and at forums, and more.

“At gatherings over the years, Rafael’s wife, Chris, was there by his side,” Barnhart noted, adding, “I’d like to take this opportunity to acknowledge her and thank her for her welcoming and gracious spirit.”

In summary, “I am grateful to Rafael for his visionary leadership and for his love of MIT and its people,” Barnhart said as she presented Reif with a 3D-printed replica of the Maclaurin buildings (MIT Buildings 3, 4, and 10), which was created through a collaboration between the Glass Lab, Edgerton Center, and Project Manus.

Next, Institute Professor Emeritus John Harbison played an interlude on the piano, and a musical ensemble reprised the “Rhumba for Rafael,” which Harbison composed for Reif’s inauguration in 2012.

When Reif took the podium, he reflected on the location of the corridor and its significance to early chapters in his own career; his first office and lab were in Building 13, overlooking what is now the eponymous walkway.

He also considered the years ahead: “The people who pass through this corridor in the future will surely experience the unparalleled excitement of being young at MIT, with the full expectation of upending the world to improve it,” he said.

Faculty and staff walking through the corridor may experience the “undimmed excitement” of working and studying alongside extraordinary students and colleagues, and feeling the “deep satisfaction of having created infinite memories here throughout a long career.”

“Even if none of them gives me a thought,” Reif continued, “I would like to believe that my spirit will be here, watching them with pride as they continue the never-ending mission of creating a better world.”

Island rivers carve passageways through coral reefs

Research shows these channels allow seawater and nutrients to flow in and out, helping to maintain reef health over millions of years.

Volcanic islands, such as the islands of Hawaii and the Caribbean, are surrounded by coral reefs that encircle an island in a labyrinthine, living ring. A coral reef is punctured at points by reef passes — wide channels that cut through the coral and serve as conduits for ocean water and nutrients to filter in and out. These watery passageways provide circulation throughout a reef, helping to maintain the health of corals by flushing out freshwater and transporting key nutrients.

Now, MIT scientists have found that reef passes are shaped by island rivers. In a study appearing today in the journal Geophysical Research Letters, the team shows that the locations of reef passes along coral reefs line up with where rivers funnel out from an island’s coast.

Their findings provide the first quantitative evidence of rivers forming reef passes.  Scientists and explorers had speculated that this may be the case: Where a river on a volcanic island meets the coast, the freshwater and sediment it carries flows toward the reef, where a strong enough flow can tunnel into the surrounding coral. This idea has been proposed from time to time but never quantitatively tested, until now.

“The results of this study help us to understand how the health of coral reefs depends on the islands they surround,” says study author Taylor Perron, the Cecil and Ida Green Professor of Earth, Atmospheric and Planetary Sciences at MIT.

“A lot of discussion around rivers and their impact on reefs today has been negative because of human impact and the effects of agricultural practices,” adds lead author Megan Gillen, a graduate student in the MIT-WHOI Joint Program in Oceanography. “This study shows the potential long-term benefits rivers can have on reefs, which I hope reshapes the paradigm and highlights the natural state of rivers interacting with reefs.”

The study’s other co-author is Andrew Ashton of the Woods Hole Oceanographic Institution.

Drawing the lines

The new study is based on the team’s analysis of the Society Islands, a chain of islands in the South Pacific Ocean that includes Tahiti and Bora Bora. Gillen, who joined the MIT-WHOI program in 2020, was interested in exploring connections between coral reefs and the islands they surround. With limited options for on-site work during the Covid-19 pandemic, she and Perron looked to see what they could learn through satellite images and maps of island topography. They did a quick search using Google Earth and zeroed in on the Society Islands for their uniquely visible reef and island features.

“The islands in this chain have these iconic, beautiful reefs, and we kept noticing these reef passes that seemed to align with deeply embayed portions of the coastline,” Gillen says. “We started asking ourselves, is there a correlation here?”

Viewed from above, the coral reefs that circle some islands bear what look to be notches, like cracks that run straight through a ring. These breaks in the coral are reef passes — large channels that run tens of meters deep and can be wide enough for some boats to pass through. On first look, Gillen noticed that the most obvious reef passes seemed to line up with flooded river valleys — depressions in the coastline that have been eroded over time by island rivers that flow toward the ocean. She wondered whether and to what extent island rivers might shape reef passes.

“People have examined the flow through reef passes to understand how ocean waves and seawater circulate in and out of lagoons, but there have been no claims of how these passes are formed,” Gillen says. “Reef pass formation has been mentioned infrequently in the literature, and people haven’t explored it in depth.”

Reefs unraveled

To get a detailed view of the topography in and around the Society Islands, the team used data from the NASA Shuttle Radar Topography Mission — two radar antennae that flew aboard the space shuttle in 1999 and measured the topography across 80 percent of the Earth’s surface.

The researchers used the mission’s topographic data in the Society Islands to create a map of every drainage basin along the coast of each island, to get an idea of where major rivers flow or once flowed. They also marked the locations of every reef pass in the surrounding coral reefs. They then essentially “unraveled” each island’s coastline and reef into a straight line, and compared the locations of basins versus reef passes.

“Looking at the unwrapped shorelines, we find a significant correlation in the spatial relationship between these big river basins and where the passes line up,” Gillen says. “So we can say that statistically, the alignment of reef passes and large rivers does not seem random. The big rivers have a role in forming passes.”

As for how rivers shape the coral conduits, the team has two ideas, which they call, respectively, reef incision and reef encroachment. In reef incision, they propose that reef passes can form in times when the sea level is relatively low, such that the reef is exposed above the sea surface and a river can flow directly over the reef. The water and sediment carried by the river can then erode the coral, progressively carving a path through the reef.

When sea level is relatively higher, the team suspects a reef pass can still form, through reef encroachment. Coral reefs naturally live close to the water surface, where there is light and opportunity for photosynthesis. When sea levels rise, corals naturally grow upward and inward toward an island, to try to “catch up” to the water line.

“Reefs migrate toward the islands as sea levels rise, trying to keep pace with changing average sea level,” Gillen says.

However, part of the encroaching reef can end up in old river channels that were previously carved out by large rivers and that are lower than the rest of the island coastline. The corals in these river beds end up deeper than light can extend into the water column, and inevitably drown, leaving a gap in the form of a reef pass.

“We don’t think it’s an either/or situation,” Gillen says. “Reef incision occurs when sea levels fall, and reef encroachment happens when sea levels rise. Both mechanisms, occurring over dozens of cycles of sea-level rise and island evolution, are likely responsible for the formation and maintenance of reef passes over time.”

The team also looked to see whether there were differences in reef passes in older versus younger islands. They observed that younger islands were surrounded by more reef passes that were spaced closer together, versus older islands that had fewer reef passes that were farther apart.

As islands age, they subside, or sink, into the ocean, which reduces the amount of land that funnels rainwater into rivers. Eventually, rivers are too weak to keep the reef passes open, at which point, the ocean likely takes over, and incoming waves could act to close up some passes.

Gillen is exploring ideas for how rivers, or river-like flow, can be engineered to create paths through coral reefs in ways that would promote circulation and benefit reef health.

“Part of me wonders: If you had a more persistent flow, in places where you don’t naturally have rivers interacting with the reef, could that potentially be a way to increase health, by incorporating that river component back into the reef system?” Gillen says. “That’s something we’re thinking about.”

This research was supported, in part, by the WHOI Watson and Von Damm fellowships.

MIT engineers uncover a surprising reason why tissues are flexible or rigid

Watery fluid between cells plays a major role, offering new insights into how organs and tissues adapt to aging, diabetes, cancer, and more.

Water makes up around 60 percent of the human body. More than half of this water sloshes around inside the cells that make up organs and tissues. Much of the remaining water flows in the nooks and crannies between cells, much like seawater between grains of sand.

Now, MIT engineers have found that this “intercellular” fluid plays a major role in how tissues respond when squeezed, pressed, or physically deformed. Their findings could help scientists understand how cells, tissues, and organs physically adapt to conditions such as aging, cancer, diabetes, and certain neuromuscular diseases.

In a paper appearing today in Nature Physics, the researchers show that when a tissue is pressed or squeezed, it is more compliant and relaxes more quickly when the fluid between its cells flows easily. When the cells are packed together and there is less room for intercellular flow, the tissue as a whole is stiffer and resists being pressed or squeezed.

The findings challenge conventional wisdom, which has assumed that a tissue’s compliance depends mainly on what’s inside, rather than around, a cell. Now that the researchers have shown that intercellular flow determines how tissues will adapt to physical forces, the results can be applied to understand a wide range of physiological conditions, including how muscles withstand exercise and recover from injury, and how a tissue’s physical adaptability may affect the progression of aging, cancer, and other medical conditions.

The team envisions the results could also inform the design of artificial tissues and organs. For instance, in engineering artificial tissue, scientists might optimize intercellular flow within the tissue to improve its function or resilience. The researchers suspect that intercellular flow could also be a route for delivering nutrients or therapies, either to heal a tissue or eradicate a tumor.

“People know there is a lot of fluid between cells in tissues, but how important that is, in particular in tissue deformation, is completely ignored,” says Ming Guo, associate professor of mechanical engineering at MIT. “Now we really show we can observe this flow. And as the tissue deforms, flow between cells dominates the behavior. So, let’s pay attention to this when we study diseases and engineer tissues.”

Guo is a co-author of the new study, which includes lead author and MIT postdoc Fan Liu PhD ’24, along with Bo Gao and Hui Li of Beijing Normal University, and Liran Lei and Shuainan Liu of Peking Union Medical College.

Pressed and squeezed

The tissues and organs in our body are constantly undergoing physical deformations, from the large stretch and strain of muscles during motion to the small and steady contractions of the heart. In some cases, how easily tissues adapt to deformation can relate to how quickly a person can recover from, for instance, an allergic reaction, a sports injury, or a brain stroke. However, exactly what sets a tissue’s response to deformation is largely unknown.

Guo and his group at MIT looked into the mechanics of tissue deformation, and the role of intercellular flow in particular, following a study they published in 2020. In that study, they focused on tumors and observed the way in which fluid can flow from the center of a tumor out to its edges, through the cracks and crevices between individual tumor cells. They found that when a tumor was squeezed or pressed, the intercellular flow increased, acting as a conveyor belt to transport fluid from the center to the edges. Intercellular flow, they found, could fuel tumor invasion into surrounding regions.

In their new study, the team looked to see what role this intercellular flow might play in other, noncancerous tissues.

“Whether you allow the fluid to flow between cells or not seems to have a major impact,” Guo says. “So we decided to look beyond tumors to see how this flow influences how other tissues respond to deformation.”

A fluid pancake

Guo, Liu, and their colleagues studied the intercellular flow in a variety of biological tissues, including cells derived from pancreatic tissue. They carried out experiments in which they first cultured small clusters of tissue, each measuring less than a quarter of a millimeter wide and numbering tens of thousands of individual cells. They placed each tissue cluster in a custom-designed testing platform that the team built specifically for the study.

“These microtissue samples are in this sweet zone where they are too large to see with atomic force microscopy techniques and too small for bulkier devices,” Guo says. “So, we decided to build a device.”

The researchers adapted a high-precision microbalance that measures minute changes in weight. They combined this with a step motor that is designed to press down on a sample with nanometer precision. The team placed tissue clusters one at a time on the balance and recorded each cluster’s changing weight as it relaxed from a sphere into the shape of a pancake in response to the compression. The team also took videos of the clusters as they were squeezed.

For each type of tissue, the team made clusters of varying sizes. They reasoned that if the tissue’s response is ruled by the flow between cells, then the bigger a tissue, the longer it should take for water to seep through, and therefore, the longer it should take the tissue to relax. It should take the same amount of time, regardless of size, if a tissue’s response is determined by the structure of the tissue rather than fluid.

Over multiple experiments with a variety of tissue types and sizes, the team observed a similar trend: The bigger the cluster, the longer it took to relax, indicating that intercellular flow dominates a tissue’s response to deformation.

“We show that this intercellular flow is a crucial component to be considered in the fundamental understanding of tissue mechanics and also applications in engineering living systems,” Liu says.

Going forward, the team plans to look into how intercellular flow influences brain function, particularly in disorders such as Alzheimer’s disease.

“Intercellular or interstitial flow can help you remove waste and deliver nutrients to the brain,” Liu adds. “Enhancing this flow in some cases might be a good thing.”

“As this work shows, as we apply pressure to a tissue, fluid will flow,” Guo says. “In the future, we can think of designing ways to massage a tissue to allow fluid to transport nutrients between cells.”

“Cold spray” 3D printing technique proves effective for on-site bridge repair

Working with the Massachusetts Department of Transportation, researchers show bridge corrosion can be repaired on-site using additive manufacturing.

More than half of the nation’s 623,218 bridges are experiencing significant deterioration. Through an in-field case study conducted in western Massachusetts, a team led by the University of Massachusetts at Amherst in collaboration with researchers from the MIT Department of Mechanical Engineering (MechE) has just successfully demonstrated that 3D printing may provide a cost-effective, minimally disruptive solution.

“Anytime you drive, you go under or over a corroded bridge,” says Simos Gerasimidis, associate professor of civil and environmental engineering at UMass Amherst and former visiting professor in the Department of Civil and Environmental Engineering at MIT, in a press release. “They are everywhere. It’s impossible to avoid, and their condition often shows significant deterioration. We know the numbers.”

The numbers, according to the American Society of Civil Engineers’ 2025 Report Card for America’s Infrastructure, are staggering: Across the United States, 49.1 percent of the nation’s 623,218 bridges are in “fair” condition and 6.8 percent are in “poor” condition. The projected cost to restore all of these failing bridges exceeds $191 billion.

A proof-of-concept repair took place last month on a small, corroded section of a bridge in Great Barrington, Massachusetts. The technique, called cold spray, can extend the life of beams, reinforcing them with newly deposited steel. The process accelerates particles of powdered steel in heated, compressed gas, and then a technician uses an applicator to spray the steel onto the beam. Repeated sprays create multiple layers, restoring thickness and other structural properties.

This method has proven to be an effective solution for other large structures like submarines, airplanes, and ships, but bridges present a problem on a greater scale. Unlike movable vessels, stationary bridges cannot be brought to the 3D printer — the printer must be brought on-site — and, to lessen systemic impacts, repairs must also be made with minimal disruptions to traffic, which the new approach allows.

“Now that we’ve completed this proof-of-concept repair, we see a clear path to a solution that is much faster, less costly, easier, and less invasive,” says Gerasimidis. “To our knowledge, this is a first. Of course, there is some R&D that needs to be developed, but this is a huge milestone to that.”

“This is a tremendous collaboration where cutting-edge technology is brought to address a critical need for infrastructure in the commonwealth and across the United States,” says John Hart, Class of 1922 Professor and head of the Department of MechE at MIT. Hart and Haden Quinlan, senior program manager in the Center for Advanced Production Technologies at MIT, are leading MIT’s efforts in in the project. Hart is also faculty co-lead of the recently announced MIT Initiative for New Manufacturing.

“Integrating digital systems with advanced physical processing is the future of infrastructure,” says Quinlan. “We’re excited to have moved this technology beyond the lab and into the field, and grateful to our collaborators in making this work possible.”

UMass says the Massachusetts Department of Transportation (MassDOT) has been a valued research partner, helping to identify the problem and providing essential support for the development and demonstration of the technology. Technical guidance and funding support were provided by the MassDOT Highway Division and the Research and Technology Transfer Program.

Equipment for this project was supported through the Massachusetts Manufacturing Innovation Initiative, a statewide program led by the Massachusetts Technology Collaborative (MassTech)’s Center for Advanced Manufacturing that helps bridge the gap between innovation and commercialization in hard tech manufacturing.

“It’s a very Massachusetts success story,” Gerasimidis says. “It involves MassDOT being open-minded to new ideas. It involves UMass and MIT putting [together] the brains to do it. It involves MassTech to bring manufacturing back to Massachusetts. So, I think it’s a win-win for everyone involved here.”

The bridge in Great Barrington is scheduled for demolition in a few years. After demolition occurs, the recently-sprayed beams will be taken back to UMass for testing and measurement to study how well the deposited steel powder adhered to the structure in the field compared to in a controlled lab setting, if it corroded further after it was sprayed, and determine its mechanical properties.

This demonstration builds on several years of research by the UMass and MIT teams, including development of a “digital thread” approach to scan corroded beam surfaces and determine material deposition profiles, alongside laboratory studies of cold spray and other additive manufacturing approaches that are suited to field deployment.

Altogether, this work is a collaborative effort among UMass Amherst, MIT MechE, MassDOT, the Massachusetts Technology Collaborative (MassTech), the U.S. Department of Transportation, and the Federal Highway Administration. Research reports are available on the MassDOT website.  

When Earth iced over, early life may have sheltered in meltwater ponds

Modern-day analogs in Antarctica reveal ponds teeming with life similar to early multicellular organisms.

When the Earth froze over, where did life shelter? MIT scientists say one refuge may have been pools of melted ice that dotted the planet’s icy surface.

In a study appearing today in Nature Communications, the researchers report that 635 million to 720 million years ago, during periods known as “Snowball Earth,” when much of the planet was covered in ice, some of our ancient cellular ancestors could have waited things out in meltwater ponds.

The scientists found that eukaryotes — complex cellular lifeforms that eventually evolved into the diverse multicellular life we see today — could have survived the global freeze by living in shallow pools of water. These small, watery oases may have persisted atop relatively shallow ice sheets present in equatorial regions. There, the ice surface could accumulate dark-colored dust and debris from below, which enhanced its ability to melt into pools. At temperatures hovering around 0 degrees Celsius, the resulting meltwater ponds could have served as habitable environments for certain forms of early complex life.

The team drew its conclusions based on an analysis of modern-day meltwater ponds. Today in Antarctica, small pools of melted ice can be found along the margins of ice sheets. The conditions along these polar ice sheets are similar to what likely existed along ice sheets near the equator during Snowball Earth.

The researchers analyzed samples from a variety of meltwater ponds located on the McMurdo Ice Shelf in an area that was first described by members of Robert Falcon Scott's 1903 expedition as “dirty ice.” The MIT researchers discovered clear signatures of eukaryotic life in every pond. The communities of eukaryotes varied from pond to pond, revealing a surprising diversity of life across the setting. The team also found that salinity plays a key role in the kind of life a pond can host: Ponds that were more brackish or salty had more similar eukaryotic communities, which differed from those in ponds with fresher waters.

“We’ve shown that meltwater ponds are valid candidates for where early eukaryotes could have sheltered during these planet-wide glaciation events,” says lead author Fatima Husain, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “This shows us that diversity is present and possible in these sorts of settings. It’s really a story of life’s resilience.”

The study’s MIT co-authors include Schlumberger Professor of Geobiology Roger Summons and former postdoc Thomas Evans, along with Jasmin Millar of Cardiff University, Anne Jungblut at the Natural History Museum in London, and Ian Hawes of the University of Waikato in New Zealand.

Polar plunge

“Snowball Earth” is the colloquial term for periods of time in Earth history during which the planet iced over. It is often used as a reference to the two consecutive, multi-million-year glaciation events which took place during the Cryogenian Period, which geologists refer to as the time between 635 and 720 million years ago. Whether the Earth was more of a hardened snowball or a softer “slushball” is still up for debate. But scientists are certain of one thing: Most of the planet was plunged into a deep freeze, with average global temperatures of minus 50 degrees Celsius. The question has been: How and where did life survive?

“We’re interested in understanding the foundations of complex life on Earth. We see evidence for eukaryotes before and after the Cryogenian in the fossil record, but we largely lack direct evidence of where they may have lived during,” Husain says. “The great part of this mystery is, we know life survived. We’re just trying to understand how and where.”

There are a number of ideas for where organisms could have sheltered during Snowball Earth, including in certain patches of the open ocean (if such environments existed), in and around deep-sea hydrothermal vents, and under ice sheets. In considering meltwater ponds, Husain and her colleagues pursued the hypothesis that surface ice meltwaters may also have been capable of supporting early eukaryotic life at the time.

“There are many hypotheses for where life could have survived and sheltered during the Cryogenian, but we don’t have excellent analogs for all of them,” Husain notes. “Above-ice meltwater ponds occur on Earth today and are accessible, giving us the opportunity to really focus in on the eukaryotes which live in these environments.”

Small pond, big life

For their new study, the researchers analyzed samples taken from meltwater ponds in Antarctica. In 2018, Summons and colleagues from New Zealand traveled to a region of the McMurdo Ice Shelf in East Antarctica, known to host small ponds of melted ice, each just a few feet deep and a few meters wide. There, water freezes all the way to the seafloor, in the process trapping dark-colored sediments and marine organisms. Wind-driven loss of ice from the surface creates a sort of conveyer belt that brings this trapped debris to the surface over time, where it absorbs the sun’s warmth, causing ice to melt, while surrounding debris-free ice reflects incoming sunlight, resulting in the formation of shallow meltwater ponds.

The bottom of each pond is lined with mats of microbes that have built up over years to form layers of sticky cellular communities.

“These mats can be a few centimeters thick, colorful, and they can be very clearly layered,” Husain says.

These microbial mats are made up of cyanobacteria, prokaryotic, single-celled photosynthetic organisms that lack a cell nucleus or other organelles. While these ancient microbes are known to survive within some of the the harshest environments on Earth including meltwater ponds, the researchers wanted to know whether eukaryotes — complex organisms that evolved a cell nucleus and other membrane bound organelles — could also weather similarly challenging circumstances. Answering this question would take more than a microscope, as the defining characteristics of the microscopic eukaryotes present among the microbial mats are too subtle to distinguish by eye.

To characterize the eukaryotes, the team analyzed the mats for specific lipids they make called sterols, as well as genetic components called ribosomal ribonucleic acid (rRNA), both of which can be used to identify organisms with varying degrees of specificity. These two independent sets of analyses provided complementary fingerprints for certain eukaryotic groups. As part of the team’s lipid research, they found many sterols and rRNA genes closely associated with specific types of algae, protists, and microscopic animals among the microbial mats. The researchers were able to assess the types and relative abundance of lipids and rRNA genes from pond to pond, and found the ponds hosted a surprising diversity of eukaryotic life.

“No two ponds were alike,” Husain says. “There are repeating casts of characters, but they’re present in different abundances. And we found diverse assemblages of eukaryotes from all the major groups in all the ponds studied. These eukaryotes are the descendants of the eukaryotes that survived the Snowball Earth. This really highlights that meltwater ponds during Snowball Earth could have served as above-ice oases that nurtured the eukaryotic life that enabled the diversification and proliferation of complex life — including us — later on.”

This research was supported, in part, by the NASA Exobiology Program, the Simons Collaboration on the Origins of Life, and a MISTI grant from MIT-New Zealand.

QS ranks MIT the world’s No. 1 university for 2025-26

Ranking at the top for the 14th year in a row, the Institute also places first in 11 subject areas.

MIT has again been named the world’s top university by the QS World University Rankings, which were announced today. This is the 14th year in a row MIT has received this distinction.

The full 2026 edition of the rankings — published by Quacquarelli Symonds, an organization specializing in education and study abroad — can be found at TopUniversities.com. The QS rankings are based on factors including academic reputation, employer reputation, citations per faculty, student-to-faculty ratio, proportion of international faculty, and proportion of international students.

MIT was also ranked the world’s top university in 11 of the subject areas ranked by QS, as announced in March of this year.

The Institute received a No. 1 ranking in the following QS subject areas: Chemical Engineering; Civil and Structural Engineering; Computer Science and Information Systems; Data Science and Artificial Intelligence; Electrical and Electronic Engineering; Linguistics; Materials Science; Mechanical, Aeronautical, and Manufacturing Engineering; Mathematics; Physics and Astronomy; and Statistics and Operational Research.

MIT also placed second in seven subject areas: Accounting and Finance; Architecture/Built Environment; Biological Sciences; Business and Management Studies; Chemistry; Earth and Marine Sciences; and Economics and Econometrics.

Memory safety is at a tipping point

Lincoln Laboratory cybersecurity expert Hamed Okhravi calls for a unified approach to securing computer memory, as a matter of national security.

Social security numbers stolen. Public transport halted. Hospital systems frozen until ransoms are paid. These are some of the damaging consequences of unsecure memory in computer systems.

Over the past decade, public awareness of such cyberattacks has intensified, as their impacts have harmed individuals, corporations, and governments. Today, this awareness is coinciding with technologies that are finally mature enough to eliminate vulnerabilities in memory safety.  

"We are at a tipping point — now is the right time to move to memory-safe systems," says Hamed Okhravi, a cybersecurity expert in MIT Lincoln Laboratory’s Secure Resilient Systems and Technology Group.

In an op-ed earlier this year in Communications of the ACM, Okhravi joined 20 other luminaries in the field of computer security to lay out a plan for achieving universal memory safety. They argue for a standardized framework as an essential next step to adopting memory-safety technologies throughout all forms of computer systems, from fighter jets to cell phones.

Memory-safety vulnerabilities occur when a program performs unintended or erroneous operations in memory. Such operations are prevalent, accounting for an estimated 70 percent of software vulnerabilities. If attackers gain access to memory, they can potentially steal sensitive information, alter program execution, or even take control of the computer system.

These vulnerabilities exist largely because common software programming languages, such as C or C++, are inherently memory-insecure. A simple error by a software engineer, perhaps one line in a system’s multimillion lines of code, could be enough for an attacker to exploit. In recent years, new memory-safe languages, such as Rust, have been developed. But rewriting legacy systems in new, memory-safe languages can be costly and complicated.

Okhravi focuses on the national security implications of memory-safety vulnerabilities. For the U.S. Department of Defense (DoD), whose systems comprise billions of lines of legacy C or C++ code, memory safety has long been a known problem. The National Security Agency (NSA) and the federal government have recently urged technology developers to eliminate memory-safety vulnerabilities from their products. Security concerns extend beyond military systems to widespread consumer products.

"Cell phones, for example, are not immediately important for defense or war-fighting, but if we have 200 million vulnerable cell phones in the nation, that’s a serious matter of national security," Okhravi says.

Memory-safe technology

In recent years, several technologies have emerged to help patch memory vulnerabilities in legacy systems. As the guest editor for a special issue of IEEE Security and Privacy, Okhravi solicited articles from top contributors in the field to highlight these technologies and the ways they can build on one another.  

Some of these memory-safety technologies have been developed at Lincoln Laboratory, with sponsorship from DoD agencies. These technologies include TRACER and TASR, which are software products for Windows and Linux systems, respectively, that reshuffle the location of code in memory each time a program accesses it, making it very difficult for attackers to find exploits. These moving-target solutions have since been licensed by cybersecurity and cloud services companies.

"These technologies are quick wins, enabling us to make a lot of immediate impact without having to rebuild the whole system. But they are only a partial solution, a way of securing legacy systems while we are transitioning to safer languages," Okhravi says.

Innovative work is underway to make that transition easier. For example, the TRACTOR program at the U.S. Defense Advanced Research Projects Agency is developing artificial intelligence tools to automatically translate legacy C code to Rust. Lincoln Laboratory researchers will test and evaluate the translator for use in DoD systems.

Okhravi and his coauthors acknowledged in their op-ed that the timeline for full adoption of memory-safe systems is long — likely decades. It will require the deployment of a combination of new hardware, software, and techniques, each with their own adoption paths, costs, and disruptions. Organizations should prioritize mission-critical systems first.

"For example, the most important components in a fighter jet, such as the flight-control algorithm or the munition-handling logic, would be made memory-safe, say, within five years," Okhravi says. Subsystems less important to critical functions would have a longer time frame.

Use of memory-safe programming languages at Lincoln Laboratory

As Lincoln Laboratory continues its leadership in advancing memory-safety technologies, the Secure Resilient Systems and Technology Group has prioritized adopting memory-safe programming languages. "We’ve been investing in the group-wide use of Rust for the past six years as part of our broader strategy to prototype cyber-hardened mission systems and high-assurance cryptographic implementations for the DoD and intelligence community," says Roger Khazan, who leads the group. "Memory safety is fundamental to trustworthiness in these systems."

Rust’s strong guarantees around memory safety, along with its speed and ability to catch bugs early during development, make it especially well-suited for building secure and reliable systems. The laboratory has been using Rust to prototype and transition secure components for embedded, distributed, and cryptographic systems where resilience, performance, and correctness are mission-critical.

These efforts support both immediate U.S. government needs and a longer-term transformation of the national security software ecosystem. "They reflect Lincoln Laboratory’s broader mission of advancing technology in service to national security, grounded in technical excellence, innovation, and trust," Khazan adds.

A technology-agnostic framework

The MIT Press acquires University Science Books from AIP Publishing

The textbook publisher will transfer to the MIT Press next month, in time for fall 2025 course adoptions.

The MIT Press announces the acquisition of textbook publisher University Science Books from AIP Publishing, a subsidiary of the American Institute of Physics (AIP).

University Science Books was founded in 1978 to publish intermediate- and advanced-level science and reference books by respected authors, published with the highest design and production standards, and priced as affordably as possible. Over the years, USB’s authors have acquired international followings, and its textbooks in chemistry, physics, and astronomy have been recognized as the gold standard in their respective disciplines. USB was acquired by AIP Publishing in 2021.

Bestsellers include John Taylor’s “Classical Mechanics,” the No. 1 adopted text for undergrad mechanics courses in the United States and Canada, and his “Introduction to Error Analysis;” and Don McQuarrie’s “Physical Chemistry: A Molecular Approach” (commonly known as “Big Red”), the second-most adopted physical chemistry textbook in the U.S.

“We are so pleased to have found a new home for USB’s prestigious list of textbooks in the sciences,” says Alix Vance, CEO of AIP Publishing. “With its strong STEM focus, academic rigor, and high production standards, the MIT Press is the perfect partner to continue the publishing legacy of University Science Books.” 

“This acquisition is both a brand and content fit for the MIT Press,” says Amy Brand, director and publisher of the MIT Press. “USB’s respected science list will complement our long-established publishing history of publishing foundational texts in computer science, finance, and economics.”

The MIT Press will take over the USB list as of July 1, with inventory transferring to Penguin Random House Publishing Services, the MIT Press’ sales and distribution partner.

For details regarding University Science Books titles, inventory, and how to order, please contact the MIT Press. 

Established in 1962, The MIT Press is one of the largest and most distinguished university presses in the world and a leading publisher of books and journals at the intersection of science, technology, art, social science, and design.

AIP Publishing is a wholly owned not-for-profit subsidiary of the AIP and supports the charitable, scientific, and educational purposes of AIP through scholarly publishing activities on its behalf and on behalf of our publishing partners.

Supercharged vaccine could offer strong protection with just one dose

By delivering an HIV vaccine candidate along with two adjuvants, researchers showed they could generate many more HIV-targeting B cells in mice.

Researchers at MIT and the Scripps Research Institute have shown that they can generate a strong immune response to HIV with just one vaccine dose, by adding two powerful adjuvants — materials that help stimulate the immune system.

In a study of mice, the researchers showed that this approach produced a much wider diversity of antibodies against an HIV antigen, compared to the vaccine given on its own or with just one of the adjuvants. The dual-adjuvant vaccine accumulated in the lymph nodes and remained there for up to a month, allowing the immune system to build up a much greater number of antibodies against the HIV protein.

This strategy could lead to the development of vaccines that only need to be given once, for infectious diseases including HIV or SARS-CoV-2, the researchers say.

“This approach is compatible with many protein-based vaccines, so it offers the opportunity to engineer new formulations for these types of vaccines across a wide range of different diseases, such as influenza, SARS-CoV-2, or other pandemic outbreaks,” says J. Christopher Love, the Raymond A. and Helen E. St. Laurent Professor of Chemical Engineering at MIT, and a member of the Koch Institute for Integrative Cancer Research and the Ragon Institute of MGH, MIT, and Harvard.

Love and Darrell Irvine, a professor of immunology and microbiology at the Scripps Research Institute, are the senior authors of the study, which appears today in Science Translational Medicine. Kristen Rodrigues PhD ’23 and Yiming Zhang PhD ’25 are the lead authors of the paper.

More powerful vaccines

Most vaccines are delivered along with adjuvants, which help to stimulate a stronger immune response to the antigen. One adjuvant commonly used with protein-based vaccines, including those for hepatitis A and B, is aluminum hydroxide, also known as alum. This adjuvant works by activating the innate immune response, helping the body to form a stronger memory of the vaccine antigen.

Several years ago, Irvine developed another adjuvant based on saponin, an FDA-approved adjuvant derived from the bark of the Chilean soapbark tree. His work showed that nanoparticles containing both saponin and a molecule called MPLA, which promotes inflammation, worked better than saponin on its own. That nanoparticle, known as SMNP, is now being used as an adjuvant for an HIV vaccine that is currently in clinical trials.

Irvine and Love then tried combining alum and SMNP and showed that vaccines containing both of those adjuvants could generate even more powerful immune responses against either HIV or SARS-CoV-2.

In the new paper, the researchers wanted to explore why these two adjuvants work so well together to boost the immune response, specifically the B cell response. B cells produce antibodies that can circulate in the bloodstream and recognize a pathogen if the body is exposed to it again.

For this study, the researchers used an HIV protein called MD39 as their vaccine antigen, and anchored dozens of these proteins to each alum particle, along with SMNP.

After vaccinating mice with these particles, the researchers found that the vaccine accumulated in the lymph nodes — structures where B cells encounter antigens and undergo rapid mutations that generate antibodies with high affinity for a particular antigen. This process takes place within clusters of cells known as germinal centers.

The researchers showed that SMNP and alum helped the HIV antigen to penetrate through the protective layer of cells surrounding the lymph nodes without being broken down into fragments. The adjuvants also helped the antigens to remain intact in the lymph nodes for up to 28 days.

“As a result, the B cells that are cycling in the lymph nodes are constantly being exposed to the antigen over that time period, and they get the chance to refine their solution to the antigen,” Love says.

This approach may mimic what occurs during a natural infection, when antigens can remain in the lymph nodes for weeks, giving the body time to build up an immune response.

Antibody diversity

Single-cell RNA sequencing of B cells from the vaccinated mice revealed that the vaccine containing both adjuvants generated a much more diverse repertoire of B cells and antibodies. Mice that received the dual-adjuvant vaccine produced two to three times more unique B cells than mice that received just one of the adjuvants.

That increase in B cell number and diversity boosts the chances that the vaccine could generate broadly neutralizing antibodies — antibodies that can recognize a variety of strains of a given virus, such as HIV.

“When you think about the immune system sampling all of the possible solutions, the more chances we give it to identify an effective solution, the better,” Love says. “Generating broadly neutralizing antibodies is something that likely requires both the kind of approach that we showed here, to get that strong and diversified response, as well as antigen design to get the right part of the immunogen shown.”

Using these two adjuvants together could also contribute to the development of more potent vaccines against other infectious diseases, with just a single dose.

“What’s potentially powerful about this approach is that you can achieve long-term exposures based on a combination of adjuvants that are already reasonably well-understood, so it doesn’t require a different technology. It’s just combining features of these adjuvants to enable low-dose or potentially even single-dose treatments,” Love says.

The research was funded by the National Institutes of Health; the Koch Institute Support (core) Grant from the National Cancer Institute; the Ragon Institute of MGH, MIT, and Harvard; and the Howard Hughes Medical Institute.

New 3D chips could make electronics faster and more energy-efficient

The low-cost, scalable technology can seamlessly integrate high-speed gallium nitride transistors onto a standard silicon chip.

The advanced semiconductor material gallium nitride will likely be key for the next generation of high-speed communication systems and the power electronics needed for state-of-the-art data centers.

Unfortunately, the high cost of gallium nitride (GaN) and the specialization required to incorporate this semiconductor material into conventional electronics have limited its use in commercial applications.

Now, researchers from MIT and elsewhere have developed a new fabrication process that integrates high-performance GaN transistors onto standard silicon CMOS chips in a way that is low-cost and scalable, and compatible with existing semiconductor foundries.

Their method involves building many tiny transistors on the surface of a GaN chip, cutting out each individual transistor, and then bonding just the necessary number of transistors onto a silicon chip using a low-temperature process that preserves the functionality of both materials.

The cost remains minimal since only a tiny amount of GaN material is added to the chip, but the resulting device can receive a significant performance boost from compact, high-speed transistors. In addition, by separating the GaN circuit into discrete transistors that can be spread over the silicon chip, the new technology is able to reduce the temperature of the overall system.

The researchers used this process to fabricate a power amplifier, an essential component in mobile phones, that achieves higher signal strength and efficiencies than devices with silicon transistors. In a smartphone, this could improve call quality, boost wireless bandwidth, enhance connectivity, and extend battery life.

Because their method fits into standard procedures, it could improve electronics that exist today as well as future technologies. Down the road, the new integration scheme could even enable quantum applications, as GaN performs better than silicon at the cryogenic temperatures essential for many types of quantum computing.

“If we can bring the cost down, improve the scalability, and, at the same time, enhance the performance of the electronic device, it is a no-brainer that we should adopt this technology. We’ve combined the best of what exists in silicon with the best possible gallium nitride electronics. These hybrid chips can revolutionize many commercial markets,” says Pradyot Yadav, an MIT graduate student and lead author of a paper on this method.

He is joined on the paper by fellow MIT graduate students Jinchen Wang and Patrick Darmawi-Iskandar; MIT postdoc John Niroula; senior authors Ulrich L. Rohde, a visiting scientist at the Microsystems Technology Laboratories (MTL), and Ruonan Han, an associate professor in the Department of Electrical Engineering and Computer Science (EECS) and member of MTL; and Tomás Palacios, the Clarence J. LeBel Professor of EECS, and director of MTL; as well as collaborators at Georgia Tech and the Air Force Research Laboratory. The research was recently presented at the IEEE Radio Frequency Integrated Circuits Symposium.

Swapping transistors

Gallium nitride is the second most widely used semiconductor in the world, just after silicon, and its unique properties make it ideal for applications such as lighting, radar systems and power electronics.

The material has been around for decades and, to get access to its maximum performance, it is important for chips made of GaN to be connected to digital chips made of silicon, also called CMOS chips. To enable this, some integration methods bond GaN transistors onto a CMOS chip by soldering the connections, but this limits how small the GaN transistors can be. The tinier the transistors, the higher the frequency at which they can work.

Other methods integrate an entire gallium nitride wafer on top of a silicon wafer, but using so much material is extremely costly, especially since the GaN is only needed in a few tiny transistors. The rest of the material in the GaN wafer is wasted.

“We wanted to combine the functionality of GaN with the power of digital chips made of silicon, but without having to compromise on either cost of bandwidth. We achieved that by adding super-tiny discrete gallium nitride transistors right on top of the silicon chip,” Yadav explains.

The new chips are the result of a multistep process.

First, a tightly packed collection of miniscule transistors is fabricated across the entire surface of a GaN wafer. Using very fine laser technology, they cut each one down to just the size of the transistor, which is 240 by 410 microns, forming what they call a dielet. (A micron is one millionth of a meter.)

Each transistor is fabricated with tiny copper pillars on top, which they use to bond directly to the copper pillars on the surface of a standard silicon CMOS chip. Copper to copper bonding can be done at temperatures below 400 degrees Celsius, which is low enough to avoid damaging either material.

Current GaN integration techniques require bonds that utilize gold, an expensive material that needs much higher temperatures and stronger bonding forces than copper. Since gold can contaminate the tools used in most semiconductor foundries, it typically requires specialized facilities.

“We wanted a process that was low-cost, low-temperature, and low-force, and copper wins on all of those related to gold. At the same time, it has better conductivity,” Yadav says.

A new tool

To enable the integration process, they created a specialized new tool that can carefully integrate the extremely tiny GaN transistor with the silicon chips. The tool uses a vacuum to hold the dielet as it moves on top of a silicon chip, zeroing in on the copper bonding interface with nanometer precision.

They used advanced microscopy to monitor the interface, and then when the dielet is in the right position, they apply heat and pressure to bond the GaN transistor to the chip.

“For each step in the process, I had to find a new collaborator who knew how to do the technique that I needed, learn from them, and then integrate that into my platform. It was two years of constant learning,” Yadav says.

Once the researchers had perfected the fabrication process, they demonstrated it by developing power amplifiers, which are radio frequency circuits that boost wireless signals.

Their devices achieved higher bandwidth and better gain than devices made with traditional silicon transistors. Each compact chip has an area of less than half a square millimeter.

In addition, because the silicon chip they used in their demonstration is based on Intel 16 22nm FinFET state-of-the-art metallization and passive options, they were able to incorporate components often used in silicon circuits, such as neutralization capacitors. This significantly improved the gain of the amplifier, bringing it one step closer to enabling the next generation of wireless technologies.

“To address the slowdown of Moore’s Law in transistor scaling, heterogeneous integration has emerged as a promising solution for continued system scaling, reduced form factor, improved power efficiency, and cost optimization. Particularly in wireless technology, the tight integration of compound semiconductors with silicon-based wafers is critical to realizing unified systems of front-end integrated circuits, baseband processors, accelerators, and memory for next-generation antennas-to-AI platforms. This work makes a significant advancement by demonstrating 3D integration of multiple GaN chips with silicon CMOS and pushes the boundaries of current technological capabilities,” says Atom Watanabe, a research scientist at IBM who was not involved with this paper.

This work is supported, in part, by the U.S. Department of Defense through the National Defense Science and Engineering Graduate (NDSEG) Fellowship Program and CHIMES, one of the seven centers in JUMP 2.0, a Semiconductor Research Corporation Program by the Department of Defense and the Defense Advanced Research Projects Agency (DARPA). Fabrication was carried out using facilities at MIT.Nano, the Air Force Research Laboratory, and Georgia Tech.

Combining technology, education, and human connection to improve online learning

Caitlin Morris, a PhD student and 2024 MAD Fellow affiliated with the MIT Media Lab, designs digital learning platforms that make room for the “social magic” that influences curiosity and motivation.

MIT Morningside Academy for Design (MAD) Fellow Caitlin Morris is an architect, artist, researcher, and educator who has studied psychology and used online learning tools to teach herself coding and other skills. She’s a soft-spoken observer, with a keen interest in how people use space and respond to their environments. Combining her observational skills with active community engagement, she works at the intersection of technology, education, and human connection to improve digital learning platforms.

Morris grew up in rural upstate New York in a family of makers. She learned to sew, cook, and build things with wood at a young age. One of her earlier memories is of a small handsaw she made — with the help of her father, a professional carpenter. It had wooden handles on both sides to make sawing easier for her.

Later, when she needed to learn something, she’d turn to project-based communities, rather than books. She taught herself to code late at night, taking advantage of community-oriented platforms where people answer questions and post sketches, allowing her to see the code behind the objects people made.

“For me, that was this huge, wake-up moment of feeling like there was a path to expression that was not a traditional computer-science classroom,” she says. “I think that’s partly why I feel so passionate about what I’m doing now. That was the big transformation: having that community available in this really personal, project-based way.”

Subsequently, Morris has become involved in community-based learning in diverse ways: She’s a co-organizer of the MIT Media Lab’s Festival of Learning; she leads creative coding community meetups; and she’s been active in the open-source software community development.

“My years of organizing learning and making communities — both in person and online — have shown me firsthand how powerful social interaction can be for motivation and curiosity,” Morris said. “My research is really about identifying which elements of that social magic are most essential, so we can design digital environments that better support those dynamics.”

Even in her artwork, Morris sometimes works with a collective. She’s contributed to the creation of about 10 large art installations that combine movement, sound, imagery, lighting, and other technologies to immerse the visitor in an experience evoking some aspect of nature, such as flowing water, birds in flight, or crowd kinetics. These marvelous installations are commanding and calming at the same time, possibly because they focus the mind, eye, and sometimes the ear.

She did much of this work with New York-based Hypersonic, a company of artists and technologists specializing in large kinetic installations in public spaces. Before that, she earned a BS in psychology and a BS in architectural building sciences from Rensselaer Polytechnic Institute, then an MFA in design and technology from the Parsons School of Design at The New School.

During, in between, after, and sometimes concurrently, she taught design, coding, and other technologies at the high school, undergraduate, and graduate-student levels.

“I think what kind of got me hooked on teaching was that the way I learned as a child was not the same as in the classroom,” Morris explains. “And I later saw this in many of my students. I got the feeling that the normal way of learning things was not working for them. And they thought it was their fault. They just didn’t really feel welcome within the traditional education model.”

Morris says that when she worked with those students, tossing aside tradition and instead saying — “You know, we’re just going to do this animation. Or we’re going to make this design or this website or these graphics, and we’re going to approach it in this totally different way” — she saw people “kind of unlock and be like, ‘Oh my gosh. I never thought I could do that.’

“For me, that was the hook, that’s the magic of it. Because I was coming from that experience of having to figure out those unlock mechanisms for myself, it was really exciting to be able to share them with other people, those unlock moments.”

For her doctoral work with the MIT Media Lab’s Fluid Interfaces Group, she’s focusing on the personal space and emotional gaps associated with learning, particularly online and AI-assisted learning. This research builds on her experience increasing human connection in both physical and virtual learning environments.

“I’m developing a framework that combines AI-driven behavioral analysis with human expert assessment to study social learning dynamics,” she says. “My research investigates how social interaction patterns influence curiosity development and intrinsic motivation in learning, with particular focus on understanding how these dynamics differ between real peers and AI-supported environments.”

The first step in her research is determining which elements of social interaction are not replaceable by an AI-based digital tutor. Following that assessment, her goal is to build a prototype platform for experiential learning.

“I’m creating tools that can simultaneously track observable behaviors — like physical actions, language cues, and interaction patterns — while capturing learners’ subjective experiences through reflection and interviews,” Morris explains. “This approach helps connect what people do with how they feel about their learning experience.

“I aim to make two primary contributions: first, analysis tools for studying social learning dynamics; and second, prototype tools that demonstrate practical approaches for supporting social curiosity in digital learning environments. These contributions could help bridge the gap between the efficiency of digital platforms and the rich social interaction that occurs in effective in-person learning.”

Her goals make Morris a perfect fit for the MIT MAD Fellowship. One statement in MAD’s mission is: “Breaking away from traditional education, we foster creativity, critical thinking, making, and collaboration, exploring a range of dynamic approaches to prepare students for complex, real-world challenges.”

Morris wants to help community organizations deal with the rapid AI-powered changes in education, once she finishes her doctorate in 2026. “What should we do with this ‘physical space versus virtual space’ divide?” she asks. That is the space currently captivating Morris’s thoughts.

Unpacking the bias of large language models

In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.

Research has shown that large language models (LLMs) tend to overemphasize information at the beginning and end of a document or conversation, while neglecting the middle.

This “position bias” means that, if a lawyer is using an LLM-powered virtual assistant to retrieve a certain phrase in a 30-page affidavit, the LLM is more likely to find the right text if it is on the initial or final pages.

MIT researchers have discovered the mechanism behind this phenomenon.

They created a theoretical framework to study how information flows through the machine-learning architecture that forms the backbone of LLMs. They found that certain design choices which control how the model processes input data can cause position bias.

Their experiments revealed that model architectures, particularly those affecting how information is spread across input words within the model, can give rise to or intensify position bias, and that training data also contribute to the problem.

In addition to pinpointing the origins of position bias, their framework can be used to diagnose and correct it in future model designs.

This could lead to more reliable chatbots that stay on topic during long conversations, medical AI systems that reason more fairly when handling a trove of patient data, and code assistants that pay closer attention to all parts of a program.

“These models are black boxes, so as an LLM user, you probably don’t know that position bias can cause your model to be inconsistent. You just feed it your documents in whatever order you want and expect it to work. But by understanding the underlying mechanism of these black-box models better, we can improve them by addressing these limitations,” says Xinyi Wu, a graduate student in the MIT Institute for Data, Systems, and Society (IDSS) and the Laboratory for Information and Decision Systems (LIDS), and first author of a paper on this research.

Her co-authors include Yifei Wang, an MIT postdoc; and senior authors Stefanie Jegelka, an associate professor of electrical engineering and computer science (EECS) and a member of IDSS and the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Ali Jadbabaie, professor and head of the Department of Civil and Environmental Engineering, a core faculty member of IDSS, and a principal investigator in LIDS. The research will be presented at the International Conference on Machine Learning.

Analyzing attention

LLMs like Claude, Llama, and GPT-4 are powered by a type of neural network architecture known as a transformer. Transformers are designed to process sequential data, encoding a sentence into chunks called tokens and then learning the relationships between tokens to predict what words comes next.

These models have gotten very good at this because of the attention mechanism, which uses interconnected layers of data processing nodes to make sense of context by allowing tokens to selectively focus on, or attend to, related tokens.

But if every token can attend to every other token in a 30-page document, that quickly becomes computationally intractable. So, when engineers build transformer models, they often employ attention masking techniques which limit the words a token can attend to.

For instance, a causal mask only allows words to attend to those that came before it.

Engineers also use positional encodings to help the model understand the location of each word in a sentence, improving performance.

The MIT researchers built a graph-based theoretical framework to explore how these modeling choices, attention masks and positional encodings, could affect position bias.

“Everything is coupled and tangled within the attention mechanism, so it is very hard to study. Graphs are a flexible language to describe the dependent relationship among words within the attention mechanism and trace them across multiple layers,” Wu says.

Their theoretical analysis suggested that causal masking gives the model an inherent bias toward the beginning of an input, even when that bias doesn’t exist in the data.

If the earlier words are relatively unimportant for a sentence’s meaning, causal masking can cause the transformer to pay more attention to its beginning anyway.

“While it is often true that earlier words and later words in a sentence are more important, if an LLM is used on a task that is not natural language generation, like ranking or information retrieval, these biases can be extremely harmful,” Wu says.

As a model grows, with additional layers of attention mechanism, this bias is amplified because earlier parts of the input are used more frequently in the model’s reasoning process.

They also found that using positional encodings to link words more strongly to nearby words can mitigate position bias. The technique refocuses the model’s attention in the right place, but its effect can be diluted in models with more attention layers.

And these design choices are only one cause of position bias — some can come from training data the model uses to learn how to prioritize words in a sequence.

“If you know your data are biased in a certain way, then you should also finetune your model on top of adjusting your modeling choices,” Wu says.

Lost in the middle

After they’d established a theoretical framework, the researchers performed experiments in which they systematically varied the position of the correct answer in text sequences for an information retrieval task.

The experiments showed a “lost-in-the-middle” phenomenon, where retrieval accuracy followed a U-shaped pattern. Models performed best if the right answer was located at the beginning of the sequence. Performance declined the closer it got to the middle before rebounding a bit if the correct answer was near the end.

Ultimately, their work suggests that using a different masking technique, removing extra layers from the attention mechanism, or strategically employing positional encodings could reduce position bias and improve a model’s accuracy.

“By doing a combination of theory and experiments, we were able to look at the consequences of model design choices that weren’t clear at the time. If you want to use a model in high-stakes applications, you must know when it will work, when it won’t, and why,” Jadbabaie says.

In the future, the researchers want to further explore the effects of positional encodings and study how position bias could be strategically exploited in certain applications.

“These researchers offer a rare theoretical lens into the attention mechanism at the heart of the transformer model. They provide a compelling analysis that clarifies longstanding quirks in transformer behavior, showing that attention mechanisms, especially with causal masks, inherently bias models toward the beginning of sequences. The paper achieves the best of both worlds — mathematical clarity paired with insights that reach into the guts of real-world systems,” says Amin Saberi, professor and director of the Stanford University Center for Computational Market Design, who was not involved with this work.

This research is supported, in part, by the U.S. Office of Naval Research, the National Science Foundation, and an Alexander von Humboldt Professorship.

This compact, low-power receiver could give a boost to 5G smart devices

Researchers designed a tiny receiver chip that is more resilient to interference, which could enable smaller 5G “internet of things” devices with longer battery lives.

MIT researchers have designed a compact, low-power receiver for 5G-compatible smart devices that is about 30 times more resilient to a certain type of interference than some traditional wireless receivers.

The low-cost receiver would be ideal for battery-powered internet of things (IoT) devices like environmental sensors, smart thermostats, or other devices that need to run continuously for a long time, such as health wearables, smart cameras, or industrial monitoring sensors.

The researchers’ chip uses a passive filtering mechanism that consumes less than a milliwatt of static power while protecting both the input and output of the receiver’s amplifier from unwanted wireless signals that could jam the device.

Key to the new approach is a novel arrangement of precharged, stacked capacitors, which are connected by a network of tiny switches. These miniscule switches need much less power to be turned on and off than those typically used in IoT receivers.

The receiver’s capacitor network and amplifier are carefully arranged to leverage a phenomenon in amplification that allows the chip to use much smaller capacitors than would typically be necessary. 

“This receiver could help expand the capabilities of IoT gadgets. Smart devices like health monitors or industrial sensors could become smaller and have longer battery lives. They would also be more reliable in crowded radio environments, such as factory floors or smart city networks,” says Soroush Araei, an electrical engineering and computer science (EECS) graduate student at MIT and lead author of a paper on the receiver.

He is joined on the paper by Mohammad Barzgari, a postdoc in the MIT Research Laboratory of Electronics (RLE); Haibo Yang, an EECS graduate student; and senior author Negar Reiskarimian, the X-Window Consortium Career Development Assistant Professor in EECS at MIT and a member of the Microsystems Technology Laboratories and RLE. The research was recently presented at the IEEE Radio Frequency Integrated Circuits Symposium.

A new standard

A receiver acts as the intermediary between an IoT device and its environment. Its job is to detect and amplify a wireless signal, filter out any interference, and then convert it into digital data for processing.

Traditionally, IoT receivers operate on fixed frequencies and suppress interference using a single narrow-band filter, which is simple and inexpensive.

But the new technical specifications of the 5G mobile network enable reduced-capability devices that are more affordable and energy-efficient. This opens a range of IoT applications to the faster data speeds and increased network capability of 5G. These next-generation IoT devices need receivers that can tune across a wide range of frequencies while still being cost-effective and low-power.

“This is extremely challenging because now we need to not only think about the power and cost of the receiver, but also flexibility to address numerous interferers that exist in the environment,” Araei says.

To reduce the size, cost, and power consumption of an IoT device, engineers can’t rely on the bulky, off-chip filters that are typically used in devices that operate on a wide frequency range.

One solution is to use a network of on-chip capacitors that can filter out unwanted signals. But these capacitor networks are prone to special type of signal noise known as harmonic interference.

In prior work, the MIT researchers developed a novel switch-capacitor network that targets these harmonic signals as early as possible in the receiver chain, filtering out unwanted signals before they are amplified and converted into digital bits for processing.

Shrinking the circuit

Here, they extended that approach by using the novel switch-capacitor network as the feedback path in an amplifier with negative gain. This configuration leverages the Miller effect, a phenomenon that enables small capacitors to behave like much larger ones.

“This trick lets us meet the filtering requirement for narrow-band IoT without physically large components, which drastically shrinks the size of the circuit,” Araei says.

Their receiver has an active area of less than 0.05 square millimeters.

One challenge the researchers had to overcome was determining how to apply enough voltage to drive the switches while keeping the overall power supply of the chip at only 0.6 volts.

In the presence of interfering signals, such tiny switches can turn on and off in error, especially if the voltage required for switching is extremely low.

To address this, the researchers came up with a novel solution, using a special circuit technique called bootstrap clocking. This method boosts the control voltage just enough to ensure the switches operate reliably while using less power and fewer components than traditional clock boosting methods.

Taken together, these innovations enable the new receiver to consume less than a milliwatt of power while blocking about 30 times more harmonic interference than traditional IoT receivers.

“Our chip also is very quiet, in terms of not polluting the airwaves. This comes from the fact that our switches are very small, so the amount of signal that can leak out of the antenna is also very small,” Araei adds.

Because their receiver is smaller than traditional devices and relies on switches and precharged capacitors instead of more complex electronics, it could be more cost-effective to fabricate. In addition, since the receiver design can cover a wide range of signal frequencies, it could be implemented on a variety of current and future IoT devices.

Now that they have developed this prototype, the researchers want to enable the receiver to operate without a dedicated power supply, perhaps by harvesting Wi-Fi or Bluetooth signals from the environment to power the chip.

This research is supported, in part, by the National Science Foundation.

Gaspare LoDuca named VP for information systems and technology and CIO

Chief information officer at Columbia University will join MIT in August.

Gaspare LoDuca has been appointed MIT’s vice president for information systems and technology (IS&T) and chief information officer, effective Aug. 18. Currently vice president for information technology and CIO at Columbia University, LoDuca has held IT leadership roles in or related to higher education for more than two decades. He succeeds Mark Silis, who led IS&T from 2019 until 2024, when he left MIT to return to the entrepreneurial ecosystem in the San Francisco Bay area.

Executive Vice President and Treasurer Glen Shor announced the appointment today in an email to MIT faculty and staff.

“I believe that Gaspare will be an incredible asset to MIT, bringing wide-ranging experience supporting faculty, researchers, staff, and students and a highly collaborative style,” says Shor. “He is eager to start his work with our talented IS&T team to chart and implement their contributions to the future of information technology at MIT.”

LoDuca will lead the IS&T organization and oversee MIT’s information technology infrastructure and services that support its research and academic enterprise across student and administrative systems, network operations, cloud services, cybersecurity, and customer support. As co-chair of the Information Technology Governance Committee, he will guide the development of IT policy and strategy at the Institute. He will also play a key role in MIT’s effort to modernize its business processes and administrative systems, working in close collaboration with the Business and Digital Transformation Office.

“Gaspare brings to his new role extensive experience leading a complex IT organization,” says Provost Cynthia Barnhart, who served as one of Shor's advisors during the search process. “His depth of experience, coupled with his vision for the future state of information technology and digital transformation at MIT, are compelling, and I am excited to see the positive impact he will have here.”

“As I start my new role, I plan to learn more about MIT’s culture and community to ensure that any decisions or changes we make are shaped by the community’s needs and carried out in a way that fits the culture. I’m also looking forward to learning more about the research and work being done by students and faculty to advance MIT’s mission. It’s inspiring, and I’m eager to support their success,” says LoDuca.

In his role at Columbia, LoDuca has overseen the IT department, headed IT governance committees for school and department-level IT functions, and ensured the secure operation of the university’s enterprise-class systems since 2015. During his tenure, he has crafted a culture of customer service and innovation — building a new student information system, identifying emerging technologies for use in classrooms and labs, and creating a data-sharing platform for university researchers and a grants dashboard for principal investigators. He also revamped Columbia’s technology infrastructure and implemented tools to ensure the security and reliability of its technology resources.

Before joining Columbia, LoDuca was the technology managing director for the education practice at Accenture from 1998 to 2015. In that role, he helped universities to develop and implement technology strategies and adopt modern applications and systems. His projects included overseeing the implementation of finance, human resources, and student administration systems for clients such as Columbia University, University of Miami, Carnegie Mellon University, the University System of Georgia, and Yale University.

“At a research institution, there’s a wide range of activities happening every day, and our job in IT is to support them all while also managing cybersecurity risks. We need to be creative and thoughtful in our solutions, and consider the needs and expectations of our community,” he says.

LoDuca holds a bachelor’s degree in chemical engineering from Michigan State University. He and his wife are recent empty nesters, and are in the process of relocating to Boston.

Closing in on superconducting semiconductors

Plasma Science and Fusion Center researchers created a superconducting circuit that could one day replace semiconductor components in quantum and high-performance computing systems.

In 2023, about 4.4 percent (176 terawatt-hours) of total energy consumption in the United States was by data centers that are essential for processing large quantities of information. Of that 176 TWh, approximately 100 TWh (57 percent) was used by CPU and GPU equipment. Energy requirements have escalated substantially in the past decade and will only continue to grow, making the development of energy-efficient computing crucial. 

Superconducting electronics have arisen as a promising alternative for classical and quantum computing, although their full exploitation for high-end computing requires a dramatic reduction in the amount of wiring linking ambient temperature electronics and low-temperature superconducting circuits. To make systems that are both larger and more streamlined, replacing commonplace components such as semiconductors with superconducting versions could be of immense value. It’s a challenge that has captivated MIT Plasma Science and Fusion Center senior research scientist Jagadeesh Moodera and his colleagues, who described a significant breakthrough in a recent Nature Electronics paper, “Efficient superconducting diodes and rectifiers for quantum circuitry.”

Moodera was working on a stubborn problem. One of the critical long-standing requirements is the need for the efficient conversion of AC currents into DC currents on a chip while operating at the extremely cold cryogenic temperatures required for superconductors to work efficiently. For example, in superconducting “energy-efficient rapid single flux quantum” (ERSFQ) circuits, the AC-to-DC issue is limiting ERSFQ scalability and preventing their use in larger circuits with higher complexities. To respond to this need, Moodera and his team created superconducting diode (SD)-based superconducting rectifiers — devices that can convert AC to DC on the same chip. These rectifiers would allow for the efficient delivery of the DC current necessary to operate superconducting classical and quantum processors.

Quantum computer circuits can only operate at temperatures close to 0 kelvins (absolute zero), and the way power is supplied must be carefully controlled to limit the effects of interference introduced by too much heat or electromagnetic noise. Most unwanted noise and heat come from the wires connecting cold quantum chips to room-temperature electronics. Instead, using superconducting rectifiers to convert AC currents into DC within a cryogenic environment reduces the number of wires, cutting down on heat and noise and enabling larger, more stable quantum systems.

In a 2023 experiment, Moodera and his co-authors developed SDs that are made of very thin layers of superconducting material that display nonreciprocal (or unidirectional) flow of current and could be the superconducting counterpart to standard semiconductors. Even though SDs have garnered significant attention, especially since 2020, up until this point the research has focused only on individual SDs for proof of concept. The group’s 2023 paper outlined how they created and refined a method by which SDs could be scaled for broader application. 

Now, by building a diode bridge circuit, they demonstrated the successful integration of four SDs and realized AC-to-DC rectification at cryogenic temperatures. 

The new approach described in their recent Nature Electronics paper will significantly cut down on the thermal and electromagnetic noise traveling from ambient into cryogenic circuitry, enabling cleaner operation. The SDs could also potentially serve as isolators/circulators, assisting in insulating qubit signals from external influence. The successful assimilation of multiple SDs into the first integrated SD circuit represents a key step toward making superconducting computing a commercial reality. 

“Our work opens the door to the arrival of highly energy-efficient, practical superconductivity-based supercomputers in the next few years,” says Moodera. “Moreover, we expect our research to enhance the qubit stability while boosting the quantum computing program, bringing its realization closer." Given the multiple beneficial roles these components could play, Moodera and his team are already working toward the integration of such devices into actual superconducting logic circuits, including in dark matter detection circuits that are essential to the operation of experiments at CERN and LUX-ZEPLIN in at the Berkeley National Lab.

This work was partially funded by MIT Lincoln Laboratory’s Advanced Concepts Committee, the U.S. National Science Foundation, U.S. Army Research Office, and U.S. Air Force Office of Scientific Research. 

This work was carried out, in part, through the use of MIT.nano’s facilities.

A brief history of the global economy, through the lens of a single barge

Ian Kumekawa’s book “Empty Vessel” explores globalization, economics, and the hazy world of short-term transactions known as “the offshore.”

In 1989, New York City opened a new jail. But not on dry land. The city leased a barge, then called the “Bibby Resolution,” which had been topped with five stories of containers made into housing, and anchored it in the East River. For five years, the vessel lodged inmates.

A floating detention center is a curiosity. But then, the entire history of this barge is curious. Built in 1979 in Sweden, it housed British troops during the Falkland Islands war with Argentina, became worker housing for Volkswagen employees in West Germany, got sent to New York, also became a detention center off the coast of England, then finally was deployed as oil worker housing off the coast of Nigeria. The barge has had nine names, several owners, and flown the flags of five countries.

In this one vessel, then, we can see many currents: globalization, the transience of economic activity, and the hazy world of transactions many analysts and observers call “the offshore,” the lightly regulated sphere of economic activity that encourages short-term actions.

“The offshore presents a quick and potentially cheap solution to a crisis,” says MIT lecturer Ian Kumekawa. “It is not a durable solution. The story of the barge is the story of it being used as a quick fix in all sorts of crises. Then these expediences become the norm, and people get used to them and have an expectation that this is the way the world works.”

Now Kumekawa, a historian who started teaching as a lecturer at MIT earlier this year, explores the ship’s entire history in “Empty Vessel: The Global Economy in One Barge,” just published by Knopf and John Murray. In it, he traces the barge’s trajectory and the many economic and geopolitical changes that helped create the ship’s distinctive deployments around the world.

“The book is about a barge, but it’s also about the developing, emerging offshore world, where you see these layers of globalization, financialization, privatization, and the dissolution of territoriality and orders,” Kumekawa says. “The barge is a vehicle through which I can tell the story of those layers together.”

“Never meant to be permanent”

Kumekawa first found out about the vessel several years ago; New York City obtained another floating detention center in the 1990s, which prompted Kumekawa to start looking into the past of the older jail ship, the former “Bibby Resolution,” from the 1990s. The more he found out about its distinctive past, the more curious he became.

“You start pulling on a thread, and you realize you can keep pulling,” Kumekawa says.

The barge Kumekawa follows in the book was built in Sweden in 1979 as the “Balder Scapa.” Even then, commerce was plenty globalized: The vessel was commissioned by a Norwegian shell company, with negotiations run by an expatriate Swedish shipping agent whose firm was registered in Panama and used a Miami bank.

The barge was built at an inflection point following the economic slowdown and oil shocks of the 1970s. Manufacturing was on the verge of declining in both Western Europe and the U.S.; about half as many people now work in manufacturing in those regions, compared to 1960. Companies were looking to find cheaper global locations for production, reinforcing the sense that economic activity was now less durable in any given place.

The barge became part of this transience. The five-story accommodation block was added in the early 1980s; in 1983 it was re-registered in the UK and sent to the Falkland Islands as a troop accommodation named the “COASTEL 3.” Then it was re-registered in the Bahamas and sent to Emden, West Germany, as housing for Volkswagen workers. The vessel then served its stints as inmate housing — first in New York, then off the coast of England from 1997 to 2005. By 2010, it had been re-re-re-registered, in St. Vincent and Grenadines, and was housing oil workers off the coast of Nigeria.

“Globalization is more about flow than about stocks, and the barge is a great example of that,” Kumekawa says. “It’s always on the move, and never meant to be a permanent container. It’s understood people are going to be passing through.”

As Kumekawa explores in the book, this sense of social dislocation overlapped with the shrinking of state capacity, as many states increasingly encouraged companies to pursue globalized production and lightly regulated financial activities in numerous jurisdictions, in the hope it would enhance growth. And it has, albeit with unresolved questions about who the benefits accrue to, the social dislocation of workers, and more.

“In a certain sense it’s not an erosion of state power at all,” Kumekawa says. “These states are making very active choices to use offshore tools, to circumvent certain roadblocks.” He adds: “What happens in the 1970s and certainly in the 1980s is that the offshore comes into its own as an entity, and didn’t exist in the same way even in the 1950s and 1960s. There’s a money interest in that, and there’s a political interest as well.”

Abstract forces, real materials and people

Kumekawa is a scholar with a strong interest in economic history; his previous book, “The First Serious Optimist: A.C. Pigou and the Birth of Welfare Economics,” was published in 2017. This coming fall, Kumekawa will be team-teaching a class on the relationship between economics and history, along with MIT economists Abhijit Banerjee and Jacob Moscona.

Working on “Empty Vessel” also necessitated that Kumekawa use a variety of research techniques, from archival work to journalistic interviews with people who knew the vessel well.

“I had a wonderful set of conversations with the man who was the last bargemaster,” Kumekawa says. “He was the person in effect steering the vessel for many years. He was so aware of all of the forces at play — the market for oil, the prices of accommodations, the regulations, the fact no one had reinforced the frame.”

“Empty Vessel” has already received critical acclaim. Reviewing it in The New York Times, Jennifer Szalai writes that this “elegant and enlightening book is an impressive feat.”

For his part, Kumekawa also took inspiration from a variety of writings about ships, voyages, commerce, and exploration, recognizing that these vessels contain stories and vignettes that illuminate the wider world.

“Ships work very well as devices connecting the global and the local,” he says. Using the barge as the organizing principle of his book, Kumekawa adds, “makes a whole bunch of abstract processes very concrete. The offshore itself is an abstraction, but it’s also entirely dependent on physical infrastructure and physical places. My hope for the book is it reinforces the material dimension of these abstract global forces.”

Students and staff work together for MIT’s first “No Mow May”

With advocacy from GSC Sustain, the No Mow May project supports pollinator habitats and provides educational opportunities.

In recent years, some grass lawns around the country have grown a little taller in springtime thanks to No Mow May, a movement originally launched by U.K. nonprofit Plantlife in 2019 designed to raise awareness about the ecological impacts of the traditional, resource-intensive, manicured grass lawn. No Mow May encourages people to skip spring mowing to allow for grass to grow tall and provide food and shelter for beneficial creatures including bees, beetles, and other pollinators.

This year, MIT took part in the practice for the first time, with portions of the Kendall/MIT Open Space, Bexley Garden, and the Tang Courtyard forgoing mowing from May 1 through June 6 to make space for local pollinators, decrease water use, and encourage new thinking about the traditional lawn. MIT’s first No Mow May was the result of championing by the Graduate Student Council Sustainability Subcommittee (GSC Sustain) and made possible by the Office of the Vice Provost for Campus Space Management and Planning. 

A student idea sprouts

Despite being a dense urban campus, MIT has no shortage of green spaces — from pocket gardens and community-managed vegetable plots to thousands of shade trees — and interest in these spaces continues to grow. In recent years, student-led initiatives supported by Institute leadership and operational staff have transformed portions of campus by increasing the number of native pollinator plants and expanding community gardens, like the Hive Garden. With No Mow May, these efforts stepped out of the garden and into MIT’s many grassy open spaces. 

“The idea behind it was to raise awareness for more sustainable and earth-friendly lawn practices,” explains Gianmarco Terrones, GSC Sustain member. Those practices include reducing the burden of mowing, limiting use of fertilizers, and providing shelter and food for pollinators. “The insects that live in these spaces are incredibly important in terms of pollination, but they’re also part of the food chain for a lot of animals,” says Terrones. 

Research has shown that holding off on mowing in spring, even in small swaths of green space, can have an impact. The early months of spring have the lowest number of flowers in regions like New England, and providing a resource and refuge — even for a short duration — can support fragile pollinators like bees. Additionally, No Mow May aims to help people rethink their yards and practices, which are not always beneficial for local ecosystems. 

Signage at each No Mow site on campus highlighted information on local pollinators, the impact of the project, and questions for visitors to ask themselves. “Having an active sign there to tell people, ‘look around. How many butterflies do you see after six weeks of not mowing? Do you see more? Do you see more bees?’ can cause subtle shifts in people’s awareness of ecosystems,” says GSC Sustain member Mingrou Xie. A mowed barrier around each project also helped visitors know that areas of tall grass at No Mow sites are intentional.

Campus partners bring sustainable practices to life

To make MIT’s No Mow May possible, GSC Sustain members worked with the Office of the Vice Provost and the Open Space Working Group, co-chaired by Vice Provost for Campus Space Management and Planning Brent Ryan and Director of Sustainability Julie Newman. The Working Group, which also includes staff from Open Space Programming, Campus Planning, and faculty in the School of Architecture and Planning, helped to identify potential No Mow locations and develop strategies for educational signage and any needed maintenance. “Massachusetts is a biodiverse state, and No Mow May provides an exciting opportunity for MIT to support that biodiversity on its own campus,” says Ryan. 

Students were eager for space on campus with high visibility, and the chosen locations of the Kendall/MIT Open Space, Bexley Garden, and the Tang Courtyard fit the bill. “We wanted to set an example and empower the community to feel like they can make a positive change to an environment they spend so much time in,” says Xie. 

For GSC Sustain, that positive change also takes the form of the Native Plant Project, which they launched in 2022 to increase the number of Massachusetts-native pollinator plants on campus — plants like swamp milkweed, zigzag goldenrod, big leaf aster, and red columbine, with which native pollinators have co-evolved. Partnering with the Open Space Working Group, GSC Sustain is currently focused on two locations for new native plant gardens — the President’s Garden and the terrace gardens at the E37 Graduate Residence. “Our short-term goal is to increase the number of native [plants] on campus, but long term we want to foster a community of students and staff interested in supporting sustainable urban gardening,” says Xie.

Campus as a test bed continues to grow

After just a few weeks of growing, the campus No Mow May locations sprouted buttercups, mouse ear chickweed, and small tree saplings, highlighting the diversity waiting dormant in the average lawn. Terrones also notes other discoveries: “It’s been exciting to see how much the grass has sprung up these last few weeks. I thought the grass would all grow at the same rate, but as May has gone on the variations in grass height have become more apparent, leading to non-uniform lawns with a clearly unmanicured feel,” he says. “We hope that members of MIT noticed how these lawns have evolved over the span of a few weeks and are inspired to implement more earth-friendly lawn practices in their own homes/spaces.”

No Mow May and the Native Plant Project fit into MIT’s overall focus on creating resilient ecosystems that support and protect the MIT community and the beneficial critters that call it home. MIT Grounds Services has long included native plants in the mix of what is grown on campus and native pollinator gardens, like the Hive Garden, have been developed and cared for through partnerships with students and Grounds Services in recent years. Grounds, along with consultants that design and install our campus landscape projects, strive to select plants that assist us with meeting sustainability goals, like helping with stormwater runoff and cooling. No Mow May can provide one more data point for the iterative process of choosing the best plants and practices for a unique microclimate like the MIT campus.

“We are always looking for new ways to use our campus as a test bed for sustainability,” says Director of Sustainability Julie Newman. “Community-led projects like No Mow May help us to learn more about our campus and share those lessons with the larger community.”

The Office of the Vice Provost, the Open Space Working Group, and GSC Sustain will plan to reconnect in the fall for a formal debrief of the project and its success. Given the positive community feedback, future possibilities of expanding or extending No Mow May will be discussed.

Anantha Chandrakasan named MIT provost

A faculty member since 1994, Chandrakasan has also served as dean of engineering and MIT’s inaugural chief innovation and strategy officer, among other roles.

Anantha Chandrakasan, a professor of electrical engineering and computer science who has held multiple leadership roles at MIT, has been named the Institute’s new provost, effective July 1.

Chandrakasan has served as the dean of the School of Engineering since 2017 and as MIT’s inaugural chief innovation and strategy officer since 2024. Prior to becoming dean, he headed the Department of Electrical Engineering and Computer Science (EECS), MIT’s largest academic department, for six years.

“Anantha brings to this post an exceptional record of shaping and leading important innovations for the Institute,” wrote MIT President Sally Kornbluth, in an email announcing the decision to the MIT community today. “I am particularly grateful that we will be able to draw on Anantha’s depth and breadth of experience; his nimbleness, entrepreneurial spirit and boundless energy; his remarkable record in raising funds from outside sources for important ideas; and his profound commitment to MIT’s mission.”

Startup’s biosensor makes drug development and manufacturing cheaper

Protein sensor developed by alumna-founded Advanced Silicon Group can be used for research and quality control in biomanufacturing.

In the biotech and pharmaceutical industries, ELISA tests provide critical quality control during drug development and manufacturing. The tests can precisely quantify protein levels, but they also require hours of work by trained technicians and specialized equipment. That makes them prohibitively expensive, driving up the costs of drugs and putting research testing out of reach for many.

Now the Advanced Silicon Group (ASG), founded by Marcie Black ’94, MEng ’95, PhD ’03 and Bill Rever, is commercializing a new technology that could dramatically lower the time and costs associated with protein sensing. ASG’s proprietary sensor combines silicon nanowires with antibodies that can bind to different proteins to create a highly sensitive measurement of their concentration in a given solution.

The tests can measure the concentration of many different proteins and other molecules at once, with results typically available in less than 15 minutes. Users simply place a tiny amount of solution on the sensor, rinse the sensor, and then insert it into ASG’s handheld testing system.

“We’re making it 15 times faster and 15 times lower cost to test for proteins,” Black says. “That’s on the drug development side. This could also make the manufacturing of drugs significantly faster and more cost-effective. It could revolutionize how we create drugs in this country and around the world.”

Since developing its sensor, ASG’s team has received inquiries from a long list of people interested in using them to develop new therapeutics, help elite athletes train, and understand soil concentrations in agriculture, among other applications.

For now, though, the small company is focusing on lowering barriers in health care by selling its low-cost sensors to companies developing and manufacturing drugs.

“Right now, money is a limiting factor in researching and creating new drugs,” explains Marissa Gillis, a member of ASG’s team. “Making these processes faster and less costly could dramatically increase the amount of biologic testing and creation. It also makes it more viable for companies to develop drugs for rare conditions with smaller markets.”

A family away from home

Black grew up in a small town in Ohio before coming to MIT for three degrees in electrical engineering.

“Going to MIT changed my life,” Black says. “It opened my eyes to the possibilities of doing science and engineering to make the world a better place. Also, just being around so many amazing people taught me how to dream big.”

For her PhD, Black worked with the late Institute Professor Mildred Dresselhaus, a highly acclaimed physicist and nanotechnology pioneer who Black remembers for her mentorship and compassion as much as her contributions to our understanding of exotic materials. Black couldn’t always afford to go home for holidays, so she’d spend Thanksgivings with the Dresselhaus family.

“Millie was an amazing person, and her family was a family away from home for me,” Black says. “Millie continued to be my mentor — and I hear she did this with a lot of students — until the day she died.”

For her thesis, Black studied the optical properties of nanowires, which taught her about the nanostructures and optoelectronics she’d eventually use as part of the Advanced Silicon Group.

Following graduation, Black worked at the Los Alamos National Laboratory before founding the company Bandgap Engineering, which developed efficient, low-cost nanostructured solar cells. That technology was subsequently commercialized by other companies and became the subject of a patent dispute. In 2015, Black spun out the Advanced Silicon Group to apply a similar technology to protein sensing.

ASG’s sensors combine known approaches for sensitizing silicon to biological molecules, using the photoelectric properties of silicon nanowires to detect proteins electrically.

“It’s basically a solar cell that we functionalize with an antibody that’s specific to a certain protein,” Black says. “When the protein gets close, it brings an electrical charge with it that will repel light carriers inside the silicon, and doing that changes how well the electron and the holes can recombine. By looking at the photocurrent when you’re exposed to a solution, you can tell how much protein is bound to the surface and thus the concentration of that protein.”

ASG was accepted into MIT.nano’s START.nano startup accelerator and MIT’s Office of Corporate Relations Startup Exchange Program soon after its founding, which gave Black’s team access to cutting-edge equipment at MIT and connected her with potential investors and partners.

Black has also received broad support from MIT’s Venture Mentoring Service and worked with researchers from MIT’s Microsystems Technology Laboratories (MTL), where she conducted research as a student.

“Even though the company is in Lowell, [Massachusetts], I’m constantly going to MIT and getting help from professors and researchers at MIT,” Black says.

Biosensing for impact

From extensive discussions with people in the pharmaceutical industry, Black learned about the need for a more affordable protein-measurement tool. During drug development and manufacturing, protein levels must be measured to detect problems such as contamination from host cell proteins, which can be fatal to patients even at very low quantities.

“It can cost more than $1 billion to develop a drug,” Black says. “A big part of the process is bioprocessing, and 50 to 80 percent of bioprocessing is dedicated to purifying these unwanted proteins. That challenge leads to drugs being more expensive and taking longer to get to market.”

ASG has since worked with researchers to develop tests for biomarkers associated with lung cancer and dormant tuberculosis and has received multiple grants from the National Science Foundation, the National Institute of Standards and Technology, and the commonwealth of Massachusetts, including funding to develop tests for host cell proteins.

This year, ASG announced a partnership with Axogen to help the regenerative nerve repair company grow nerve tissue.

“There’s a lot of interest in using our sensor for applications in regenerative medicine,” Black says. “Another example we envision is if you’re sick in rural India and there’s no doctor nearby, you can show up at a clinic, nurses can give this to you and test for the flu, Covid-19, food poisoning, pregnancy, and 10 other things all at once. The results come in 15 minutes, then you could get what you need or teleconference a doctor.”

ASG is currently able to produce about 2,000 of its sensors on 8-inch chips per production line in its partner’s semiconductor foundry. As the company continues scaling up production, Black is hopeful the sensors will lower costs at every step between drug developers and patients.

“We really want to lower the barriers for testing so that everyone has access to good health care,” Black says. “Beyond that, there are so many applications for protein sensing. It’s really where the rubber hits the road in biology, agriculture, diagnostics. We’re excited to partner with leaders in every one of these industries.”

Tiny organisms, huge implications for people

A new book by Thomas Levenson examines how germ theory arose, launched modern medicine, and helped us limit fatal infectious diseases.

Back in 1676, a Dutch cloth merchant with a keen interest in microscopes, Antony van Leeuwenhoek, discovered microbes and began cataloging them. Two hundred years later, a German doctor in current-day Poland, Robert Koch, identified the anthrax bacterium, a crucial step toward modern germ theory. Those two signal advances, with others, have helped create the conditions of modern living as we know it.

After all, germ theory led to modern medical advances that have drastically limited deaths from infectious diseases. In the U.S. in 1900, the leading causes of death were pneumonia, influenza, tuberculosis, and gut infection, which combined for close to half of the country’s fatalities. For that matter, due to the threat of disease, childhood was a precarious thing more or less from the start of civilization until the last half-century.

“The world we’ve experienced since the 1950s, and really since the 1970s, is unprecedented in human history,” says MIT Professor Thomas Levenson. “Think of all the grandparents able to dance at their grandkids’ weddings who would not have been able to, because either they or the kids would have died from one of these diseases. Human flourishing has come from this extraordinary scientific development.”

To Levenson, two things about this historical trajectory stand out. One is that it took 200 years to develop germ theory. Another is our ability to combat these diseases so thoroughly — something he believes we should not take for granted.

Now in a new book, “So Very Small: How Humans Discovered the Microcosmos, Defeated Germs — and May Still Lose the War against Infectious Disease,” published by Penguin Random House, Levenson explores both these issues, crafting a historically rich narrative with relevance today. In writing about the development of germ theory, Levenson says, he is aiming to better illuminate “the single most lifesaving tool that human ingenuity has ever come up with.”

A 200-year incubation period

The starting point of Levenson’s research was the simple fact that van Leeuwenhoek’s discovery — accompanied by his illustrations of microbes we can identify today — did not lead to concrete advances for a long, long time.

“It’s almost exactly 200 years between the discovery of bacteria and the definitive proof that they matter to us in life-and-death ways,” Levenson says. “Infectious disease is a big deal and yet it took two centuries to get there. And I wanted to know why.”

Among other things, a variety of ideas, often about the structure of society, blocked the way. The common notion of a “great chain of being” steered people away from the idea that microorganisms could affect human health. Still, some people did recognize the possibility that tiny creatures might be spreading disease. In the late 1600s, the Puritan clergyman Cotton Mather wondered if specific types of “animacules” might each be responsible for spreading different diseases.

Into the 19th century, a few intellectually lonely figures recognized the significance of microbes in the spread of infectious disease, without their ideas gaining much traction. An 18th-century physician in Aberdeen, Scotland, Alexander Gordon, traced the spread of puerperal fever — a disease that killed new mothers — to something doctors and midwives carried on their hands as they delivered babies. A few decades later a doctor in Vienna, Ignaz Semmelweis, deduced that doctors performing autopsies were spreading illness into maternity wards. But skeptics doubted that respectable, gentlemanly doctors could be vectors of disease, and for decades, little was done to prevent the spread of infection.

Eventually, as Levenson chronicles, more scientists, especially Louis Pasteur in France, accumulated enough evidence to establish bacteriology as a field. Medicine advanced through much of the 20th century to the point where, in the postwar years in the U.S., vaccines and antibiotics had enormously reduced human deaths and suffering.

Ultimately, acceptance of new ideas like microbes causing disease involve “how strong cultural presuppositions are and how strong the hierarchical organization of society is,” Levenson says. “If you think you’ve shown that doctors can carry infections from patient to patient, but other people can’t entertain that insight because of other assumptions, that tells you why it took so long to arrive at germ theory. The facts of the science may win out in the end, but even if they do, the end can be delayed.”

He adds: “It can happen when a solution then gets entangled with things that have nothing to do with science.”

Science and society

Understanding that entanglement, between science and society, is a key part of “So Very Small,” as it is in Levenson’s numerous books and other works. Science almost never stands apart from society. The question is how they interact, in any given circumstance.

“One of the themes of my work is how science really works, as opposed to how we’re told it works,” Levenson says. “It’s not simply an ongoing iterative machine to generate new knowledge and hypotheses. Science is a huge human endeavor. The human beings who do it have their own beliefs and cultural assumptions, and are part of larger societies which they interact with all the time, and which have their own characteristics. Those things matter a lot to what science gets done, and how. And that’s still true.”

To be sure, infectious diseases have never entirely been a thing of the past. Some are still prevalent in developing countries, while Covid and the HIV/AIDS epidemics are cases where new medical treatments needed to be developed to staunch emerging illnesses. Still, as Levenson observes in the book, the interplay of science and society may produce yet more uncertainties for us in the future. Antibiotics can lose effectiveness over time, for one thing.

“If we want new antibiotics that can defeat bacterial infections, we need to fund research into them and market them and regulate them,” Levenson says. “That isn’t a political statement. Bacteria do what they do, they evolve when they are challenged.” Meanwhile, he notes, while “there has always been [human] resistance to vaccines,” the greater prevalence of that today introduces new questions about how widely vaccines will be available and used.

“So Very Small” has earned strongly positive reviews in major publications. The Wall Street Journal stated that “With extraordinary detail and authoritative prose … What Mr. Levenson’s book makes clear is that the battle against germs never ends.” The New York Review of Books has called it “an elegant, wide-ranging history of the discovery of microorganisms and their relation to disease.”

Ultimately, Levenson says, “Science both gives us the material power that drives changes in society, that drives history, and science is done by people who are embedded in places and times. Looking at that is a wonderful way into bigger questions. That’s true of germ theory as well. It tells you a great deal about what societies value, and probes the society we now live in.”

Photonic processor could streamline 6G wireless signal processing

By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.

As more connected devices demand an increasing amount of bandwidth for tasks like teleworking and cloud computing, it will become extremely challenging to manage the finite amount of wireless spectrum available for all users to share.

Engineers are employing artificial intelligence to dynamically manage the available wireless spectrum, with an eye toward reducing latency and boosting performance. But most AI methods for classifying and processing wireless signals are power-hungry and can’t operate in real-time.

Now, MIT researchers have developed a novel AI hardware accelerator that is specifically designed for wireless signal processing. Their optical processor performs machine-learning computations at the speed of light, classifying wireless signals in a matter of nanoseconds.

The photonic chip is about 100 times faster than the best digital alternative, while converging to about 95 percent accuracy in signal classification. The new hardware accelerator is also scalable and flexible, so it could be used for a variety of high-performance computing applications. At the same time, it is smaller, lighter, cheaper, and more energy-efficient than digital AI hardware accelerators.

The device could be especially useful in future 6G wireless applications, such as cognitive radios that optimize data rates by adapting wireless modulation formats to the changing wireless environment.

By enabling an edge device to perform deep-learning computations in real-time, this new hardware accelerator could provide dramatic speedups in many applications beyond signal processing. For instance, it could help autonomous vehicles make split-second reactions to environmental changes or enable smart pacemakers to continuously monitor the health of a patient’s heart.

“There are many applications that would be enabled by edge devices that are capable of analyzing wireless signals. What we’ve presented in our paper could open up many possibilities for real-time and reliable AI inference. This work is the beginning of something that could be quite impactful,” says Dirk Englund, a professor in the MIT Department of Electrical Engineering and Computer Science, principal investigator in the Quantum Photonics and Artificial Intelligence Group and the Research Laboratory of Electronics (RLE), and senior author of the paper.

He is joined on the paper by lead author Ronald Davis III PhD ’24; Zaijun Chen, a former MIT postdoc who is now an assistant professor at the University of Southern California; and Ryan Hamerly, a visiting scientist at RLE and senior scientist at NTT Research. The research appears today in Science Advances.

Light-speed processing  

State-of-the-art digital AI accelerators for wireless signal processing convert the signal into an image and run it through a deep-learning model to classify it. While this approach is highly accurate, the computationally intensive nature of deep neural networks makes it infeasible for many time-sensitive applications.

Optical systems can accelerate deep neural networks by encoding and processing data using light, which is also less energy intensive than digital computing. But researchers have struggled to maximize the performance of general-purpose optical neural networks when used for signal processing, while ensuring the optical device is scalable.

By developing an optical neural network architecture specifically for signal processing, which they call a multiplicative analog frequency transform optical neural network (MAFT-ONN), the researchers tackled that problem head-on.

The MAFT-ONN addresses the problem of scalability by encoding all signal data and performing all machine-learning operations within what is known as the frequency domain — before the wireless signals are digitized.

The researchers designed their optical neural network to perform all linear and nonlinear operations in-line. Both types of operations are required for deep learning.

Thanks to this innovative design, they only need one MAFT-ONN device per layer for the entire optical neural network, as opposed to other methods that require one device for each individual computational unit, or “neuron.”

“We can fit 10,000 neurons onto a single device and compute the necessary multiplications in a single shot,” Davis says.   

The researchers accomplish this using a technique called photoelectric multiplication, which dramatically boosts efficiency. It also allows them to create an optical neural network that can be readily scaled up with additional layers without requiring extra overhead.

Results in nanoseconds

MAFT-ONN takes a wireless signal as input, processes the signal data, and passes the information along for later operations the edge device performs. For instance, by classifying a signal’s modulation, MAFT-ONN would enable a device to automatically infer the type of signal to extract the data it carries.

One of the biggest challenges the researchers faced when designing MAFT-ONN was determining how to map the machine-learning computations to the optical hardware.

“We couldn’t just take a normal machine-learning framework off the shelf and use it. We had to customize it to fit the hardware and figure out how to exploit the physics so it would perform the computations we wanted it to,” Davis says.

When they tested their architecture on signal classification in simulations, the optical neural network achieved 85 percent accuracy in a single shot, which can quickly converge to more than 99 percent accuracy using multiple measurements.  MAFT-ONN only required about 120 nanoseconds to perform entire process.

“The longer you measure, the higher accuracy you will get. Because MAFT-ONN computes inferences in nanoseconds, you don’t lose much speed to gain more accuracy,” Davis adds.

While state-of-the-art digital radio frequency devices can perform machine-learning inference in a microseconds, optics can do it in nanoseconds or even picoseconds.

Moving forward, the researchers want to employ what are known as multiplexing schemes so they could perform more computations and scale up the MAFT-ONN. They also want to extend their work into more complex deep learning architectures that could run transformer models or LLMs.

This work was funded, in part, by the U.S. Army Research Laboratory, the U.S. Air Force, MIT Lincoln Laboratory, Nippon Telegraph and Telephone, and the National Science Foundation.

Have a damaged painting? Restore it in just hours with an AI-generated “mask”

A new method can physically restore original paintings using digitally constructed films, which can be removed if desired.

Art restoration takes steady hands and a discerning eye. For centuries, conservators have restored paintings by identifying areas needing repair, then mixing an exact shade to fill in one area at a time. Often, a painting can have thousands of tiny regions requiring individual attention. Restoring a single painting can take anywhere from a few weeks to over a decade.

In recent years, digital restoration tools have opened a route to creating virtual representations of original, restored works. These tools apply techniques of computer vision, image recognition, and color matching, to generate a “digitally restored” version of a painting relatively quickly.

Still, there has been no way to translate digital restorations directly onto an original work, until now. In a paper appearing today in the journal Nature, Alex Kachkine, a mechanical engineering graduate student at MIT, presents a new method he’s developed to physically apply a digital restoration directly onto an original painting.

The restoration is printed on a very thin polymer film, in the form of a mask that can be aligned and adhered to an original painting. It can also be easily removed. Kachkine says that a digital file of the mask can be stored and referred to by future conservators, to see exactly what changes were made to restore the original painting.

“Because there’s a digital record of what mask was used, in 100 years, the next time someone is working with this, they’ll have an extremely clear understanding of what was done to the painting,” Kachkine says. “And that’s never really been possible in conservation before.”

As a demonstration, he applied the method to a highly damaged 15th century oil painting. The method automatically identified 5,612 separate regions in need of repair, and filled in these regions using 57,314 different colors. The entire process, from start to finish, took 3.5 hours, which he estimates is about 66 times faster than traditional restoration methods.

Kachkine acknowledges that, as with any restoration project, there are ethical issues to consider, in terms of whether a restored version is an appropriate representation of an artist’s original style and intent. Any application of his new method, he says, should be done in consultation with conservators with knowledge of a painting’s history and origins.

“There is a lot of damaged art in storage that might never be seen,” Kachkine says. “Hopefully with this new method, there’s a chance we’ll see more art, which I would be delighted by.”

Digital connections

The new restoration process started as a side project. In 2021, as Kachkine made his way to MIT to start his PhD program in mechanical engineering, he drove up the East Coast and made a point to visit as many art galleries as he could along the way.

“I’ve been into art for a very long time now, since I was a kid,” says Kachkine, who restores paintings as a hobby, using traditional hand-painting techniques. As he toured galleries, he came to realize that the art on the walls is only a fraction of the works that galleries hold. Much of the art that galleries acquire is stored away because the works are aged or damaged, and take time to properly restore.

“Restoring a painting is fun, and it’s great to sit down and infill things and have a nice evening,” Kachkine says. “But that’s a very slow process.”

As he has learned, digital tools can significantly speed up the restoration process. Researchers have developed artificial intelligence algorithms that quickly comb through huge amounts of data. The algorithms learn connections within this visual data, which they apply to generate a digitally restored version of a particular painting, in a way that closely resembles the style of an artist or time period. However, such digital restorations are usually displayed virtually or printed as stand-alone works and cannot be directly applied to retouch original art.

“All this made me think: If we could just restore a painting digitally, and effect the results physically, that would resolve a lot of pain points and drawbacks of a conventional manual process,” Kachkine says.

“Align and restore”

For the new study, Kachkine developed a method to physically apply a digital restoration onto an original painting, using a 15th-century painting that he acquired when he first came to MIT. His new method involves first using traditional techniques to clean a painting and remove any past restoration efforts.

“This painting is almost 600 years old and has gone through conservation many times,” he says. “In this case there was a fair amount of overpainting, all of which has to be cleaned off to see what’s actually there to begin with.”

He scanned the cleaned painting, including the many regions where paint had faded or cracked. He then used existing artificial intelligence algorithms to analyze the scan and create a virtual version of what the painting likely looked like in its original state.

Then, Kachkine developed software that creates a map of regions on the original painting that require infilling, along with the exact colors needed to match the digitally restored version. This map is then translated into a physical, two-layer mask that is printed onto thin polymer-based films. The first layer is printed in color, while the second layer is printed in the exact same pattern, but in white.

“In order to fully reproduce color, you need both white and color ink to get the full spectrum,” Kachkine explains. “If those two layers are misaligned, that’s very easy to see. So I also developed a few computational tools, based on what we know of human color perception, to determine how small of a region we can practically align and restore.”

Kachkine used high-fidelity commercial inkjets to print the mask’s two layers, which he carefully aligned and overlaid by hand onto the original painting and adhered with a thin spray of conventional varnish. The printed films are made from materials that can be easily dissolved with conservation-grade solutions, in case conservators need to reveal the original, damaged work. The digital file of the mask can also be saved as a detailed record of what was restored.

For the painting that Kachkine used, the method was able to fill in thousands of losses in just a few hours. “A few years ago, I was restoring this baroque Italian painting with probably the same order magnitude of losses, and it took me nine months of part-time work,” he recalls. “The more losses there are, the better this method is.”

He estimates that the new method can be orders of magnitude faster than traditional, hand-painted approaches. If the method is adopted widely, he emphasizes that conservators should be involved at every step in the process, to ensure that the final work is in keeping with an artist’s style and intent.

“It will take a lot of deliberation about the ethical challenges involved at every stage in this process to see how can this be applied in a way that’s most consistent with conservation principles,” he says. “We’re setting up a framework for developing further methods. As others work on this, we’ll end up with methods that are more precise.”

This work was supported, in part, by the John O. and Katherine A. Lutz Memorial Fund. The research was carried out, in part, through the use of equipment and facilities at MIT.Nano, with additional support from the MIT Microsystems Technology Laboratories, the MIT Department of Mechanical Engineering, and the MIT Libraries.

Window-sized device taps the air for safe drinking water

MIT engineers developed an atmospheric water harvester that produces fresh water anywhere — even Death Valley, California.

Today, 2.2 billion people in the world lack access to safe drinking water. In the United States, more than 46 million people experience water insecurity, living with either no running water or water that is unsafe to drink. The increasing need for drinking water is stretching traditional resources such as rivers, lakes, and reservoirs.

To improve access to safe and affordable drinking water, MIT engineers are tapping into an unconventional source: the air. The Earth’s atmosphere contains millions of billions of gallons of water in the form of vapor. If this vapor can be efficiently captured and condensed, it could supply clean drinking water in places where traditional water resources are inaccessible.

With that goal in mind, the MIT team has developed and tested a new atmospheric water harvester and shown that it efficiently captures water vapor and produces safe drinking water across a range of relative humidities, including dry desert air.

The new device is a black, window-sized vertical panel, made from a water-absorbent hydrogel material, enclosed in a glass chamber coated with a cooling layer. The hydrogel resembles black bubble wrap, with small dome-shaped structures that swell when the hydrogel soaks up water vapor. When the captured vapor evaporates, the domes shrink back down in an origami-like transformation. The evaporated vapor then condenses on the the glass, where it can flow down and out through a tube, as clean and drinkable water.

The system runs entirely on its own, without a power source, unlike other designs that require batteries, solar panels, or electricity from the grid. The team ran the device for over a week in Death Valley, California — the driest region in North America. Even in very low-humidity conditions, the device squeezed drinking water from the air at rates of up to 160 milliliters (about two-thirds of a cup) per day.

The team estimates that multiple vertical panels, set up in a small array, could passively supply a household with drinking water, even in arid desert environments. What’s more, the system’s water production should increase with humidity, supplying drinking water in temperate and tropical climates.

“We have built a meter-scale device that we hope to deploy in resource-limited regions, where even a solar cell is not very accessible,” says Xuanhe Zhao, the Uncas and Helen Whitaker Professor of Mechanical Engineering and Civil and Environmental Engineering at MIT. “It’s a test of feasibility in scaling up this water harvesting technology. Now people can build it even larger, or make it into parallel panels, to supply drinking water to people and achieve real impact.”

Zhao and his colleagues present the details of the new water harvesting design in a paper appearing today in the journal Nature Water. The study’s lead author is former MIT postdoc “Will” Chang Liu, who is currently an assistant professor at the National University of Singapore (NUS). MIT co-authors include Xiao-Yun Yan, Shucong Li, and Bolei Deng, along with collaborators from multiple other institutions.

Carrying capacity

Hydrogels are soft, porous materials that are made mainly from water and a microscopic network of interconnecting polymer fibers. Zhao’s group at MIT has primarily explored the use of hydrogels in biomedical applications, including adhesive coatings for medical implants, soft and flexible electrodes, and noninvasive imaging stickers.

“Through our work with soft materials, one property we know very well is the way hydrogel is very good at absorbing water from air,” Zhao says.

Researchers are exploring a number of ways to harvest water vapor for drinking water. Among the most efficient so far are devices made from metal-organic frameworks, or MOFs — ultra-porous materials that have also been shown to capture water from dry desert air. But the MOFs do not swell or stretch when absorbing water, and are limited in vapor-carrying capacity.

Water from air

The group’s new hydrogel-based water harvester addresses another key problem in similar designs. Other groups have designed water harvesters out of micro- or nano-porous hydrogels. But the water produced from these designs can be salty, requiring additional filtering. Salt is a naturally absorbent material, and researchers embed salts — typically, lithium chloride — in hydrogel to increase the material’s water absorption. The drawback, however, is that this salt can leak out with the water when it is eventually collected.

The team’s new design significantly limits salt leakage. Within the hydrogel itself, they included an extra ingredient: glycerol, a liquid compound that naturally stabilizes salt, keeping it within the gel rather than letting it crystallize and leak out with the water. The hydrogel itself has a microstructure that lacks nanoscale pores, which further prevents salt from escaping the material. The salt levels in the water they collected were below the standard threshold for safe drinking water, and significantly below the levels produced by many other hydrogel-based designs.

In addition to tuning the hydrogel’s composition, the researchers made improvements to its form. Rather than keeping the gel as a flat sheet, they molded it into a pattern of small domes resembling bubble wrap, that act to increase the gel’s surface area, along with the amount of water vapor it can absorb.

The researchers fabricated a half-square-meter of hydrogel and encased the material in a window-like glass chamber. They coated the exterior of the chamber with a special polymer film, which helps to cool the glass and stimulates any water vapor in the hydrogel to evaporate and condense onto the glass. They installed a simple tubing system to collect the water as it flows down the glass.

In November 2023, the team traveled to Death Valley, California, and set up the device as a vertical panel. Over seven days, they took measurements as the hydrogel absorbed water vapor during the night (the time of day when water vapor in the desert is highest). In the daytime, with help from the sun, the harvested water evaporated out from the hydrogel and condensed onto the glass.

Over this period, the device worked across a range of humidities, from 21 to 88 percent, and produced between 57 and 161.5 milliliters of drinking water per day. Even in the driest conditions, the device harvested more water than other passive and some actively powered designs.

“This is just a proof-of-concept design, and there are a lot of things we can optimize,” Liu says. “For instance, we could have a multipanel design. And we’re working on a next generation of the material to further improve its intrinsic properties.”

“We imagine that you could one day deploy an array of these panels, and the footprint is very small because they are all vertical,” says Zhao, who has plans to further test the panels in many resource-limited regions. “Then you could have many panels together, collecting water all the time, at household scale.”

This work was supported, in part, by the MIT J-WAFS Water and Food Seed Grant, the MIT-Chinese University of Hong Kong collaborative research program, and the UM6P-MIT collaborative research program.

How the brain solves complicated problems

Study shows humans flexibly deploy different reasoning strategies to tackle challenging mental tasks — offering insights for building machines that think more like us.

The human brain is very good at solving complicated problems. One reason for that is that humans can break problems apart into manageable subtasks that are easy to solve one at a time.

This allows us to complete a daily task like going out for coffee by breaking it into steps: getting out of our office building, navigating to the coffee shop, and once there, obtaining the coffee. This strategy helps us to handle obstacles easily. For example, if the elevator is broken, we can revise how we get out of the building without changing the other steps.

While there is a great deal of behavioral evidence demonstrating humans’ skill at these complicated tasks, it has been difficult to devise experimental scenarios that allow precise characterization of the computational strategies we use to solve problems.

In a new study, MIT researchers have successfully modeled how people deploy different decision-making strategies to solve a complicated task — in this case, predicting how a ball will travel through a maze when the ball is hidden from view. The human brain cannot perform this task perfectly because it is impossible to track all of the possible trajectories in parallel, but the researchers found that people can perform reasonably well by flexibly adopting two strategies known as hierarchical reasoning and counterfactual reasoning.

The researchers were also able to determine the circumstances under which people choose each of those strategies.

“What humans are capable of doing is to break down the maze into subsections, and then solve each step using relatively simple algorithms. Effectively, when we don’t have the means to solve a complex problem, we manage by using simpler heuristics that get the job done,” says Mehrdad Jazayeri, a professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, an investigator at the Howard Hughes Medical Institute, and the senior author of the study.

Mahdi Ramadan PhD ’24 and graduate student Cheng Tang are the lead authors of the paper, which appears today in Nature Human Behavior. Nicholas Watters PhD ’25 is also a co-author.

Rational strategies

When humans perform simple tasks that have a clear correct answer, such as categorizing objects, they perform extremely well. When tasks become more complex, such as planning a trip to your favorite cafe, there may no longer be one clearly superior answer. And, at each step, there are many things that could go wrong. In these cases, humans are very good at working out a solution that will get the task done, even though it may not be the optimal solution.

Those solutions often involve problem-solving shortcuts, or heuristics. Two prominent heuristics humans commonly rely on are hierarchical and counterfactual reasoning. Hierarchical reasoning is the process of breaking down a problem into layers, starting from the general and proceeding toward specifics. Counterfactual reasoning involves imagining what would have happened if you had made a different choice. While these strategies are well-known, scientists don’t know much about how the brain decides which one to use in a given situation.

“This is really a big question in cognitive science: How do we problem-solve in a suboptimal way, by coming up with clever heuristics that we chain together in a way that ends up getting us closer and closer until we solve the problem?” Jazayeri says.

To overcome this, Jazayeri and his colleagues devised a task that is just complex enough to require these strategies, yet simple enough that the outcomes and the calculations that go into them can be measured.

The task requires participants to predict the path of a ball as it moves through four possible trajectories in a maze. Once the ball enters the maze, people cannot see which path it travels. At two junctions in the maze, they hear an auditory cue when the ball reaches that point. Predicting the ball’s path is a task that is impossible for humans to solve with perfect accuracy.

“It requires four parallel simulations in your mind, and no human can do that. It’s analogous to having four conversations at a time,” Jazayeri says. “The task allows us to tap into this set of algorithms that the humans use, because you just can’t solve it optimally.”

The researchers recruited about 150 human volunteers to participate in the study. Before each subject began the ball-tracking task, the researchers evaluated how accurately they could estimate timespans of several hundred milliseconds, about the length of time it takes the ball to travel along one arm of the maze.

For each participant, the researchers created computational models that could predict the patterns of errors that would be seen for that participant (based on their timing skill) if they were running parallel simulations, using hierarchical reasoning alone, counterfactual reasoning alone, or combinations of the two reasoning strategies.

The researchers compared the subjects’ performance with the models’ predictions and found that for every subject, their performance was most closely associated with a model that used hierarchical reasoning but sometimes switched to counterfactual reasoning.

That suggests that instead of tracking all the possible paths that the ball could take, people broke up the task. First, they picked the direction (left or right), in which they thought the ball turned at the first junction, and continued to track the ball as it headed for the next turn. If the timing of the next sound they heard wasn’t compatible with the path they had chosen, they would go back and revise their first prediction — but only some of the time.

Switching back to the other side, which represents a shift to counterfactual reasoning, requires people to review their memory of the tones that they heard. However, it turns out that these memories are not always reliable, and the researchers found that people decided whether to go back or not based on how good they believed their memory to be.

“People rely on counterfactuals to the degree that it’s helpful,” Jazayeri says. “People who take a big performance loss when they do counterfactuals avoid doing them. But if you are someone who’s really good at retrieving information from the recent past, you may go back to the other side.”

Human limitations

To further validate their results, the researchers created a machine-learning neural network and trained it to complete the task. A machine-learning model trained on this task will track the ball’s path accurately and make the correct prediction every time, unless the researchers impose limitations on its performance.

When the researchers added cognitive limitations similar to those faced by humans, they found that the model altered its strategies. When they eliminated the model’s ability to follow all possible trajectories, it began to employ hierarchical and counterfactual strategies like humans do. If the researchers reduced the model’s memory recall ability, it began to switch to counterfactual only if it thought its recall would be good enough to get the right answer — just as humans do.

“What we found is that networks mimic human behavior when we impose on them those computational constraints that we found in human behavior,” Jazayeri says. “This is really saying that humans are acting rationally under the constraints that they have to function under.”

By slightly varying the amount of memory impairment programmed into the models, the researchers also saw hints that the switching of strategies appears to happen gradually, rather than at a distinct cut-off point. They are now performing further studies to try to determine what is happening in the brain as these shifts in strategy occur.

The research was funded by a Lisa K. Yang ICoN Fellowship, a Friends of the McGovern Institute Student Fellowship, a National Science Foundation Graduate Research Fellowship, the Simons Foundation, the Howard Hughes Medical Institute, and the McGovern Institute.

Once-a-week pill for schizophrenia shows promise in clinical trials

The ingestible capsule forms a drug depot in the stomach, gradually releasing its payload and eliminating the need for patients to take medicine every day.

For many patients with schizophrenia, other psychiatric illnesses, or diseases such as hypertension and asthma, it can be difficult to take their medicine every day. To help overcome that challenge, MIT researchers have developed a pill that can be taken just once a week and gradually releases medication from within the stomach.

In a phase 3 clinical trial conducted by MIT spinout Lyndra Therapeutics, the researchers used the once-a-week pill to deliver a widely used medication for managing the symptoms of schizophrenia. They found that this treatment regimen maintained consistent levels of the drug in patients’ bodies and controlled their symptoms just as well as daily doses of the drug. The results are published today in Lancet Psychiatry.

“We’ve converted something that has to be taken once a day to once a week, orally, using a technology that can be adapted for a variety of medications,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, an associate member of the Broad Institute, and an author of the study. “The ability to provide a sustained level of drug for a prolonged period, in an easy-to-administer system, makes it easier to ensure patients are receiving their medication.”

Traverso’s lab began developing the ingestible capsule studied in this trial more than 10 years ago, as part of an ongoing effort to make medications easier for patients to take. The capsule is about the size of a multivitamin, and once swallowed, it expands into a star shape that helps it remain in the stomach until all of the drug is released.

Richard Scranton, chief medical officer of Lyndra Therapeutics, is the senior author of the paper, and Leslie Citrome, a clinical professor of psychiatry and behavioral sciences at New York Medical College School of Medicine, is the lead author. Nayana Nagaraj, medical director at Lyndra Therapeutics, and Todd Dumas, senior director of pharmacometrics at Certara, are also authors.

Sustained delivery

Over the past decade, Traverso’s lab has been working on a variety of capsules that can be swallowed and remain in the digestive tract for days or weeks, slowly releasing their drug payload. In 2016, his team reported the star-shaped device, which was then further developed by Lyndra for clinical trials in patients with schizophrenia.

The device contains six arms that can be folded in, allowing it to fit inside a capsule. The capsule dissolves when the device reaches the stomach, allowing the arms to spring out. Once the arms are extended, the device becomes too large to pass through the pylorus (the exit of the stomach), so it remains freely floating in the stomach as drugs are slowly released from the arms. After about a week, the arms break off on their own, and each segment exits the stomach and passes through the digestive tract.

For the clinical trials, the capsule was loaded with risperidone, a commonly prescribed medication used to treat schizophrenia. Most patients take the drug orally once a day. There are also injectable versions that can be given every two weeks, every month, or every two months, but they require administration by a health care provider and are not always acceptable to patients.

The MIT and Lyndra team chose to focus on schizophrenia in hopes that a drug regimen that could be administered less frequently, through oral delivery, could make treatment easier for patients and their caregivers.

“One of the areas of unmet need that was recognized early on is neuropsychiatric conditions, where the illness can limit or impair one’s ability to remember to take their medication,” Traverso says. “With that in mind, one of the conditions that has been a big focus has been schizophrenia.”

The phase 3 trial was coordinated by researchers at Lyndra and enrolled 83 patients at five different sites around the United States. Forty-five of those patients completed the full five weeks of the study, in which they took one risperidone-loaded capsule per week.

Throughout the study, the researchers measured the amount of drug in each patient’s bloodstream. Each week, they found a sharp increase on the day the pill was given, followed by a slow decline over the next week. The levels were all within the optimal range, and there was less variation over time than is seen when patients take a pill each day.

Effective treatment

Using an evaluation known as the Positive and Negative Syndrome Scale (PANSS), the researchers also found that the patients’ symptoms remained stable throughout the study.

“One of the biggest obstacles in the care of people with chronic illnesses in general is that medications are not taken consistently. This leads to worsening symptoms, and in the case of schizophrenia, potential relapse and hospitalization,” Citrome says. “Having the option to take medication by mouth once a week represents an important option that can assist with adherence for the many patients who would prefer oral medications versus injectable formulations.”

Side effects from the treatment were minimal, the researchers found. Some patients experienced mild acid reflux and constipation early in the study, but these did not last long. The results, showing effectiveness of the capsule and few side effects, represent a major milestone in this approach to drug delivery, Traverso says.

“This really demonstrates that what we had hypothesized a decade ago, which is that a single capsule providing a drug depot within the GI tract could be possible,” he says. “Here what you see is that the capsule can achieve the drug levels that were predicted, and also control symptoms in a sizeable cohort of patients with schizophrenia.”

The investigators now hope to complete larger phase 3 studies before applying for FDA approval of this delivery approach for risperidone. They are also preparing for phase 1 trials using this capsule to deliver other drugs, including contraceptives.

“We are delighted that this technology which started at MIT has reached the point of phase 3 clinical trials,” says Robert Langer, the David H. Koch Institute Professor at MIT, who was an author of the original study on the star capsule and is a co-founder of Lyndra Therapeutics.

The research was funded by Lyndra Therapeutics.

How we really judge AI

Forget optimists vs. Luddites. Most people evaluate AI based on its perceived capability and their need for personalization.

Suppose you were shown that an artificial intelligence tool offers accurate predictions about some stocks you own. How would you feel about using it? Now, suppose you are applying for a job at a company where the HR department uses an AI system to screen resumes. Would you be comfortable with that?

A new study finds that people are neither entirely enthusiastic nor totally averse to AI. Rather than falling into camps of techno-optimists and Luddites, people are discerning about the practical upshot of using AI, case by case.

“We propose that AI appreciation occurs when AI is perceived as being more capable than humans and personalization is perceived as being unnecessary in a given decision context,” says MIT Professor Jackson Lu, co-author of a newly published paper detailing the study’s results. “AI aversion occurs when either of these conditions is not met, and AI appreciation occurs only when both conditions are satisfied.”

The paper, “AI Aversion or Appreciation? A Capability–Personalization Framework and a Meta-Analytic Review,” appears in Psychological Bulletin. The paper has eight co-authors, including Lu, who is the Career Development Associate Professor of Work and Organization Studies at the MIT Sloan School of Management.

New framework adds insight

People’s reactions to AI have long been subject to extensive debate, often producing seemingly disparate findings. An influential 2015 paper on “algorithm aversion” found that people are less forgiving of AI-generated errors than of human errors, whereas a widely noted 2019 paper on “algorithm appreciation” found that people preferred advice from AI, compared to advice from humans.

To reconcile these mixed findings, Lu and his co-authors conducted a meta-analysis of 163 prior studies that compared people’s preferences for AI versus humans. The researchers tested whether the data supported their proposed “Capability–Personalization Framework” — the idea that in a given context, both the perceived capability of AI and the perceived necessity for personalization shape our preferences for either AI or humans.

Across the 163 studies, the research team analyzed over 82,000 reactions to 93 distinct “decision contexts” — for instance, whether or not participants would feel comfortable with AI being used in cancer diagnoses. The analysis confirmed that the Capability–Personalization Framework indeed helps account for people’s preferences.

“The meta-analysis supported our theoretical framework,” Lu says. “Both dimensions are important: Individuals evaluate whether or not AI is more capable than people at a given task, and whether the task calls for personalization. People will prefer AI only if they think the AI is more capable than humans and the task is nonpersonal.”

He adds: “The key idea here is that high perceived capability alone does not guarantee AI appreciation. Personalization matters too.”

For example, people tend to favor AI when it comes to detecting fraud or sorting large datasets — areas where AI’s abilities exceed those of humans in speed and scale, and personalization is not required. But they are more resistant to AI in contexts like therapy, job interviews, or medical diagnoses, where they feel a human is better able to recognize their unique circumstances.

“People have a fundamental desire to see themselves as unique and distinct from other people,” Lu says. “AI is often viewed as impersonal and operating in a rote manner. Even if the AI is trained on a wealth of data, people feel AI can’t grasp their personal situations. They want a human recruiter, a human doctor who can see them as distinct from other people.”

Context also matters: From tangibility to unemployment

The study also uncovered other factors that influence individuals’ preferences for AI. For instance, AI appreciation is more pronounced for tangible robots than for intangible algorithms.

Economic context also matters. In countries with lower unemployment, AI appreciation is more pronounced.

“It makes intuitive sense,” Lu says. “If you worry about being replaced by AI, you’re less likely to embrace it.”  

Lu is continuing to examine people’s complex and evolving attitudes toward AI. While he does not view the current meta-analysis as the last word on the matter, he hopes the Capability–Personalization Framework offers a valuable lens for understanding how people evaluate AI across different contexts.

“We’re not claiming perceived capability and personalization are the only two dimensions that matter, but according to our meta-analysis, these two dimensions capture much of what shapes people’s preferences for AI versus humans across a wide range of studies,” Lu concludes.

In addition to Lu, the paper’s co-authors are Xin Qin, Chen Chen, Hansen Zhou, Xiaowei Dong, and Limei Cao of Sun Yat-sen University; Xiang Zhou of Shenzhen University; and Dongyuan Wu of Fudan University.

The research was supported, in part, by grants to Qin and Wu from the National Natural Science Foundation of China. 

AI-enabled control system helps autonomous drones stay on target in uncertain environments

The system automatically learns to adapt to unknown disturbances such as gusting winds.

An autonomous drone carrying water to help extinguish a wildfire in the Sierra Nevada might encounter swirling Santa Ana winds that threaten to push it off course. Rapidly adapting to these unknown disturbances inflight presents an enormous challenge for the drone’s flight control system.

To help such a drone stay on target, MIT researchers developed a new, machine learning-based adaptive control algorithm that could minimize its deviation from its intended trajectory in the face of unpredictable forces like gusty winds.

Unlike standard approaches, the new technique does not require the person programming the autonomous drone to know anything in advance about the structure of these uncertain disturbances. Instead, the control system’s artificial intelligence model learns all it needs to know from a small amount of observational data collected from 15 minutes of flight time.

Importantly, the technique automatically determines which optimization algorithm it should use to adapt to the disturbances, which improves tracking performance. It chooses the algorithm that best suits the geometry of specific disturbances this drone is facing.

The researchers train their control system to do both things simultaneously using a technique called meta-learning, which teaches the system how to adapt to different types of disturbances.

Taken together, these ingredients enable their adaptive control system to achieve 50 percent less trajectory tracking error than baseline methods in simulations and perform better with new wind speeds it didn’t see during training.

In the future, this adaptive control system could help autonomous drones more efficiently deliver heavy parcels despite strong winds or monitor fire-prone areas of a national park.

“The concurrent learning of these components is what gives our method its strength. By leveraging meta-learning, our controller can automatically make choices that will be best for quick adaptation,” says Navid Azizan, who is the Esther and Harold E. Edgerton Assistant Professor in the MIT Department of Mechanical Engineering and the Institute for Data, Systems, and Society (IDSS), a principal investigator of the Laboratory for Information and Decision Systems (LIDS), and the senior author of a paper on this control system.

Azizan is joined on the paper by lead author Sunbochen Tang, a graduate student in the Department of Aeronautics and Astronautics, and Haoyuan Sun, a graduate student in the Department of Electrical Engineering and Computer Science. The research was recently presented at the Learning for Dynamics and Control Conference.

Finding the right algorithm

Typically, a control system incorporates a function that models the drone and its environment, and includes some existing information on the structure of potential disturbances. But in a real world filled with uncertain conditions, it is often impossible to hand-design this structure in advance.

Many control systems use an adaptation method based on a popular optimization algorithm, known as gradient descent, to estimate the unknown parts of the problem and determine how to keep the drone as close as possible to its target trajectory during flight. However, gradient descent is only one algorithm in a larger family of algorithms available to choose, known as mirror descent.

“Mirror descent is a general family of algorithms, and for any given problem, one of these algorithms can be more suitable than others. The name of the game is how to choose the particular algorithm that is right for your problem. In our method, we automate this choice,” Azizan says.

In their control system, the researchers replaced the function that contains some structure of potential disturbances with a neural network model that learns to approximate them from data. In this way, they don’t need to have an a priori structure of the wind speeds this drone could encounter in advance.

Their method also uses an algorithm to automatically select the right mirror-descent function while learning the neural network model from data, rather than assuming a user has the ideal function picked out already. The researchers give this algorithm a range of functions to pick from, and it finds the one that best fits the problem at hand.

“Choosing a good distance-generating function to construct the right mirror-descent adaptation matters a lot in getting the right algorithm to reduce the tracking error,” Tang adds.

Learning to adapt

While the wind speeds the drone may encounter could change every time it takes flight, the controller’s neural network and mirror function should stay the same so they don’t need to be recomputed each time.

To make their controller more flexible, the researchers use meta-learning, teaching it to adapt by showing it a range of wind speed families during training.

“Our method can cope with different objectives because, using meta-learning, we can learn a shared representation through different scenarios efficiently from data,” Tang explains.

In the end, the user feeds the control system a target trajectory and it continuously recalculates, in real-time, how the drone should produce thrust to keep it as close as possible to that trajectory while accommodating the uncertain disturbance it encounters.

In both simulations and real-world experiments, the researchers showed that their method led to significantly less trajectory tracking error than baseline approaches with every wind speed they tested.

“Even if the wind disturbances are much stronger than we had seen during training, our technique shows that it can still handle them successfully,” Azizan adds.

In addition, the margin by which their method outperformed the baselines grew as the wind speeds intensified, showing that it can adapt to challenging environments.

The team is now performing hardware experiments to test their control system on real drones with varying wind conditions and other disturbances.

They also want to extend their method so it can handle disturbances from multiple sources at once. For instance, changing wind speeds could cause the weight of a parcel the drone is carrying to shift in flight, especially when the drone is carrying sloshing payloads.

They also want to explore continual learning, so the drone could adapt to new disturbances without the need to also be retrained on the data it has seen so far.

“Navid and his collaborators have developed breakthrough work that combines meta-learning with conventional adaptive control to learn nonlinear features and the suitable adaptation law from data. Key to their approach is the use of mirror descent techniques that exploit the underlying geometry of the problem and do so automatically. Their work can contribute significantly to the design of autonomous systems that need to operate in complex and uncertain environments,” says Babak Hassibi, the Mose and Lillian S. Bohn Professor of Electrical Engineering and Computing and Mathematical Sciences at Caltech, who was not involved with this work.

This research was supported, in part, by MathWorks, the MIT-IBM Watson AI Lab, the MIT-Amazon Science Hub, and the MIT-Google Program for Computing Innovation.

Helping machines understand visual content with AI

Coactive, founded by two MIT alumni, has built an AI-powered platform to unlock new insights from content of all types.

Data should drive every decision a modern business makes. But most businesses have a massive blind spot: They don’t know what’s happening in their visual data.

Coactive is working to change that. The company, founded by Cody Coleman ’13, MEng ’15 and William Gaviria Rojas ’13, has created an artificial intelligence-powered platform that can make sense of data like images, audio, and video to unlock new insights.

Coactive’s platform can instantly search, organize, and analyze unstructured visual content to help businesses make faster, better decisions.

“In the first big data revolution, businesses got better at getting value out of their structured data,” Coleman says, referring to data from tables and spreadsheets. “But now, approximately 80 to 90 percent of the data in the world is unstructured. In the next chapter of big data, companies will have to process data like images, video, and audio at scale, and AI is a key piece of unlocking that capability.”

Coactive is already working with several large media and retail companies to help them understand their visual content without relying on manual sorting and tagging. That’s helping them get the right content to users faster, remove explicit content from their platforms, and uncover how specific content influences user behavior.

More broadly, the founders believe Coactive serves as an example of how AI can empower humans to work more efficiently and solve new problems.

“The word coactive means to work together concurrently, and that’s our grand vision: helping humans and machines work together,” Coleman says. “We believe that vision is more important now than ever because AI can either pull us apart or bring us together. We want Coactive to be an agent that pulls us together and gives human beings a new set of superpowers.”

Giving computers vision

Coleman met Gaviria Rojas in the summer before their first yearthrough the MIT Interphase Edge program. Both would go on to major in electrical engineering and computer science and work on bringing MIT OpenCourseWare content to Mexican universities, among other projects.

“That was a great example of entrepreneurship,” Coleman recalls of the OpenCourseWare project. “It was really empowering to be responsible for the business and the software development. It led me to start my own small web-development businesses afterward, and to take [the MIT course] Founder’s Journey.”

Coleman first explored the power of AI at MIT while working as a graduate researcher with the Office of Digital Learning (now MIT Open Learning), where he used machine learning to study how humans learn on MITx, which hosts massive, open online courses created by MIT faculty and instructors.

“It was really amazing to me that you could democratize this transformational journey that I went through at MIT with digital learning — and that you could apply AI and machine learning to create adaptive systems that not only help us understand how humans learn, but also deliver more personalized learning experiences to people around the world,” Coleman says of MITx. “That was also the first time I got to explore video content and apply AI to it.”

After MIT, Coleman went to Stanford University for his PhD, where he worked on lowering barriers to using AI. The research led him to work with companies like Pinterest and Meta on AI and machine-learning applications.

“That’s where I was able to see around the corner into the future of what people wanted to do with AI and their content,” Coleman recalls. “I was seeing how leading companies were using AI to drive business value, and that’s where the initial spark for Coactive came from. I thought, ‘What if we create an enterprise-grade operating system for content and multimodal AI to make that easy?’”

Meanwhile, Gaviria Rojas moved to the Bay Area in 2020 and started working as a data scientist at eBay. As part of the move, he needed help transporting his couch, and Coleman was the lucky friend he called.

“On the car ride, we realized we both saw an explosion happening around data and AI,” Gaviria Rojas says. “At MIT, we got a front row seat to the big data revolution, and we saw people inventing technologies to unlock value from that data at scale. Cody and I realized we had another powder keg about to explode with enterprises collecting tremendous amount of data, but this time it was multimodal data like images, video, audio, and text. There was a missing technology to unlock it at scale. That was AI.”

The platform the founders went on to build — what Coleman describes as an “AI operating system” — is model agnostic, meaning the company can swap out the AI systems under the hood as models continue to improve. Coactive’s platform includes prebuilt applications that business customers can use to do things like search through their content, generate metadata, and conduct analytics to extract insights.

“Before AI, computers would see the world through bytes, whereas humans would see the world through vision,” Coleman says. “Now with AI, machines can finally see the world like we do, and that’s going to cause the digital and physical worlds to blur.”

Improving the human-computer interface

Reuters’ database of images supplies the world’s journalists with millions of photos. Before Coactive, the company relied on reporters manually entering tags with each photo so that the right images would show up when journalists searched for certain subjects.

“It was incredible slow and expensive to go through all of these raw assets, so people just didn’t add tags,” Coleman says. “That meant when you searched for things, there were limited results even if relevant photos were in the database.”

Now, when journalists on Reuters’ website select ‘Enable AI Search,’ Coactive can pull up relevant content based on its AI system’s understanding of the details in each image and video.

“It’s vastly improving the quality of results for reporters, which enables them to tell better, more accurate stories than ever before,” Coleman says.

Reuters is not alone in struggling to manage all of its content. Digital asset management is a huge component of many media and retail companies, who today often rely on manually entered metadata for sorting and searching through that content.

Another Coactive customer is Fandom, which is one of the world’s largest platforms for information around TV shows, videogames, and movies with more than 300 million monthly active users. Fandom is using Coactive to understand visual data in their online communities and help remove excessive gore and sexualized content.

“It used to take 24 to 48 hours for Fandom to review each new piece of content,” Coleman says. “Now with Coactive, they’ve codified their community guidelines and can generate finer-grain information in an average of about 500 milliseconds.”

With every use case, the founders see Coactive as enabling a new paradigm in the ways humans work with machines.

“Throughout the history of human-computer interaction, we’ve had to bend over a keyboard and mouse to input information in a way that machines could understand,” Coleman says. “Now, for the first time, we can just speak naturally, we can share images and video with AI, and it can understand that content. That’s a fundamental change in the way we think about human-computer interactions. The core vision of Coactive is because of that change, we need a new operating system and a new way of working with content and AI.”

How the brain distinguishes between ambiguous hypotheses

Neural activity patterns can encode competing hypotheses about which landmark will lead to the correct destination.

When navigating a place that we’re only somewhat familiar with, we often rely on unique landmarks to help make our way. However, if we’re looking for an office in a brick building, and there are many brick buildings along our route, we might use a rule like looking for the second building on a street, rather than relying on distinguishing the building itself.

Until that ambiguity is resolved, we must hold in mind that there are multiple possibilities (or hypotheses) for where we are in relation to our destination. In a study of mice, MIT neuroscientists have now discovered that these hypotheses are explicitly represented in the brain by distinct neural activity patterns.

This is the first time that neural activity patterns that encode simultaneous hypotheses have been seen in the brain. The researchers found that these representations, which were observed in the brain’s retrosplenial cortex (RSC), not only encode hypotheses but also could be used by the animals to choose the correct way to go.

“As far as we know, no one has shown in a complex reasoning task that there’s an area in association cortex that holds two hypotheses in mind and then uses one of those hypotheses, once it gets more information, to actually complete the task,” says Mark Harnett, an associate professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

Jakob Voigts PhD ’17, a former postdoc in Harnett’s lab and now a group leader at the Howard Hughes Medical Institute Janelia Research Campus, is the lead author of the paper, which appears today in Nature Neuroscience.

Ambiguous landmarks

The RSC receives input from the visual cortex, the hippocampal formation, and the anterior thalamus, which it integrates to help guide navigation.

In a 2020 paper, Harnett’s lab found that the RSC uses both visual and spatial information to encode landmarks used for navigation. In that study, the researchers showed that neurons in the RSC of mice integrate visual information about the surrounding environment with spatial feedback of the mice’s own position along a track, allowing them to learn where to find a reward based on landmarks that they saw.

In their new study, the researchers wanted to delve further into how the RSC uses spatial information and situational context to guide navigational decision-making. To do that, the researchers devised a much more complicated navigational task than typically used in mouse studies. They set up a large, round arena, with 16 small openings, or ports, along the side walls. One of these openings would give the mice a reward when they stuck their nose through it. In the first set of experiments, the researchers trained the mice to go to different reward ports indicated by dots of light on the floor that were only visible when the mice get close to them.

Once the mice learned to perform this relatively simple task, the researchers added a second dot. The two dots were always the same distance from each other and from the center of the arena. But now the mice had to go to the port by the counterclockwise dot to get the reward. Because the dots were identical and only became visible at close distances, the mice could never see both dots at once and could not immediately determine which dot was which.

To solve this task, mice therefore had to remember where they expected a dot to show up, integrating their own body position, the direction they were heading, and path they took to figure out which landmark is which. By measuring RSC activity as the mice approached the ambiguous landmarks, the researchers could determine whether the RSC encodes hypotheses about spatial location. The task was carefully designed to require the mice to use the visual landmarks to obtain rewards, instead of other strategies like odor cues or dead reckoning.

“What is important about the behavior in this case is that mice need to remember something and then use that to interpret future input,” says Voigts, who worked on this study while a postdoc in Harnett’s lab. “It’s not just remembering something, but remembering it in such a way that you can act on it.”

The researchers found that as the mice accumulated information about which dot might be which, populations of RSC neurons displayed distinct activity patterns for incomplete information. Each of these patterns appears to correspond to a hypothesis about where the mouse thought it was with respect to the reward.

When the mice get close enough to figure out which dot was indicating the reward port, these patterns collapsed into the one that represents the correct hypothesis. The findings suggest that these patterns not only passively store hypotheses, they can also be used to compute how to get to the correct location, the researchers say.

“We show that RSC has the required information for using this short-term memory to distinguish the ambiguous landmarks. And we show that this type of hypothesis is encoded and processed in a way that allows the RSC to use it to solve the computation,” Voigts says.

Interconnected neurons

When analyzing their initial results, Harnett and Voigts consulted with MIT Professor Ila Fiete, who had run a study about 10 years ago using an artificial neural network to perform a similar navigation task.

That study, previously published on bioRxiv, showed that the neural network displayed activity patterns that were conceptually similar to those seen in the animal studies run by Harnett’s lab. The neurons of the artificial neural network ended up forming highly interconnected low-dimensional networks, like the neurons of the RSC.

“That interconnectivity seems, in ways that we still don’t understand, to be key to how these dynamics emerge and how they’re controlled. And it’s a key feature of how the RSC holds these two hypotheses in mind at the same time,” Harnett says.

In his lab at Janelia, Voigts now plans to investigate how other brain areas involved in navigation, such as the prefrontal cortex, are engaged as mice explore and forage in a more naturalistic way, without being trained on a specific task.

“We’re looking into whether there are general principles by which tasks are learned,” Voigts says. “We have a lot of knowledge in neuroscience about how brains operate once the animal has learned a task, but in comparison we know extremely little about how mice learn tasks or what they choose to learn when given freedom to behave naturally.”

The research was funded, in part, by the National Institutes of Health, a Simons Center for the Social Brain at MIT postdoctoral fellowship, the National Institute of General Medical Sciences, and the Center for Brains, Minds, and Machines at MIT, funded by the National Science Foundation.

Animation technique simulates the motion of squishy objects

The approach could help animators to create realistic 3D characters or engineers to design elastic products.

Animators could create more realistic bouncy, stretchy, and squishy characters for movies and video games thanks to a new simulation method developed by researchers at MIT.

Their approach allows animators to simulate rubbery and elastic materials in a way that preserves the physical properties of the material and avoids pitfalls like instability.

The technique simulates elastic objects for animation and other applications, with improved reliability compared to other methods. In comparison, many existing simulation techniques can produce elastic animations that become erratic or sluggish or can even break down entirely.

To achieve this improvement, the MIT researchers uncovered a hidden mathematical structure in equations that capture how elastic materials deform on a computer. By leveraging this property, known as convexity, they designed a method that consistently produces accurate, physically faithful simulations.

“The way animations look often depends on how accurately we simulate the physics of the problem,” says Leticia Mattos Da Silva, an MIT graduate student and lead author of a paper on this research. “Our method aims to stay true to physical laws while giving more control and stability to animation artists.”

Beyond 3D animation, the researchers also see potential future uses in the design of real elastic objects, such as flexible shoes, garments, or toys. The method could be extended to help engineers explore how stretchy objects will perform before they are built.

She is joined on the paper by Silvia Sellán, an assistant professor of computer science at Columbia University; Natalia Pacheco-Tallaj, an MIT graduate student; and senior author Justin Solomon, an associate professor in the MIT Department of Electrical Engineering and Computer Science and leader of the Geometric Data Processing Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL). The research will be presented at the SIGGRAPH conference.

Truthful to physics

If you drop a rubber ball on a wooden floor, it bounces back up. Viewers expect to see the same behavior in an animated world, but recreating such dynamics convincingly can be difficult. Many existing techniques simulate elastic objects using fast solvers that trade physical realism for speed, which can result in excessive energy loss or even simulation failure.

More accurate approaches, including a class of techniques called variational integrators, preserve the physical properties of the object, such as its total energy or momentum, and, in this way, mimic real-world behavior more closely. But these methods are often unreliable because they depend on complex equations that are hard to solve efficiently.

The MIT researchers tackled this problem by rewriting the equations of variational integrators to reveal a hidden convex structure. They broke the deformation of elastic materials into a stretch component and a rotation component, and found that the stretch portion forms a convex problem that is well-suited for stable optimization algorithms.

“If you just look at the original formulation, it seems fully non-convex. But because we can rewrite it so that is convex in at least some of its variables, we can inherit some advantages of convex optimization algorithms,” she says.

These convex optimization algorithms, when applied under the right conditions, come with guarantees of convergence, meaning they are more likely to find the correct answer to the problem. This generates more stable simulations over time, avoiding issues like a bouncing rubber ball losing too much energy or exploding mid-animation.

One of the biggest challenges the researchers faced was reinterpreting the formulation so they could extract that hidden convexity. Some other works explored hidden convexity in static problems, but it was not clear whether the structures remained solid for dynamic problems like simulating elastic objects in motion, Mattos Da Silva says.

Stability and efficiency

In experiments, their solver was able to simulate a wide range of elastic behavior, from bouncing shapes to squishy characters, with preservation of important physical properties and stability over long periods of time. Other simulation methods quickly ran into trouble: Some became unstable, causing erratic behavior, while others showed visible damping.

“Because our method demonstrates more stability, it can give animators more reliability and confidence when simulating anything elastic, whether it’s something from the real world or even something completely imaginary,” she says.

While the solver is not as fast as some simulation tools that prioritize speed over accuracy, it avoids many of the trade-offs those methods make. Compared to other physics-based approaches, it also avoids the need for complex, nonlinear solvers that can be sensitive and prone to failure.

In the future, the researchers want to explore techniques to further reduce computational cost. In addition, they want to explore applications of this technique in fabrication and engineering, where reliable simulations of elastic materials could support the design of real-world objects, like garments and toys.

“We were able to revive an old class of integrators in our work. My guess is there are other examples where researchers can revisit a problem to find a hidden convexity structure that could offer a lot of advantages,” she says.

This research is funded, in part, by a MathWorks Engineering Fellowship, the Army Research Office, the National Science Foundation, the CSAIL Future of Data Program, the MIT-IBM Watson AI Laboratory, the Wistron Corporation, and the Toyota-CSAIL Joint Research Center.

Former MIT researchers advance a new model for innovation

Focused research organizations (FROs) undertake large research efforts and have begun to yield scientific advances.

Academic research groups and startups are essential drivers of scientific progress. But some projects, like the Hubble Space Telescope or the Human Genome Project, are too big for any one academic lab or loose consortium. They’re also not immediately profitable enough for industry to take on.

That’s the gap researchers at MIT were trying to fill when they created the concept of focused research organizations, or FROs. They describe a FRO as a new type of entity, often philanthropically funded, that undertakes large research efforts using tightly coordinated teams to create a public good that accelerates scientific progress.

The original idea for focused research organizations came out of talks among researchers, most of whom were working to map the brain in MIT Professor Ed Boyden’s lab. After they began publishing their ideas, however, the researchers realized FROs could be a powerful tool to unlock scientific advances across many other applications.

“We were quite pleasantly surprised by the range of fields where we see FRO-shaped problems,” says Adam Marblestone, a former MIT research scientist who co-founded the nonprofit Convergent Research to help launch FROs in 2021. “Convergent has FRO proposals from climate, materials science, chemistry, biology — we even have launched a FRO on software for math. You wouldn’t expect math to be something with a large-scale technological research bottleneck, but it turns out even there, we found a software engineering bottleneck that needed to be solved.”

Marblestone helped formulate the idea for focused research organizations at MIT with a group including Andrew Payne SM ’17, PhD ’21 and Sam Rodriques PhD ’19, who were PhD students in Boyden’s lab at the time. Since then, the FRO concept has caught on. Convergent has helped attract philanthropic funding for FROs working to decode the immune system, identify the unintended targets of approved drugs, and understand the impacts of carbon dioxide removal in our oceans.

In total, Convergent has supported the creation of 10 FROs since its founding in 2021. Many of those groups have already released important tools for better understanding our world — and their leaders believe the best is yet to come.

“We’re starting to see these first open-source tools released in important areas,” Marblestone says. “We’re seeing the first concrete evidence that FROs are effective, because no other entity could have released these tools, and I think 2025 is going to be a significant year in terms of our newer FROs putting out new datasets and tools.”

A new model

Marblestone joined Boyden’s lab in 2014 as a research scientist after completing his PhD at Harvard University. He also worked in a new position called director of scientific architecting at the MIT Media Lab, which Boyden helped create, through which he tried to organize individual research efforts into larger projects. His own research focused on overcoming the challenges of measuring brain activity across large scales.

Marblestone discussed this and other large-scale neuroscience problems with Payne and Rodriques, and the researchers began thinking about gaps in scientific funding more broadly.

“The combination of myself, Sam, Andrew, Ed, and others’ experiences trying to start various large brain-mapping projects convinced us of the gap in support for medium-sized science and engineering teams with startup-inspired structures, built for the nonprofit purpose of building scientific infrastructure,” Marblestone says.

Through MIT, the researchers also connected with Tom Kalil, who was at the time chief innovation officer at Schmidt Futures, a philanthropic initiative of Eric and Wendy Schmidt. Rodriques wrote about the concept of a focused research organization as the last chapter of his PhD thesis in 2019.

“Ed always encouraged us to dream very, very big,” Rodriques says. “We were always trying to think about the hardest problems in biology and how to tackle them. My thesis basically ended with me explaining why we needed a new structure that is like a company, but nonprofit and dedicated to science.”

As part of a fellowship with the Federation of American Scientists in 2020, and working with Kalil, Marblestone interviewed scientists in dozens of fields outside of neuroscience and learned that the funding gap existed across disciplines.

When Rodriques and Marblestone published an essay about their findings, it helped attract philanthropic funding, which Marblestone, Kalil, and co-founder Anastasia Gamick used to launch Convergent Research, a nonprofit science studio for launching FROs.

“I see Ed’s lab as a melting pot where myself, Ed, Sam, and others worked on articulating a need and identifying specific projects that might make sense as FROs,” Marblestone says. “All those ideas later got crystallized when we created Convergent Research.”

In 2021, Convergent helped launch the first FROs: E11 Bio, which is led by Payne and committed to developing tools to understand how the brain is wired, and Cultivarium, a FRO making microorganisms more accessible for work in synthetic biology.

“From our brain mapping work we started asking the question, ‘Are there other projects that look like this that aren’t getting funded?’” Payne says. “We realized there was a gap in the research ecosystem, where some of these interdisciplinary, team science projects were being systematically overlooked. We knew a lot of amazing things would come out of getting those projects funded.”

Tools to advance science

Early progress from the first focused research organizations has strengthened Marblestone’s conviction that they’re filling a gap.

[C]Worthy is the FRO building tools to ensure safe, ocean-based carbon dioxide removal. It recently released an interactive map of alkaline activity to improve our understanding of one method for sequestering carbon known as ocean alkalinity enhancement. Last year, a math FRO, Lean, released a programming language and proof assistant that was used by Google’s DeepMind AI lab to solve problems in the International Mathematical Olympiad, achieving the same level as a silver medalist in the competition for the first time. The synthetic biology FRO Cultivarium, in turn, has already released software that can predict growth conditions for microbes based on their genome.

Last year, E11 Bio previewed a new method for mapping the brain called PRISM, which it has used to map out a portion of the mouse hippocampus. It will be making the data and mapping tool available to all researchers in coming months.

“A lot of this early work has proven you can put a really talented team together and move fast to go from zero to one,” Payne says. “The next phase is proving FROs can continue to build on that momentum and develop even more datasets and tools, establish even bigger collaborations, and scale their impact.”

Payne credits Boyden for fostering an ecosystem where researchers could think about problems beyond their narrow area of study.

“Ed’s lab was a really intellectually stimulating, collaborative environment,” Payne says. “He trains his students to think about impact first and work backward. It was a bunch of people thinking about how they were going to change the world, and that made it a particularly good place to develop the FRO idea.”

Marblestone says supporting FROs has been the highest-impact thing he’s been able to do in his career. Still, he believes the success of FROs should be judged over closer to 10-year periods and will depend on not just the tools they produce but also whether they spin out companies, partner with other institutes, and create larger, long-lasting initiatives to deploy what they built.

“We were initially worried people wouldn’t be willing to join these organizations because it doesn’t offer tenure and it doesn’t offer equity in a startup,” Marblestone says. “But we’ve been able to recruit excellent leaders, scientists, engineers, and others to create highly motivated teams. That’s good evidence this is working. As we get strong projects and good results, I hope it will create this flywheel where it becomes easier to fund these ideas, more scientists will come up with them, and I think we’re starting to get there.”

Scene at MIT: Reflecting on a shared journey toward MIT PhDs

Viraat Goel MBA ’25, PhD ’25 shares a poignant moment at the OneMIT Commencement ceremony with his wife, Erin Tevonian PhD ’25, as they celebrate their academic journey together.

“My wife, Erin Tevonian, and I both graduated last week with our PhDs in biological engineering, a program we started together when we arrived at MIT in fall 2019. At the time, we had already been dating for three years, having met as classmates in the bioengineering program at the University of Illinois at Urbana-Champaign in 2015. We went through college together — taking classes, vacationing with friends, and biking cross-country, all side-by-side — and so we were lucky to be able to continue doing so by coming to Course 20 at MIT together. It was during our graduate studies at MIT that we got engaged (spring 2022) and married (last September), a milestone that we were able to celebrate with the many wonderful friends we found at MIT.

First-year students in the MIT Biological Engineering PhD program rotate through labs of interest before picking where they will complete their doctorates, and so we found our way to research groups by January 2020 just before the Covid-19 pandemic disrupted on-campus research and caused social distancing. Erin completed her PhD in Doug Lauffenburger and Linda Griffith’s labs, during which she used computational and experimental models to study human insulin resistance and built better liver tissue models for recapitulating disease pathology. I completed my PhD in Anders Hansen’s lab and studied how DNA folds in 3D space to drive gene regulation by building and applying a new method for mapping DNA architecture at finer resolutions than previously possible. The years flew by as we dove into our research projects, and we defended our PhDs a week apart back in April.

Erin and I were standing at Commencement with the Class of 2025 at the moment this photo was snapped, smiling as we listened to MIT’s school song. Graduation is a bittersweet milestone because it represents the end of what has been an incredible adventure for us, an adventure that made campus feel like home, so I must admit that I wasn’t sure how I would feel going into graduation week. This moment, though, felt like a fitting close for our time at MIT, and I was filled with gratitude for the many memories, opportunities, and adventures I got to share with Erin over the course of grad school. I also graduated from the MIT Sloan School of Management/School of Engineering’s Leaders for Global Operations program (hence the stole), so I was also reflecting on the many folks I’ve met across campus that make MIT the wonderful place that it is, and how special it is to be a part of a community that makes it so hard to say goodbye.”

—Viraat Goel MBA ’25, PhD ’25

Have a creative photo of campus life you'd like to share? Submit it to Scene at MIT.

New system enables robots to solve manipulation problems in seconds

Researchers developed an algorithm that lets a robot “think ahead” and consider thousands of potential motion plans simultaneously.

Ready for that long-awaited summer vacation? First, you’ll need to pack all items required for your trip into a suitcase, making sure everything fits securely without crushing anything fragile.

Because humans possess strong visual and geometric reasoning skills, this is usually a straightforward problem, even if it may take a bit of finagling to squeeze everything in.

To a robot, though, it is an extremely complex planning challenge that requires thinking simultaneously about many actions, constraints, and mechanical capabilities. Finding an effective solution could take the robot a very long time — if it can even come up with one.

Researchers from MIT and NVIDIA Research have developed a novel algorithm that dramatically speeds up the robot’s planning process. Their approach enables a robot to “think ahead” by evaluating thousands of possible solutions in parallel and then refining the best ones to meet the constraints of the robot and its environment.

Instead of testing each potential action one at a time, like many existing approaches, this new method considers thousands of actions simultaneously, solving multistep manipulation problems in a matter of seconds.

The researchers harness the massive computational power of specialized processors called graphics processing units (GPUs) to enable this speedup.

In a factory or warehouse, their technique could enable robots to rapidly determine how to manipulate and tightly pack items that have different shapes and sizes without damaging them, knocking anything over, or colliding with obstacles, even in a narrow space.

“This would be very helpful in industrial settings where time really does matter and you need to find an effective solution as fast as possible. If your algorithm takes minutes to find a plan, as opposed to seconds, that costs the business money,” says MIT graduate student William Shen SM ’23, lead author of the paper on this technique.

He is joined on the paper by Caelan Garrett ’15, MEng ’15, PhD ’21, a senior research scientist at NVIDIA Research; Nishanth Kumar, an MIT graduate student; Ankit Goyal, a NVIDIA research scientist; Tucker Hermans, a NVIDIA research scientist and associate professor at the University of Utah; Leslie Pack Kaelbling, the Panasonic Professor of Computer Science and Engineering at MIT and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); Tomás Lozano-Pérez, an MIT professor of computer science and engineering and a member of CSAIL; and Fabio Ramos, principal research scientist at NVIDIA and a professor at the University of Sydney. The research will be presented at the Robotics: Science and Systems Conference.

Planning in parallel

The researchers’ algorithm is designed for what is called task and motion planning (TAMP). The goal of a TAMP algorithm is to come up with a task plan for a robot, which is a high-level sequence of actions, along with a motion plan, which includes low-level action parameters, like joint positions and gripper orientation, that complete that high-level plan.

To create a plan for packing items in a box, a robot needs to reason about many variables, such as the final orientation of packed objects so they fit together, as well as how it is going to pick them up and manipulate them using its arm and gripper.

It must do this while determining how to avoid collisions and achieve any user-specified constraints, such as a certain order in which to pack items.

With so many potential sequences of actions, sampling possible solutions at random and trying one at a time could take an extremely long time.

“It is a very large search space, and a lot of actions the robot does in that space don’t actually achieve anything productive,” Garrett adds.

Instead, the researchers’ algorithm, called cuTAMP, which is accelerated using a parallel computing platform called CUDA, simulates and refines thousands of solutions in parallel. It does this by combining two techniques, sampling and optimization.

Sampling involves choosing a solution to try. But rather than sampling solutions randomly, cuTAMP limits the range of potential solutions to those most likely to satisfy the problem’s constraints. This modified sampling procedure allows cuTAMP to broadly explore potential solutions while narrowing down the sampling space.

“Once we combine the outputs of these samples, we get a much better starting point than if we sampled randomly. This ensures we can find solutions more quickly during optimization,” Shen says.

Once cuTAMP has generated that set of samples, it performs a parallelized optimization procedure that computes a cost, which corresponds to how well each sample avoids collisions and satisfies the motion constraints of the robot, as well as any user-defined objectives.

It updates the samples in parallel, chooses the best candidates, and repeats the process until it narrows them down to a successful solution.

Harnessing accelerated computing

The researchers leverage GPUs, specialized processors that are far more powerful for parallel computation and workloads than general-purpose CPUs, to scale up the number of solutions they can sample and optimize simultaneously. This maximized the performance of their algorithm.

“Using GPUs, the computational cost of optimizing one solution is the same as optimizing hundreds or thousands of solutions,” Shen explains.

When they tested their approach on Tetris-like packing challenges in simulation, cuTAMP took only a few seconds to find successful, collision-free plans that might take sequential planning approaches much longer to solve.

And when deployed on a real robotic arm, the algorithm always found a solution in under 30 seconds.

The system works across robots and has been tested on a robotic arm at MIT and a humanoid robot at NVIDIA. Since cuTAMP is not a machine-learning algorithm, it requires no training data, which could enable it to be readily deployed in many situations.

“You can give it a brand-new problem and it will provably solve it,” Garrett says.

The algorithm is generalizable to situations beyond packing, like a robot using tools. A user could incorporate different skill types into the system to expand a robot’s capabilities automatically.

In the future, the researchers want to leverage large language models and vision language models within cuTAMP, enabling a robot to formulate and execute a plan that achieves specific objectives based on voice commands from a user.

This work is supported, in part, by the National Science Foundation (NSF), Air Force Office for Scientific Research, Office of Naval Research, MIT Quest for Intelligence, NVIDIA, and the Robotics and Artificial Intelligence Institute.

Guardian Ag’s crop-spraying drone is replacing dangerous pilot missions

Founded by two former regulars at the MITERS makerspace, the company has built huge, rugged drones to more safely and sustainably apply fertilizers and pesticides on farms.

Every year during the growing season, thousands of pilots across the country climb into small planes loaded with hundreds of pounds of pesticides and fly extremely close to the ground at upward of 140 miles an hour, unloading their cargo onto rows of corn, cotton, and soybeans.

The world of agricultural aviation is as dangerous as it is vital to America’s farms. Unfortunately, fatal crashes are common. Now Guardian Ag, founded by former MIT Electronics Research Society (MITERS) makers Adam Bercu and Charles Guan ’11, is offering an alternative in the form of a large, purpose-built drone that can autonomously deliver 200-pound payloads across farms. The company’s drones feature an 18-foot spray radius, 80-inch rotors, a custom battery pack, and aerospace-grade materials designed to make crop spraying more safe, efficient, and inexpensive for farmers.

“We’re trying to bring technology to American farms that are hundreds or thousands of acres, where you’re not replacing a human with a hand pump — you’re replacing a John Deere tractor or a helicopter or an airplane,” Bercu says.

“With Guardian, the operator shows up about 30 minutes before they want to spray, they mix the product, path plan the field in our app, and it gives an estimate for how long the job will take,” he says. “With our fast charging, you recharge the aircraft while you fill the tank, and those two operations take about the same amount of time.”

From Battlebots to farmlands

At a young age, Bercu became obsessed with building robots. Growing up in south Florida, he’d attend robotic competitions, build prototypes, and even dumpster dive for particularly hard-to-find components. At one competition, Bercu met Charles Guan, who would go on to major in mechanical engineering at MIT, and the two robot enthusiasts became lifelong friends.

“When Charles came to MIT, he basically convinced me to move to Cambridge,” Bercu says. “He said, ‘You need to come up here. I found more people like us. Hackers!’”

Bercu visited Cambridge, Massachusetts, and indeed fell in love with the region’s makerspaces and hacker culture. He moved soon after, and he and Guan began spending free time at spaces including the Artisans Asylum makerspace in Somerville, Massachusetts; MIT’s International Design Center; and the MIT Electronics Research Society (MITERS) makerspace. Guan held several leadership positions at MITERS, including facilities manager, treasurer, and president.

“MIT offered enormous latitude to its students to be independent and creative, which was reflected in the degree of autonomy they permit student-run organizations like MITERS to have compared to other top-tier schools,” Guan says. “It was a key selling point to me when I was touring mechanical engineering labs as a junior in high school. I was well-known in the department circle for being at MITERS all the time, possibly even more than I spent on classes.”

After Guan graduated, he and Bercu started a hardware consulting business and competed in the robot combat show Battlebots. Guan also began working as a design instructor in MIT’s Department of Mechanical Engineering, where he taught a section of Course 2.007 that tasked students with building go-karts.

Eventually, Guan and Bercu decided to use their experience to start a drone company.

“Over the course of Battlebots and building go-karts, we knew electric batteries were getting really cheap and electric vehicle supply chains were established,” Bercu explains. “People were raising money to build eVTOL [electric vertical take-off and landing] vehicles to transport people, but we knew diesel fuel still outperformed batteries over long distances. Where electric systems did outperform combustion engines was in areas where you needed peak power for short periods of time. Basically, batteries are awesome when you have a short mission.”

That idea made the founders think crop spraying could be a good early application. Bercu’s family runs an aviation business, and he knew pilots who would spray crops as their second jobs.

“It’s one of those high-paying but very dangerous jobs,” Bercu says. “Even in the U.S., we lose between 1 and 2 percent of all agriculture pilots each year to fatal accidents. These people are rolling the dice every time they do this: You’re flying 6 feet off the ground at 140 miles an hour with 800 gallons of pesticide in your tank.”

After cobbling together spare parts from Battlebots and their consulting business, the founders built a 600-pound drone. When they finally got it to fly, they decided the time was right to launch their company, receiving crucial early guidance and their first funding from the MIT-affiliated investment firm the E14 Fund.

The founders spent the next year interviewing crop dusters and farmers. They also started engaging with the Federal Aviation Administration.

“There was no category for anything like this,” Bercu explains. “With the FAA, we not only got through the approval process, we helped them build the process as we went through it, because we wanted to establish some common-sense standards.”

Guardian custom-built its batteries to optimize throughput and utilization rate of its drones. Depending on the farm, Bercu says his machines can unload about 1.5 to 2 tons of payload per hour.

Guardian’s drones can also spray more precisely than planes, reducing the environmental impact of pesticides, which often pollute the landscapes and waterways surrounding farms.

“This thing has the precision to spray the ‘Mona Lisa’ on 20 acres, but we’re not leveraging that functionality today,” Bercu says. “For the operator we want to make it very easy. The goal is to take someone who sprays with a tractor and teach them to spray with a drone in less than a week.”

Scaling for farmers

To date, Guardian Ag has built eight of its aircraft, which are actively delivering payloads over California farms in trials with paying customers. The company is currently ramping up manufacturing in its 60,000-square-foot facility in Massachusetts, and Bercu says Guardian has a backlog of hundreds of millions of dollars-worth of drones.

“Grower demand has been exceptional,” Bercu says. “We don’t need to educate them on the need for this. They see the big drone with the big tank and they’re in.”

Bercu envisions Guardian’s drones helping with a number of other tasks like ship-to-ship logistics, delivering supplies to offshore oil rigs, mining, and other areas where helicopters and small aircraft are currently flown through difficult terrain. But for now, the company is focused on starting with agriculture.

“Agriculture is such an important and foundational aspect of our country,” says Guardian Ag chief operating officer Ashley Ferguson MBA ’19. “We work with multigenerational farming families, and when we talk to them, it’s clear aerial spray has taken hold in the industry. But there’s a large shortage of pilots, especially for agriculture applications. So, it’s clear there’s a big opportunity.”

Seven years since founding Guardian, Bercu remains grateful that MIT’s community opened its doors for him when he moved to Cambridge.

“Without the MIT community, this company wouldn’t be possible,” Bercu says. “I was never able to go to college, but I’d love to one day apply to MIT and do my engineering undergrad or go to the Sloan School of Management. I’ll never forget MIT’s openness to me. It’s a place I hold near and dear to my heart.”

Physicists observe a new form of magnetism for the first time

The magnetic state offers a new route to “spintronic” memory devices that would be faster and more efficient than their electronic counterparts.

MIT physicists have demonstrated a new form of magnetism that could one day be harnessed to build faster, denser, and less power-hungry “spintronic” memory chips.

The new magnetic state is a mash-up of two main forms of magnetism: the ferromagnetism of everyday fridge magnets and compass needles, and antiferromagnetism, in which materials have magnetic properties at the microscale yet are not macroscopically magnetized.

Now, the MIT team has demonstrated a new form of magnetism, termed “p-wave magnetism.”

Physicists have long observed that electrons of atoms in regular ferromagnets share the same orientation of “spin,” like so many tiny compasses pointing in the same direction. This spin alignment generates a magnetic field, which gives a ferromagnet its inherent magnetism. Electrons belonging to magnetic atoms in an antiferromagnet also have spin, although these spins alternate, with electrons orbiting neighboring atoms aligning their spins antiparallel to each other. Taken together, the equal and opposite spins cancel out, and the antiferromagnet does not exhibit macroscopic magnetization.

The team discovered the new p-wave magnetism in nickel iodide (NiI₂), a two-dimensional crystalline material that they synthesized in the lab. Like a ferromagnet, the electrons exhibit a preferred spin orientation, and, like an antiferromagnet, equal populations of opposite spins result in a net cancellation. However, the spins on the nickel atoms exhibit a unique pattern, forming spiral-like configurations within the material that are mirror-images of each other, much like the left hand is the right hand’s mirror image.

What’s more, the researchers found this spiral spin configuration enabled them to carry out “spin switching”: Depending on the direction of spiraling spins in the material, they could apply a small electric field in a related direction to easily flip a left-handed spiral of spins into a right-handed spiral of spins, and vice-versa.

The ability to switch electron spins is at the heart of “spintronics,” which is a proposed alternative to conventional electronics. With this approach, data can be written in the form of an electron’s spin, rather than its electronic charge, potentially allowing orders of magnitude more data to be packed onto a device while using far less power to write and read that data.   

“We showed that this new form of magnetism can be manipulated electrically,” says Qian Song, a research scientist in MIT’s Materials Research Laboratory. “This breakthrough paves the way for a new class of ultrafast, compact, energy-efficient, and nonvolatile magnetic memory devices.”

Song and his colleagues published their results May 28 in the journal Nature. MIT co-authors include Connor Occhialini, Batyr Ilyas, Emre Ergeçen, Nuh Gedik, and Riccardo Comin, along with Rafael Fernandes at the University of Illinois Urbana-Champaign, and collaborators from multiple other institutions.

Connecting the dots

The discovery expands on work by Comin’s group in 2022. At that time, the team probed the magnetic properties of the same material, nickel iodide. At the microscopic level, nickel iodide resembles a triangular lattice of nickel and iodine atoms. Nickel is the material’s main magnetic ingredient, as the electrons on the nickel atoms exhibit spin, while those on iodine atoms do not.

In those experiments, the team observed that the spins of those nickel atoms were arranged in a spiral pattern throughout the material’s lattice, and that this pattern could spiral in two different orientations.

At the time, Comin had no idea that this unique pattern of atomic spins could enable precise switching of spins in surrounding electrons. This possibility was later raised by collaborator Rafael Fernandes, who along with other theorists was intrigued by a recently proposed idea for a new, unconventional, “p-wave” magnet, in which electrons moving along opposite directions in the material would have their spins aligned in opposite directions.

Fernandes and his colleagues recognized that if the spins of atoms in a material form the geometric spiral arrangement that Comin observed in nickel iodide, that would be a realization of a “p-wave” magnet. Then, when an electric field is applied to switch the “handedness” of the spiral, it should also switch the spin alignment of the electrons traveling along the same direction.

In other words, such a p-wave magnet could enable simple and controllable switching of electron spins, in a way that could be harnessed for spintronic applications.

“It was a completely new idea at the time, and we decided to test it experimentally because we realized nickel iodide was a good candidate to show this kind of p-wave magnet effect,” Comin says.

Spin current

For their new study, the team synthesized single-crystal flakes of nickel iodide by first depositing powders of the respective elements on a crystalline substrate, which they placed in a high-temperature furnace. The process causes the elements to settle into layers, each arranged microscopically in a triangular lattice of nickel and iodine atoms.

“What comes out of the oven are samples that are several millimeters wide and thin, like cracker bread,” Comin says. “We then exfoliate the material, peeling off even smaller flakes, each several microns wide, and a few tens of nanometers thin.”

The researchers wanted to know if, indeed, the spiral geometry of the nickel atoms’s spins would force electrons traveling in opposite directions to have opposite spins, like what Fernandes expected a p-wave magnet should exhibit. To observe this, the group applied to each flake a beam of circularly polarized light — light that produces an electric field that rotates in a particular direction, for instance, either clockwise or counterclockwise.

They reasoned that if travelling electrons interacting with the spin spirals have a spin that is aligned in the same direction, then incoming light, polarized in that same direction, should resonate and produce a characteristic signal. Such a signal would confirm that the traveling electrons’ spins align because of the spiral configuration, and furthermore, that the material does in fact exhibit p-wave magnetism.

And indeed, that’s what the group found. In experiments with multiple nickel iodide flakes, the researchers directly observed that the direction of the electron’s spin was correlated to the handedness of the light used to excite those electrons. Such is a telltale signature of p-wave magnetism, here observed for the first time.

Going a step further, they looked to see whether they could switch the spins of the electrons by applying an electric field, or a small amount of voltage, along different directions through the material. They found that when the direction of the electric field was in line with the direction of the spin spiral, the effect switched electrons along the route to spin in the same direction, producing a current of like-spinning electrons.

“With such a current of spin, you can do interesting things at the device level, for instance, you could flip magnetic domains that can be used for control of a magnetic bit,” Comin explains. “These spintronic effects are more efficient than conventional electronics because you’re just moving spins around, rather than moving charges. That means you’re not subject to any dissipation effects that generate heat, which is essentially the reason computers heat up.”

“We just need a small electric field to control this magnetic switching,” Song adds. “P-wave magnets could save five orders of magnitude of energy. Which is huge.”

“We are excited to see these cutting-edge experiments confirm our prediction of p-wave spin polarized states,” says Libor Šmejkal, head of the Max Planck Research Group in Dresden, Germany, who is one of the authors of the theoretical work that proposed the concept of p-wave magnetism but was not involved in the new paper. “The demonstration of electrically switchable p-wave spin polarization also highlights the promising applications of unconventional magnetic states.”

The team observed p-wave magnetism in nickel iodide flakes, only at ultracold temperatures of about 60 kelvins.

“That’s below liquid nitrogen, which is not necessarily practical for applications,” Comin says. “But now that we’ve realized this new state of magnetism, the next frontier is finding a material with these properties, at room temperature. Then we can apply this to a spintronic device.”

This research was supported, in part, by the National Science Foundation, the Department of Energy, and the Air Force Office of Scientific Research.

Day of Climate inspires young learners to take action

Featuring a diverse lineup of speakers, including Jaylen Brown of the Boston Celtics and an interactive projects showcase, the event empowered youth to tackle big challenges together.

“Close your eyes and imagine we are on the same team. Same arena. Same jersey. And the game is on the line,” Jaylen Brown, the 2024 NBA Finals MVP for the Boston Celtics, said to a packed room of about 200 people at the recent Day of Climate event at the MIT Museum.

“Now think about this: We aren’t playing for ourselves; we are playing for the next generation,” Brown added, encouraging attendees to take climate action. 

The inaugural Day of Climate event brought together local learners, educators, community leaders, and the MIT community. Featuring project showcases, panels, and a speaker series, the event sparked hands-on learning and inspired climate action across all ages.

The event marked the celebration of the first year of a larger initiative by the same name. Led by the pK-12 team at MIT Open Learning, Day of Climate has brought together learners and educators by offering free, hands-on curriculum lessons and activities designed to introduce learners to climate change, teach how it shapes their lives, and consider its effects on humanity. 

Cynthia Breazeal, dean of digital learning at MIT Open Learning, notes the breadth of engagement across MIT that made the event, and the larger initiative, possible with contributions from more than 10 different MIT departments, labs, centers, and initiatives. 

“MIT is passionate about K-12 education,” she says. “It was truly inspiring to witness how our entire community came together to demonstrate the power of collaboration and advocacy in driving meaningful change.”

From education to action 

The event kicked off with a showcase, where the Day of Climate grantees and learners invited attendees to learn about their projects and meaningfully engage with lessons and activities. Aranya Karighattam, a local high school senior, adapted the curriculum Urban Heat Islands — developed by Lelia Hampton, a PhD student in electrical engineering and computer science at MIT, and Chris Rabe, program director at the MIT Environmental Solution Initiative — sharing how this phenomenon affects the Boston metropolitan area. 

Karighattam discussed what could be done to shield local communities from urban heat islands. They suggested doubling the tree cover in areas with the lowest quartile tree coverage as one mitigating strategy, but noted that even small steps, like building a garden and raising awareness for this issue, can help.

Day of Climate echoed a consistent call to action, urging attendees to meaningfully engage in both education and action. Brown, who is an MIT Media Lab Director’s Fellow, spoke about how education and collective action will pave the way to tackle big societal challenges. “We need to invest in sustainability communities,” he said. “We need to invest in clean technology, and we need to invest in education that fosters environmental stewardship.”

Part of MIT’s broader sustainability efforts, including The Climate Project, the event reflected a commitment to building a resilient and sustainable future for all. Influenced by the Climate Action Through Education (CATE), Day of Climate panelist Sophie Shen shared how climate education inspired her civic life. “Learning about climate change has inspired me to take action on a wider systemic level,” she said.

Shen, a senior at Arlington High School and local elected official, emphasized how engagement and action looks different for everyone. “There are so many ways to get involved,” she said. “That could be starting a community garden — those can be great community hubs and learning spaces — or it could include advocating to your local or state governments.”

Becoming a catalyst for change 

The larger Day of Climate initiative encourages young people to understand the interdisciplinary nature of climate change and consider how the changing climate impacts many aspects of life. With curriculum available for learners from ages 4 to 18, these free activities range from Climate Change Charades — where learners act out words like “deforestation” and “recycling” — to Climate Change Happens Below Water, where learners use sensors to analyze water quality data like pH and solubility.

Many of the speakers at the event shared personal anecdotes from their childhood about how climate education, both in and out of the classroom, has changed the trajectory of their lives. Addaline Jorroff, deputy climate chief and director of mitigation and community resilience in the Office of Climate Resilience and Innovation for the Commonwealth of Massachusetts, explained how resources from MIT were instrumental in her education as a middle and high schooler, while Jaylen Brown told how his grandmother helped him see the importance of taking care of the planet, through recycling and picking up trash together, when he was young.

Claudia Urrea, director of the pK-12 team at Open Learning and director of Day of Climate, emphasizes how providing opportunities at schools — through new curriculum, classroom resources and mentorship — are crucial, but providing other educational opportunities also matter: in particular, opportunities that support learners in becoming strong leaders.

“I strongly believe that this event not only inspired young learners to take meaningful action, both large and small, towards a better future, but also motivated all the stakeholders to continue to create opportunities for these young learners to emerge as future leaders,” Urrea says.

The team plans to hold the Day of Climate event annually, bringing together young people, educators, and the MIT community. Urrea hopes the event will act as a catalyst for change — for everyone.

“We hope Day of Climate serves as the opportunity for everyone to recognize the interconnectedness of our actions,” Urrea says. “Understanding this larger system is crucial for addressing current and future challenges, ultimately making the world a better place for all.”

The Day of Climate event was hosted by the Day of Climate team in collaboration with MIT Climate Action Through Education (CATE) and Earth Day Boston.

Study helps pinpoint areas where microplastics will accumulate

Biofilms deposited by living organisms reduce the accumulation of small particles, while areas of bare sand can be microplastics hotspots.

The accumulation of microplastics in the environment, and within our bodies, is an increasingly worrisome issue. But predicting where these ubiquitous particles will accumulate, and therefore where remediation efforts should be focused, has been difficult because of the many factors that contribute to their dispersal and deposition.

New research from MIT shows that one key factor in determining where microparticles are likely to build up has to do with the presence of biofilms. These thin, sticky biopolymer layers are shed by microorganisms and can accumulate on surfaces, including along sandy riverbeds or seashores. The study found that, all other conditions being equal, microparticles are less likely to accumulate in sediment infused with biofilms, because if they land there, they are more likely to be resuspended by flowing water and carried away.

The open-access findings appear in the journal Geophysical Research Letters, in a paper by MIT postdoc Hyoungchul Park and professor of civil and environmental engineering Heidi Nepf. “Microplastics are definitely in the news a lot,” Nepf says, “and we don’t fully understand where the hotspots of accumulation are likely to be. This work gives a little bit of guidance” on some of the factors that can cause these particles, and small particles in general, to accumulate in certain locations.

Most experiments looking at the ways microparticles are transported and deposited have been conducted over bare sand, Park says. “But in nature, there are a lot of microorganisms, such as bacteria, fungi, and algae, and when they adhere to the stream bed they generate some sticky things.” These substances are known as extracellular polymeric substances, or EPS, and they “can significantly affect the channel bed characteristics,” he says. The new research focused on determining exactly how these substances affected the transport of microparticles, including microplastics.

The research involved a flow tank with a bottom lined with fine sand, and sometimes with vertical plastic tubes simulating the presence of mangrove roots. In some experiments the bed consisted of pure sand, and in others the sand was mixed with a biological material to simulate the natural biofilms found in many riverbed and seashore environments.

Water mixed with tiny plastic particles was pumped through the tank for three hours, and then the bed surface was photographed under ultraviolet light that caused the plastic particles to fluoresce, allowing a quantitative measurement of their concentration.

The results revealed two different phenomena that affected how much of the plastic accumulated on the different surfaces. Immediately around the rods that stood in for above-ground roots, turbulence prevented particle deposition. In addition, as the amount of simulated biofilms in the sediment bed increased, the accumulation of particles also decreased.

Nepf and Park concluded that the biofilms filled up the spaces between the sand grains, leaving less room for the microparticles to fit in. The particles were more exposed because they penetrated less deeply in between the sand grains, and as a result they were much more easily resuspended and carried away by the flowing water.

“These biological films fill the pore spaces between the sediment grains,” Park explains, “and that makes the deposited particles — the particles that land on the bed — more exposed to the forces generated by the flow, which makes it easier for them to be resuspended. What we found was that in a channel with the same flow conditions and the same vegetation and the same sand bed, if one is without EPS and one is with EPS, then the one without EPS has a much higher deposition rate than the one with EPS.”

Nepf adds: “The biofilm is blocking the plastics from accumulating in the bed because they can’t go deep into the bed. They just stay right on the surface, and then they get picked up and moved elsewhere. So, if I spilled a large amount of microplastic in two rivers, and one had a sandy or gravel bottom, and one was muddier with more biofilm, I would expect more of the microplastics to be retained in the sandy or gravelly river.”

All of this is complicated by other factors, such as the turbulence of the water or the roughness of the bottom surface, she says. But it provides a “nice lens” to provide some suggestions for people who are trying to study the impacts of microplastics in the field. “They’re trying to determine what kinds of habitats these plastics are in, and this gives a framework for how you might categorize those habitats,” she says. “It gives guidance to where you should go to find more plastics versus less.”

As an example, Park suggests, in mangrove ecosystems, microplastics may preferentially accumulate in the outer edges, which tend to be sandy, while the interior zones have sediment with more biofilm. Thus, this work suggests “the sandy outer regions may be potential hotspots for microplastic accumulation,” he says, and can make this a priority zone for monitoring and protection.

“This is a highly relevant finding,” says Isabella Schalko, a research scientist at ETH Zurich, who was not associated with this research. “It suggests that restoration measures such as re-vegetation or promoting biofilm growth could help mitigate microplastic accumulation in aquatic systems. It highlights the powerful role of biological and physical features in shaping particle transport processes.”

The work was supported by Shell International Exploration and Production through the MIT Energy Initiative.

Professor Emeritus Stanley Fischer, a towering figure in academic macroeconomics and global economic policymaking, dies at 81

Influential MIT economist and former vice chair of the US Federal Reserve inspired generations of students and helped shape modern macroeconomics.

Stanley Fischer PhD ’69, MIT professor emeritus of economics and a towering figure in both academic macroeconomics and global economic policymaking, passed away on May 31. He was 81. Fischer was a foundational scholar as well as a wise mentor and a central force in shaping the macroeconomic tradition of MIT’s Department of Economics that continues today.

“Together with Rudi Dornbusch and later Olivier Blanchard, Stan was one of the intellectual engines that powered MIT macroeconomics in the 1970s and beyond,” says Ricardo Caballero PhD ’88, one of Fischer’s advisees and now the Ford International Professor of Economics at MIT. “He was quietly brilliant, never flashy, and always razor-sharp. His students learned not just from his lectures or his groundbreaking work on New Keynesian models and rational expectations, but from the clarity of his mind and the gentleness of his wit. Nearly 40 years later, I can still hear him saying: ‘Isn’t it easier to do it right the first time than to explain why you didn’t?’ That line has stayed with me ever since. A simple comment from Stan during a seminar — often offered with a disarming smile — could puncture a weak argument or crystallize a central insight. He taught generations of macroeconomists to prize discipline, clarity, and policy relevance.”

Olivier Blanchard PhD ’77, the Robert M. Solow Professor of Economics Emeritus at MIT and another advisee, explains that Fischer “was one of the most popular teachers, and one of the most popular thesis advisers. We flocked to his office, and I suspect that the only time for research he had was during the night. What we admired most were his technical skills — he knew how to use stochastic calculus — and his ability to take on big questions and simplify them to the point where the answer, ex post, looked obvious. When Rudi Dornbusch joined him in 1975, macro and international quickly became the most exciting fields at MIT.” Within a decade of his joining the MIT faculty, “Stan had acquired near-guru status.”

Fischer built bridges between economic theory and the practice of economic policy. He served as chief economist of the World Bank (1988-90), first deputy managing director at the International Monetary Fund (IMF, 1994-2001), governor of the Bank of Israel (2005-13), and vice chair of the U.S. Federal Reserve (2014-17). These leadership roles gave him a rare platform to implement ideas he helped develop in the classroom and he was widely praised for his successes at averting financial crises across several decades and continents. Yet even as he moved through the highest circles of global policymaking, he remained a teacher at heart — accessible, thoughtful, and generous with his time.

At MIT, Fischer is best remembered for inspiring generations of graduate students who moved between academics and policy just as he did. Over the course of two decades before he began his active policy role, he was primary adviser for 49 PhD students, secondary adviser to another 23, and a celebrated teacher for many more. 

Many of his students became important macroeconomic policymakers, including Ben Bernanke PhD ’79; Mario Draghi PhD ’77; Ilan Goldfajn PhD ’95; Philip Lowe PhD ’91; and Kazuo Ueda PhD ’80, who chaired the Federal Reserve Board, the European Central Bank, the Banco Central do Brazil, the Reserve Bank of Australia, and the Bank of Japan. Students Gregory Mankiw PhD ’84 and Christina Romer PhD ’85 chaired the Council of Economic Advisors; Maurice Obstfeld PhD ’79 and Kenneth Rogoff PhD ’80 were chief economist at the International Monetary Fund; and Frederic Mishkin PhD ’76 was a governor of the Federal Reserve. Another of his students, former Treasury Secretary Lawrence Summers ’75, explains that “no one had more cumulative influence on the macroeconomic policymakers of the last generation than Stanley Fischer … We all were shaped by his clarity of thought, intellectual balance, personal decency, and quality of character. In a broader sense, everyone who was involved in the macro policy enterprise was Stan Fischer’s disciple. People all over the world who never knew his name lived better, more secure, lives because of all that he did through his teaching, writing, and service.”

Fischer grew up in Northern Rhodesia (now Zambia), living behind the general store his family ran before moving to Southern Rhodesia (now Zimbabwe) at the age of 13. Inspired by the quality of writing in John Maynard Keynes’ “The General Theory of Employment, Interest, and Money,” he applied for and won a scholarship to study at the London School of Economics. He moved to MIT for his graduate studies, where his dissertation was supervised by Franklin M. Fisher. After several years on the University of Chicago faculty, he returned to MIT in 1973, where he stayed for the remainder of his academic career. He held the Elizabeth and James Killian Class of 1926 professorship from 1992 to 1995, serving as department chair in 1993–94, before being called away to the IMF.

Fischer’s intellectual journey from MIT to Chicago and back culminated in his most influential academic work. Ivan Werning, the Robert M. Solow Professor of Economics at MIT notes, “his research was pathbreaking and paved the way to the modern approach to macroeconomics. By merging nominal rigidities associated with MIT’s Keynesian tradition with rational expectations emanating from the Chicago school, his 1977 paper on ‘Long-Term Contracts, Rational Expectations, and the Optimal Money Supply Rule’ showed how the non-neutrality of money did not require agent irrationality or confusion.” The dynamic stochastic general equilibrium models now used at every central bank to evaluate monetary policy options are direct descendants of Fischer’s thinking.

Fischer’s influence goes beyond what has become known as New Keynesian Economics. Werning continues, “Fischer’s research combined theoretical insights to very applied questions. His textbook with Blanchard was instrumental to an entire generation of macroeconomists, showing macroeconomics as a rich and evolving field, ripe with tools and great questions to study. Along with Bob Solow, Rudi Dornbusch, and others, Fischer had a huge impact within the MIT economics department and helped build its day-to-day culture, with an inquisitive, open-minded, and friendly atmosphere.”

Macroeconomics — and MIT — owe him a profound debt.

Fischer is survived by his three sons, Michael, David, and Jonathan, and nine grandchildren.

Study shows making hydrogen with soda cans and seawater is scalable and sustainable

The method’s overall carbon emissions are on par with those of other green hydrogen technologies.

Hydrogen has the potential to be a climate-friendly fuel since it doesn’t release carbon dioxide when used as an energy source. Currently, however, most methods for producing hydrogen involve fossil fuels, making hydrogen less of a “green” fuel over its entire life cycle.

A new process developed by MIT engineers could significantly shrink the carbon footprint associated with making hydrogen.

Last year, the team reported that they could produce hydrogen gas by combining seawater, recycled soda cans, and caffeine. The question then was whether the benchtop process could be applied at an industrial scale, and at what environmental cost.

Now, the researchers have carried out a “cradle-to-grave” life cycle assessment, taking into account every step in the process at an industrial scale. For instance, the team calculated the carbon emissions associated with acquiring and processing aluminum, reacting it with seawater to produce hydrogen, and transporting the fuel to gas stations, where drivers could tap into hydrogen tanks to power engines or fuel cell cars. They found that, from end to end, the new process could generate a fraction of the carbon emissions that is associated with conventional hydrogen production.

In a study appearing today in Cell Reports Sustainability, the team reports that for every kilogram of hydrogen produced, the process would generate 1.45 kilograms of carbon dioxide over its entire life cycle. In comparison, fossil-fuel-based processes emit 11 kilograms of carbon dioxide per kilogram of hydrogen generated.

The low-carbon footprint is on par with other proposed “green hydrogen” technologies, such as those powered by solar and wind energy.

“We’re in the ballpark of green hydrogen,” says lead author Aly Kombargi PhD ’25, who graduated this spring from MIT with a doctorate in mechanical engineering. “This work highlights aluminum’s potential as a clean energy source and offers a scalable pathway for low-emission hydrogen deployment in transportation and remote energy systems.”

The study’s MIT co-authors are Brooke Bao, Enoch Ellis, and professor of mechanical engineering Douglas Hart.

Gas bubble

Dropping an aluminum can in water won’t normally cause much of a chemical reaction. That’s because when aluminum is exposed to oxygen, it instantly forms a shield-like layer. Without this layer, aluminum exists in its pure form and can readily react when mixed with water. The reaction that occurs involves aluminum atoms that efficiently break up molecules of water, producing aluminum oxide and pure hydrogen. And it doesn’t take much of the metal to bubble up a significant amount of the gas.

“One of the main benefits of using aluminum is the energy density per unit volume,” Kombargi says. “With a very small amount of aluminum fuel, you can conceivably supply much of the power for a hydrogen-fueled vehicle.”

Last year, he and Hart developed a recipe for aluminum-based hydrogen production. They found they could puncture aluminum’s natural shield by treating it with a small amount of gallium-indium, which is a rare-metal alloy that effectively scrubs aluminum into its pure form. The researchers then mixed pellets of pure aluminum with seawater and observed that the reaction produced pure hydrogen. What’s more, the salt in the water helped to precipitate gallium-indium, which the team could subsequently recover and reuse to generate more hydrogen, in a cost-saving, sustainable cycle.

“We were explaining the science of this process in conferences, and the questions we would get were, ‘How much does this cost?’ and, ‘What’s its carbon footprint?’” Kombargi says. “So we wanted to look at the process in a comprehensive way.”

A sustainable cycle

For their new study, Kombargi and his colleagues carried out a life cycle assessment to estimate the environmental impact of aluminum-based hydrogen production, at every step of the process, from sourcing the aluminum to transporting the hydrogen after production. They set out to calculate the amount of carbon associated with generating 1 kilogram of hydrogen — an amount that they chose as a practical, consumer-level illustration.

“With a hydrogen fuel cell car using 1 kilogram of hydrogen, you can go between 60 to 100 kilometers, depending on the efficiency of the fuel cell,” Kombargi notes.

They performed the analysis using Earthster — an online life cycle assessment tool that draws data from a large repository of products and processes and their associated carbon emissions. The team considered a number of scenarios to produce hydrogen using aluminum, from starting with “primary” aluminum mined from the Earth, versus “secondary” aluminum that is recycled from soda cans and other products, and using various methods to transport the aluminum and hydrogen.

After running life cycle assessments for about a dozen scenarios, the team identified one scenario with the lowest carbon footprint. This scenario centers on recycled aluminum — a source that saves a significant amount of emissions compared with mining aluminum — and seawater — a natural resource that also saves money by recovering gallium-indium. They found that this scenario, from start to finish, would generate about 1.45 kilograms of carbon dioxide for every kilogram of hydrogen produced. The cost of the fuel produced, they calculated, would be about $9 per kilogram, which is comparable to the price of hydrogen that would be generated with other green technologies such as wind and solar energy.

The researchers envision that if the low-carbon process were ramped up to a commercial scale, it would look something like this: The production chain would start with scrap aluminum sourced from a recycling center. The aluminum would be shredded into pellets and treated with gallium-indium. Then, drivers could transport the pretreated pellets as aluminum “fuel,” rather than directly transporting hydrogen, which is potentially volatile. The pellets would be transported to a fuel station that ideally would be situated near a source of seawater, which could then be mixed with the aluminum, on demand, to produce hydrogen. A consumer could then directly pump the gas into a car with either an internal combustion engine or a fuel cell.

The entire process does produce an aluminum-based byproduct, boehmite, which is a mineral that is commonly used in fabricating semiconductors, electronic elements, and a number of industrial products. Kombargi says that if this byproduct were recovered after hydrogen production, it could be sold to manufacturers, further bringing down the cost of the process as a whole.

“There are a lot of things to consider,” Kombargi says. “But the process works, which is the most exciting part. And we show that it can be environmentally sustainable.”

The group is continuing to develop the process. They recently designed a small reactor, about the size of a water bottle, that takes in aluminum pellets and seawater to generate hydrogen, enough to power an electric bike for several hours. They previously demonstrated that the process can produce enough hydrogen to fuel a small car. The team is also exploring underwater applications, and are designing a hydrogen reactor that would take in surrounding seawater to power a small boat or underwater vehicle.

This research was supported, in part, by the MIT Portugal Program.

New 3D printing method enables complex designs and creates less waste

MIT engineers developed a technique for making intricate structures with supports that can be dissolved and reused instead of thrown away.

Hearing aids, mouth guards, dental implants, and other highly tailored structures are often products of 3D printing. These structures are typically made via vat photopolymerization — a form of 3D printing that uses patterns of light to shape and solidify a resin, one layer at a time.

The process also involves printing structural supports from the same material to hold the product in place as it’s printed. Once a product is fully formed, the supports are removed manually and typically thrown out as unusable waste.

MIT engineers have found a way to bypass this last finishing step, in a way that could significantly speed up the 3D-printing process. They developed a resin that turns into two different kinds of solids, depending on the type of light that shines on it: Ultraviolet light cures the resin into an highly resilient solid, while visible light turns the same resin into a solid that is easily dissolvable in certain solvents.

The team exposed the new resin simultaneously to patterns of UV light to form a sturdy structure, as well as patterns of visible light to form the structure’s supports. Instead of having to carefully break away the supports, they simply dipped the printed material into solution that dissolved the supports away, revealing the sturdy, UV-printed part.

The supports can dissolve in a variety of food-safe solutions, including baby oil. Interestingly, the supports could even dissolve in the main liquid ingredient of the original resin, like a cube of ice in water. This means that the material used to print structural supports could be continuously recycled: Once a printed structure’s supporting material dissolves, that mixture can be blended directly back into fresh resin and used to print the next set of parts — along with their dissolvable supports.

The researchers applied the new method to print complex structures, including functional gear trains and intricate lattices.

“You can now print — in a single print — multipart, functional assemblies with moving or interlocking parts, and you can basically wash away the supports,” says graduate student Nicholas Diaco. “Instead of throwing out this material, you can recycle it on site and generate a lot less waste. That’s the ultimate hope.”

He and his colleagues report the details of the new method in a paper appearing today in Advanced Materials Technologies. The MIT study’s co-authors include Carl Thrasher, Max Hughes, Kevin Zhou, Michael Durso, Saechow Yap, Professor Robert Macfarlane, and Professor A. John Hart, head of MIT’s Department of Mechanical Engineering.

Waste removal

Conventional vat photopolymerization (VP) begins with a 3D computer model of a structure to be printed — for instance, of two interlocking gears. Along with the gears themselves, the model includes small support structures around, under, and between the gears to keep every feature in place as the part is printed. This computer model is then sliced into many digital layers that are sent to a VP printer for printing.

A standard VP printer includes a small vat of liquid resin that sits over a light source. Each slice of the model is translated into a matching pattern of light that is projected onto the liquid resin, which solidifies into the same pattern. Layer by layer, a solid, light-printed version of the model’s gears and supports forms on the build platform. When printing is finished, the platform lifts the completed part above the resin bath. Once excess resin is washed away, a person can go in by hand to remove the intermediary supports, usually by clipping and filing, and the support material is ultimately thrown away.

“For the most part, these supports end up generating a lot of waste,” Diaco says.

Print and dip

Diaco and the team looked for a way to simplify and speed up the removal of printed supports and, ideally, recycle them in the process. They came up with a general concept for a resin that, depending on the type of light that it is exposed to, can take on one of two phases: a resilient phase that would form the desired 3D structure and a secondary phase that would function as a supporting material but also be easily dissolved away.

After working out some chemistry, the team found they could make such a two-phase resin by mixing two commercially available monomers, the chemical building blocks that are found in many types of plastic. When ultraviolet light shines on the mixture, the monomers link together into a tightly interconnected network, forming a tough solid that resists dissolution. When the same mixture is exposed to visible light, the same monomers still cure, but at the molecular scale the resulting monomer strands remain separate from one another. This solid can quickly dissolve when placed in certain solutions.

In benchtop tests with small vials of the new resin, the researchers found the material did transform into both the insoluble and soluble forms in response to ultraviolet and visible light, respectively. But when they moved to a 3D printer with LEDs dimmer than the benchtop setup, the UV-cured material fell apart in solution. The weaker light only partially linked the monomer strands, leaving them too loosely tangled to hold the structure together.

Diaco and his colleagues found that adding a small amount of a third “bridging” monomer could link the two original monomers together under UV light, knitting them into a much sturdier framework. This fix enabled the researchers to simultaneously print resilient 3D structures and dissolvable supports using timed pulses of UV and visible light in one run.

The team applied the new method to print a variety of intricate structures, including interlocking gears, intricate lattices, a ball within a square frame, and, for fun, a small dinosaur encased in an egg-shaped support that dissolved away when dipped in solution.

“With all these structures, you need a lattice of supports inside and out while printing,” Diaco says. “Removing those supports normally requires careful, manual removal. This shows we can print multipart assemblies with a lot of moving parts, and detailed, personalized products like hearing aids and dental implants, in a way that’s fast and sustainable.”

“We’ll continue studying the limits of this process, and we want to develop additional resins with this wavelength-selective behavior and mechanical properties necessary for durable products,” says professor of mechanical engineering John Hart. “Along with automated part handling and closed-loop reuse of the dissolved resin, this is an exciting path to resource-efficient and cost-effective polymer 3D printing at scale.”

This research was supported, in part, by the Center for Perceptual and Interactive Intelligence (InnoHK) in Hong Kong, the U.S. National Science Foundation, the U.S. Office of Naval Research, and the U.S. Army Research Office.

Teaching AI models what they don’t know

A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.

Artificial intelligence systems like ChatGPT provide plausible-sounding answers to any question you might ask. But they don’t always reveal the gaps in their knowledge or areas where they’re uncertain. That problem can have huge consequences as AI systems are increasingly used to do things like develop drugs, synthesize information, and drive autonomous cars.

Now, the MIT spinout Themis AI is helping quantify model uncertainty and correct outputs before they cause bigger problems. The company’s Capsa platform can work with any machine-learning model to detect and correct unreliable outputs in seconds. It works by modifying AI models to enable them to detect patterns in their data processing that indicate ambiguity, incompleteness, or bias.

“The idea is to take a model, wrap it in Capsa, identify the uncertainties and failure modes of the model, and then enhance the model,” says Themis AI co-founder and MIT Professor Daniela Rus, who is also the director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). “We’re excited about offering a solution that can improve models and offer guarantees that the model is working correctly.”

Rus founded Themis AI in 2021 with Alexander Amini ’17, SM ’18, PhD ’22 and Elaheh Ahmadi ’20, MEng ’21, two former research affiliates in her lab. Since then, they’ve helped telecom companies with network planning and automation, helped oil and gas companies use AI to understand seismic imagery, and published papers on developing more reliable and trustworthy chatbots.

“We want to enable AI in the highest-stakes applications of every industry,” Amini says. “We’ve all seen examples of AI hallucinating or making mistakes. As AI is deployed more broadly, those mistakes could lead to devastating consequences. Themis makes it possible that any AI can forecast and predict its own failures, before they happen.”

Rus’ lab has been researching model uncertainty for years. In 2018, she received funding from Toyota to study the reliability of a machine learning-based autonomous driving solution.

“That is a safety-critical context where understanding model reliability is very important,” Rus says.

In separate work, Rus, Amini, and their collaborators built an algorithm that could detect racial and gender bias in facial recognition systems and automatically reweight the model’s training data, showing it eliminated bias. The algorithm worked by identifying the unrepresentative parts of the underlying training data and generating new, similar data samples to rebalance it.

In 2021, the eventual co-founders showed a similar approach could be used to help pharmaceutical companies use AI models to predict the properties of drug candidates. They founded Themis AI later that year.

“Guiding drug discovery could potentially save a lot of money,” Rus says. “That was the use case that made us realize how powerful this tool could be.”

Today Themis AI is working with enterprises in a variety of industries, and many of those companies are building large language models. By using Capsa, these models are able to quantify their own uncertainty for each output.

“Many companies are interested in using LLMs that are based on their data, but they’re concerned about reliability,” observes Stewart Jamieson SM ’20, PhD ’24, Themis AI's head of technology. “We help LLMs self-report their confidence and uncertainty, which enables more reliable question answering and flagging unreliable outputs.”

Themis AI is also in discussions with semiconductor companies building AI solutions on their chips that can work outside of cloud environments.

“Normally these smaller models that work on phones or embedded systems aren’t very accurate compared to what you could run on a server, but we can get the best of both worlds: low latency, efficient edge computing without sacrificing quality,” Jamieson explains. “We see a future where edge devices do most of the work, but whenever they’re unsure of their output, they can forward those tasks to a central server.”

Pharmaceutical companies can also use Capsa to improve AI models being used to identify drug candidates and predict their performance in clinical trials.

“The predictions and outputs of these models are very complex and hard to interpret — experts spend a lot of time and effort trying to make sense of them,” Amini remarks. “Capsa can give insights right out of the gate to understand if the predictions are backed by evidence in the training set or are just speculation without a lot of grounding. That can accelerate the identification of the strongest predictions, and we think that has a huge potential for societal good.”

Research for impact

Themis AI’s team believes the company is well-positioned to improve the cutting edge of constantly evolving AI technology. For instance, the company is exploring Capsa’s ability to improve accuracy in an AI technique known as chain-of-thought reasoning, in which LLMs explain the steps they take to get to an answer.

“We’ve seen signs Capsa could help guide those reasoning processes to identify the highest-confidence chains of reasoning,” Jamieson says. “We think that has huge implications in terms of improving the LLM experience, reducing latencies, and reducing computation requirements. It’s an extremely high-impact opportunity for us.”

For Rus, who has co-founded several companies since coming to MIT, Themis AI is an opportunity to ensure her MIT research has impact.

“My students and I have become increasingly passionate about going the extra step to make our work relevant for the world," Rus says. “AI has tremendous potential to transform industries, but AI also raises concerns. What excites me is the opportunity to help develop technical solutions that address these challenges and also build trust and understanding between people and the technologies that are becoming part of their daily lives.”

3 Questions: How to help students recognize potential bias in their AI datasets

Courses on developing AI models for health care need to focus more on identifying and addressing bias, says Leo Anthony Celi.

Every year, thousands of students take courses that teach them how to deploy artificial intelligence models that can help doctors diagnose disease and determine appropriate treatments. However, many of these courses omit a key element: training students to detect flaws in the training data used to develop the models.

Leo Anthony Celi, a senior research scientist at MIT’s Institute for Medical Engineering and Science, a physician at Beth Israel Deaconess Medical Center, and an associate professor at Harvard Medical School, has documented these shortcomings in a new paper and hopes to persuade course developers to teach students to more thoroughly evaluate their data before incorporating it into their models. Many previous studies have found that models trained mostly on clinical data from white males don’t work well when applied to people from other groups. Here, Celi describes the impact of such bias and how educators might address it in their teachings about AI models.

Q: How does bias get into these datasets, and how can these shortcomings be addressed?

A: Any problems in the data will be baked into any modeling of the data. In the past we have described instruments and devices that don’t work well across individuals. As one example, we found that pulse oximeters overestimate oxygen levels for people of color, because there weren’t enough people of color enrolled in the clinical trials of the devices. We remind our students that medical devices and equipment are optimized on healthy young males. They were never optimized for an 80-year-old woman with heart failure, and yet we use them for those purposes. And the FDA does not require that a device work well on this diverse of a population that we will be using it on. All they need is proof that it works on healthy subjects.

Additionally, the electronic health record system is in no shape to be used as the building blocks of AI. Those records were not designed to be a learning system, and for that reason, you have to be really careful about using electronic health records. The electronic health record system is to be replaced, but that’s not going to happen anytime soon, so we need to be smarter. We need to be more creative about using the data that we have now, no matter how bad they are, in building algorithms.

One promising avenue that we are exploring is the development of a transformer model of numeric electronic health record data, including but not limited to laboratory test results. Modeling the underlying relationship between the laboratory tests, the vital signs and the treatments can mitigate the effect of missing data as a result of social determinants of health and provider implicit biases.

Q: Why is it important for courses in AI to cover the sources of potential bias? What did you find when you analyzed such courses’ content?

A: Our course at MIT started in 2016, and at some point we realized that we were encouraging people to race to build models that are overfitted to some statistical measure of model performance, when in fact the data that we’re using is rife with problems that people are not aware of. At that time, we were wondering: How common is this problem?

Our suspicion was that if you looked at the courses where the syllabus is available online, or the online courses, that none of them even bothers to tell the students that they should be paranoid about the data. And true enough, when we looked at the different online courses, it’s all about building the model. How do you build the model? How do you visualize the data? We found that of 11 courses we reviewed, only five included sections on bias in datasets, and only two contained any significant discussion of bias.

That said, we cannot discount the value of these courses. I’ve heard lots of stories where people self-study based on these online courses, but at the same time, given how influential they are, how impactful they are, we need to really double down on requiring them to teach the right skillsets, as more and more people are drawn to this AI multiverse. It’s important for people to really equip themselves with the agency to be able to work with AI. We’re hoping that this paper will shine a spotlight on this huge gap in the way we teach AI now to our students.

Q: What kind of content should course developers be incorporating?

A: One, giving them a checklist of questions in the beginning. Where did this data came from? Who were the observers? Who were the doctors and nurses who collected the data? And then learn a little bit about the landscape of those institutions. If it’s an ICU database, they need to ask who makes it to the ICU, and who doesn’t make it to the ICU, because that already introduces a sampling selection bias. If all the minority patients don’t even get admitted to the ICU because they cannot reach the ICU in time, then the models are not going to work for them. Truly, to me, 50 percent of the course content should really be understanding the data, if not more, because the modeling itself is easy once you understand the data.

Since 2014, the MIT Critical Data consortium has been organizing datathons (data “hackathons”) around the world. At these gatherings, doctors, nurses, other health care workers, and data scientists get together to comb through databases and try to examine health and disease in the local context. Textbooks and journal papers present diseases based on observations and trials involving a narrow demographic typically from countries with resources for research. 

Our main objective now, what we want to teach them, is critical thinking skills. And the main ingredient for critical thinking is bringing together people with different backgrounds.

You cannot teach critical thinking in a room full of CEOs or in a room full of doctors. The environment is just not there. When we have datathons, we don’t even have to teach them how do you do critical thinking. As soon as you bring the right mix of people — and it’s not just coming from different backgrounds but from different generations — you don’t even have to tell them how to think critically. It just happens. The environment is right for that kind of thinking. So, we now tell our participants and our students, please, please do not start building any model unless you truly understand how the data came about, which patients made it into the database, what devices were used to measure, and are those devices consistently accurate across individuals?

When we have events around the world, we encourage them to look for data sets that are local, so that they are relevant. There’s resistance because they know that they will discover how bad their data sets are. We say that that’s fine. This is how you fix that. If you don’t know how bad they are, you’re going to continue collecting them in a very bad manner and they’re useless. You have to acknowledge that you’re not going to get it right the first time, and that’s perfectly fine. MIMIC (the Medical Information Marked for Intensive Care database built at Beth Israel Deaconess Medical Center) took a decade before we had a decent schema, and we only have a decent schema because people were telling us how bad MIMIC was.

We may not have the answers to all of these questions, but we can evoke something in people that helps them realize that there are so many problems in the data. I’m always thrilled to look at the blog posts from people who attended a datathon, who say that their world has changed. Now they’re more excited about the field because they realize the immense potential, but also the immense risk of harm if they don’t do this correctly.

Chancellor Melissa Nobles’ address to MIT’s undergraduate Class of 2025

Nobles urged graduates to be “bold and imaginative” in tackling big problems, “and to do so with compassion and generosity.”

Below is the text of Melissa Nobles’ remarks, as prepared for delivery today.

Wow, thank you Emily and Andrew! Emily Jin on vocals and Andrew Li on saxophone, and their fellow musicians!

Class of 2025! Look at you, you’re looking really good in your regalia! It’s your graduation day! You did it! Congratulations!

And congratulations to all of your loved ones, all of the people who helped support you.

Your parents, your brothers and sisters, your aunties and your uncles, and your friends. This is a special day for them too. They are so proud of you!

A warm welcome to the loved ones who are here with us today on Killian Court — they’ve come here from all over to celebrate you!

And a special shout out to those who are watching from afar, wishing they could be here with you in person!

Class of 2025, you’ve made a lot of memories during your time here: from classes to crushes, from the East Campus REX build to the Simmons ball pit to Next Haunt, from UROPs to the Hobby Shop, and from the Outfinite to the Infinite!

So, I’d like to take you back to the fall of 2021, when you arrived here at MIT.

You traveled from all parts of this country and the world — from 62 countries, to be exact — and landed right here in Cambridge. Together, you became MIT’s Class of 2025.

And you arrived on campus — all bright-eyed and beaver-tailed — after missing a lot of in-person high school rituals, a lot of the high school experience. So, you were extra eager for college, and, more specifically, super excited to be MIT students!

Although the campus was officially fully open for the first time since the Covid shutdown — students, staff, and faculty were all here in person, with Zoom taking a back seat to meeting in real life — there were still a lot of protocols in place.

You had to get through all the Covid tests because we were still testing. Do you remember those Ziploc bags?

You swabbed and submitted attestations because you wanted the keys to unlock doors to labs, classrooms, and all the experiences that make MIT, MIT.

And once you gained access, you discovered a campus that was shiny and welcoming, yet dusty after being mostly empty for a long while. And there was no manual for how to reanimate this place.

You didn’t flinch.

You chose MIT because you like to solve problems, and your inner beaver came out to bring the campus back to life, to make it a home.

You were curious, you surveyed the landscape, and you started to dig into the past in order to build your future.

You sought out seniors, the Class of 2022, to read you in, to show you the ropes, and they really came through for you. They felt the urgency of their limited time left on campus, and they taught you “how to MIT.”

You also pored through archival records of clubs, soaking up history to guide you forward. You filled in the gaps by speaking with faculty and staff and alums. You evaluated the options, decided what you wanted to revive and what you wanted to scrap.

And true to your nature as MIT students, you launched new stuff. You innovated and invented.

And you built communities, from FPOPs and orientation through 8.01, 18.02, your HASS classes, and your p-set groups.

You built communities in your dorms and in your sororities and fraternities.

You built communities through your sports, through your hobbies and through the arts.

You built communities all across campus.

And you learned that building communities is not always easy and quick. It takes effort, patience, and a willingness to listen to and learn from others.

But, in the end, it is so worth it because you’ve met and made friends with really interesting people. Some with similar backgrounds and others from very different backgrounds. And from that interesting and diverse group, you’ve identified your crew — the people with whom you’ve shared not only interests — but your dreams, your fears, your concerns, laughs, and tears. You’ve made real connections — connections that lead to a lifetime of friendship.

And over the past four years, right before our eyes, you’ve demonstrated the enduring value and power of higher education to change lives.

Throughout your time at MIT, you ideated, prototyped, and tested. You created new knowledge, waded through ambiguity, worked collaboratively, and, of course, you optimized.

Now, on your graduation day, we send you on your way with enormous pride and hope.

But at the same time, we are sending you out into the world at a very difficult and challenging time. It’s a time when we all are being asked to focus on traditions that we should honor and defend. It’s also a time calling on us to create new traditions, better suited to human thriving in this century.

It’s a time when the issues are big, the answers are complex, the stakes are high, and the paths are uncharted.

But, Class of 2025, you are prepared to face these daunting conditions. In the words of one of your classmates: MIT taught the Class of 2025 to have “confidence in your competence.”

You are ready to assess your environment, diagnose what is stale and what is broken, learn from history, apply your talents and skills, and create new knowledge.

You are ready to tackle the toughest of problems! You are ready to shape the future.   

And while you are doing so, I ask that you keep MIT’s values and mission at the center of your efforts: to be bold and imaginative in tackling these big problems and to do so with compassion and generosity.

Now, more than ever, we — meaning the world’s people — need you to lean in.

Once again, Congratulations Class of 2025!

Mary Robinson urges MIT School of Architecture and Planning graduates to “find a way to lead”

The former president of Ireland provides wit and wisdom to the graduating Class of 2025 and guests.

“Class of 2025, are you ready?”

This was the question Hashim Sarkis, dean of the MIT School of Architecture and Planning, posed to the graduating class at the school’s Advanced Degree Ceremony at Kresge Auditorium on May 29. The response was enthusiastic applause and cheers from the 224 graduates from the departments of Architecture and Urban Studies and Planning, the Program in Media Arts and Sciences, and the Center for Real Estate.

Following his welcome to an audience filled with family and friends of the graduates, Sarkis introduced the day’s guest speaker, whom he cited as the “perfect fit for this class.” Recognizing the “international rainbow of graduates,” Sarkis welcomed Mary Robinson, former president of Ireland and head of the Mary Robinson Foundation — Climate Justice to the podium. Robinson, a lawyer by training, has had a wide-ranging career that began with elected positions in Ireland followed by leadership roles in global causes for justice, human rights, and climate change.

Robinson laced her remarks with personal anecdotes from her career, from with earning a master’s in law at nearby Harvard University in 1968 — a year of political unrest in the United States — to founding The Elders in 2007 with world leaders: former South African President Nelson Mandela, anti-apartheid and human rights activist Desmond Tutu, and former U.S. President Jimmy Carter.

She described an “early lesson” in recounting her efforts to reform the laws of contraception in Ireland at the beginning of her career in the Irish legislature. Previously, women were not prescribed birth control unless they were married and had irregular menstrual cycles certified by their physicians. Robinson received thousands of letters of condemnation and threats that she would destroy the country of Ireland if she would allow contraception to be more broadly available. The legislation introduced was successful despite the “hate mail” she received, which was so abhorrent that her fiancé at the time, now her husband, burned it. That experience taught her to stand firm to her values.

“If you really believe in something, you must be prepared to pay a price,” she told the graduates.

In closing, Robinson urged the class to put their “skills and talent to work to address the climate crisis,” a problem she said she came late to in her career.

“You have had the privilege of being here at the School of Architecture and Planning at MIT,” said Robinson. “When you leave here, find ways to lead.”

Sally Kornbluth’s charge to the Class of 2025

MIT’s president urges graduates to become ambassadors for scientific thinking and discovery.

Below is the text of President Sally Kornbluth’s 2025 MIT Commencement remarks, as prepared for delivery today.

Good afternoon, everyone! Governor Healey. The members of the Class of 1975, in their incredibly fashionable red jackets! And of course, all the members of the Class of 2025 — and your devoted family and friends!

At MIT, it’s customary for the president to deliver a “charge” to the graduating class. And I’ll start by reflecting briefly on the world we make together here at MIT.

At MIT, we allow a lot of room for disagreement, whether the subject is scientific, personal, or political. The friction of disagreement is a very effective way to sharpen each other’s thinking. (If you don’t believe me, I’d urge you to attend a faculty meeting!)

But in this disconcerting time, as we prepare to send the Class of 2025 out into the world, I want to 
celebrate three fundamental things we do agree on — the rock-solid foundation of our shared work and understanding.

First, we believe in the beauty and power of the scientific method. Winston Churchill once observed that, “No one pretends that democracy is perfect or all-wise,” In fact, as he famously acknowledged, “Democracy is the worst form of government — except for all the other forms that have been tried.”

And you could say the same — with reverence! — for the scientific method. None of us would argue that it’s “perfect or all-wise.”

But the scientific method remains the single most reliable tool humans have ever devised to arrive at the truth about the physical world. It’s designed to root out error, protect us against our own biases and assumptions, and provide a systematic way to turn facts we cannot see at first into knowledge we can act on. 

It’s hard to imagine anything more useful than that.

Second, we believe in the beauty and power of fundamental scientific discovery – that incredibly intricate, maddening, heroic, intoxicating process of exploration and testing that somehow got stuck with the bland label “basic research.” 
 

We believe scientific discovery is deeply valuable and inspiring, in itself — and we know that it’s absolutely essential for driving innovation and delivering new tools, technologies, treatments, and cures.

And finally — from direct personal experience here at MIT — we all know that we’re sharper, more rigorous, more curious, more inventive and more likely to achieve breakthrough results when we work together with brilliant people, across a broad spectrum of backgrounds, perspectives, and viewpoints, from across the country and all around the world.

You don’t find the big ideas in an echo chamber! 

And I want to say something I’ve said repeatedly: MIT would not be MIT without our international students!

*              *

The beauty and power of the scientific method. The beauty and power of scientific discovery. And frankly, the beauty and power of the Institute’s incredible global community. 

For those of us associated with MIT, these three concepts may seem almost too obvious to require explanation, let alone celebration.

But we find ourselves in a bewildering time, a time when these concepts have never been more important — and have rarely been in such peril.

So now, I offer my charge to the members of the Class of 2025.

To today’s graduates:

I hope and believe that, in your time here, you’ve prepared yourselves very effectively for the next steps in your life and career. I wish you every success in that next step, and all that come after it.

But I must ask that each of you take on another job. A lifelong job. An urgent job.

I need you all to become ambassadors for the way we think and work and thrive at MIT.

Ambassadors for scientific thinking and scientific discovery! For thoughtful research of every kind, here — and at universities across the country! For the importance of research to the advancement of our nation — and our species! And ambassadors for the limitless possibilities when we understand, appreciate and magnify each other’s talent and potential, in a thriving global community.

This ambassadorship has no salary besides your sense of its crucial importance. But I hope you will accept the responsibility — because no one else can make the case more effectively. And these concepts are the indispensable foundation of everything else we aim to achieve.

*              *

There’s only one way to get through MIT.

The hard way.

Each of you has done that — and in the context of historic challenges. May all the strengths and insights that you’ve gained here serve you brilliantly on the road ahead. Thank you — and congratulations!

Hank Green urges the Class of 2025 to work on “everyday solvable problems of normal people”

Lively Commencement ceremony gives students, family, and friends a chance to celebrate years of hard work by the Institute’s newest graduates.

An energetic OneMIT Commencement ceremony today featured calls for MIT’s newest graduates to have a positive impact on society while upholding the Institute’s core values of open inquiry and productive innovation.

“Orient yourself not just toward the construction and acquisition of new tools, but to the needs of people,” said science communicator Hank Green, in the event’s keynote remarks. He urged MIT’s newest graduates to focus their work on the “everyday solvable problems of normal people,” even if it is not always the easiest or most obvious course of action.

“Because people are so complex and messy, some of you may be tempted to build around them and not for them,” Green continued. “But remember to ask yourself where value and meaning originate, where they come from.” He then provided one answer: “Value and meaning come from people.”

Green is a hugely popular content creator and YouTuber whose work often focuses on science and STEM issues, and who has built, with his brother, John, the educational media company Complexly. Their content, including the channels SciShow and CrashCourse, is widely used in schools and has tallied over 2 billion views. Green, a cancer survivor, is also writing a book explaining the biology of cancer.

The ceremony also featured remarks from MIT President Sally A. Kornbluth, who delivered the traditional “charge” to new graduates while reflecting on the values of MIT and the value it brings society.

“We believe scientific discovery is deeply valuable and inspiring in itself — and we know that it’s absolutely essential for driving innovation and delivering new tools, technologies, treatments, and cures,” she said.

Kornbluth challenged graduates to be “ambassadors” for the open-minded inquiry and collaborative work that marks everyday life at MIT.

“I need you all to become ambassadors for the way we think and work and thrive at MIT,” she said. “Ambassadors for scientific thinking and scientific discovery. For thoughtful research of every kind — here, and at universities across the country. For the importance of research to the advancement of our nation — and our species. And ambassadors for the limitless possibilities when we understand, appreciate and magnify each other’s talent and potential, in a thriving global community.”

Kornbluth also elaborated on the core elements of the work MIT has always pursued.

“At MIT, we allow a lot of room for disagreement, whether the subject is scientific, personal or political,” Kornbluth said. Still, she noted, “in this disconcerting time, as we prepare to send the Class of 2025 out into the world, I want to celebrate three fundamental things we do agree on — the rock-solid foundation of our shared work and understanding.”

The first of these, Kornbluth said, is that “we believe in the beauty and power of the scientific method. … It’s designed to root out error, protect us against our own biases and assumptions, and provide a systematic way to turn facts we cannot see at first into knowledge we can act on. It’s hard to imagine anything more useful than that.” Secondly, she said, in a similar vein, “we believe in the beauty and power of fundamental scientific discovery.”

A third element, Kornbluth observed, is that “we all know that we’re sharper, more rigorous, more curious, more inventive and more likely to achieve breakthrough results when we work together with brilliant people, across a broad spectrum of backgrounds, perspectives and viewpoints, from across the country and all around the world. You don’t find the big ideas in an echo chamber.”

Kornbluth added: “I want to say something I’ve said repeatedly: MIT would not be MIT without our international students.”

MIT’s Commencement celebrations are taking place this week, from May 28 through May 30. The OneMIT Commencement Ceremony is an Institute-wide event, held in MIT’s Killian Court and streamed online. MIT’s undergraduates, as well as advanced degree students in its five schools and the MIT Schwarzman College of Computing, also have additional, separate ceremonies in which graduates receive their degrees individually.The OneMIT event also featured remarks from Massachusetts Governor Maura Healey, who said she was “incredibly proud” of the graduates and the Institute itself.

“You stand for the qualities that make Massachusetts special: a passion for learning and discovery that is so powerful it changes the world,” Healey said. “Curing disease. Inventing technologies. Solving tough problems for communities, organizations, and people all around the globe. Making lives better and powering our economies. Thanks to you, Massachusetts is No. 1 for innovation and education.” She added: “MIT’s contributions to our knowledge economy — and our culture of discovery — are a pillar of Massachusetts’ national and global leadership.”

Speaking of the economic impact of MIT-linked businesses, Healey had an additional suggestion for the graduates: “Put your talents to work in Massachusetts, a place where you are valued, respected, and surrounded by incredibly talented, engaged innovators and investors. Make your discoveries here. Found your startups here. Scale your companies here.”

She even quipped, “We put forward some pretty good incentives through our economic development legislation and we’ll help you find a way to spend that. Just reach out to my economic development team.”

Green imparted general life advice as well.

“One of the problems you will solve is how to find joy in an imperfect world,” Green said in his Commencement address. “And you might struggle with not feeling productive, unless and until you accept that your own joy can be one of the things you produce.”

On another note, Green added, “Ideas do not belong in your head. They can’t help anyone in there. I sometimes see people become addicted to their good idea. … They can’t bring themselves to expose it to the imperfection of reality. Stop waiting. Get the ideas out. … You may fail, but while you fail, you will build new tools.”

Throughout his speech, Green emphasized the humanitarian qualities of MIT’s students. This past semester, after being named Commencement speaker, he sent the graduating class a survey that about half of the class responded to.

The survey included the question, “What gives you hope?” In his speech, Green said the many of the responses involved other people. Or, as he characterized it, “People who care. People who focus on improving life in their communities. People who are standing up for what they believe in. People who see big problems and have the determination to fix them.”

The OneMIT ceremony began with the annual alumni parade, this time featuring the undergraduate class of 1975, while the Killian Court Brass Ensemble, conducted by Kenneth Amis, played the processional entry music.

The Chaplain to the Institite, Thea Keith-Lucas, delivered the invocation, while the campus a capella group, the Chorallaries of MIT, sang “The Star Spangled Banner,” and later, the school song, “In praise of MIT,” as well as another Institute anthem, “Take Me Back to Tech.”

Despite many uncertainties facing higher education, the MIT students, families, friends, and community members present reveled in a festive moment, celebrating the achievements of the graduates. A total of 1,158 undergraduate and 2,593 graduate students received MIT diplomas this academic year.

“There’s only one way to get through MIT,” Kornbluth quipped. “The hard way.” 

Commencement address by Hank Green

“Do not forget how special and bizarre it is to get to live a human life,” the science communicator and video creator told the Class of 2025.

Below is the text of Hank Green’s Commencement remarks as prepared for delivery on May 29.

I don’t really do imposter syndrome, that’s where you feel like you don’t belong. I have a superior syndrome called “Hahaha I fooled them again” syndrome where I know that I don’t belong, but I also am very pleased that I have once again cleverly convinced you that I do.

I, a man you might very well know as a tiktoker, a man who recently blind-ranked AI company logos by how much they look like buttholes, have snuck into giving MIT’s Commencement speech. And I can admit this because you can’t kick me off now, I’ve already started speaking! It would be weird if you stopped … but still, I’m going to try to do a good job.

Hello and thank you very much to everybody for welcoming me out, all the lovely people up here, the president, the governor, the alumni, Class of 75, and also of course, thank you especially to a class of extremely impressive charismatic and attractive students of the Massachusetts Institute of Technology graduating Class of 2025.

To express my thanks: The average human skeleton has more than 25,000 calories. More than half of your bones are in your hands and feet, and all together your skeleton contains enough oxygen atoms that, if you freed them, you could produce around 24 hours of breathable air.

Those were some of my best bone facts, and I assume that good bone facts are a totally normal way for humans to show gratitude.

I gave you my very best bone facts because I owe an extra debt of gratitude to you, the Class of 2025, because more than half of you filled out a survey I sent you! I assume you did it late at night while you should have been p-setting, whatever that is, but instead you did this.

And I have loved looking through your responses and learning a little bit about you, and a little bit from you.

One of the things asked you what the most MIT thing you did at MIT was, and this was my favorite section to read.

Some of it was definitely not meant for me to understand, like several of you counted up all the smoots on the Harvard Bridge.

Whatever that means … good work.

One of you was Tim the Beaver. Another tried to impress a date with train facts.

I see you. Same … but with bones.

A lot, and I mean a lot of you simply said the word “hack,” and the lack of specificity there, I have to say, does make me feel like whatever you did, the statute of limitations has not yet kicked in.

But by far the most common beginning of a sentence in this section was “I built…” You built robots and bridges and incubators and startups and Geiger counters and a remote-controlled shopping cart and a ukelele and an eight-foot-wide periodic table. Y’all built … a lot.

And that is something I found reassuring. We are going to need to do a lot of building.

I took a look at your shoes as you were coming, but it turns out I didn’t need to see them to know I wouldn’t want to be in them.

I think the only people jealous of you right now is the Class of 2026 because I’m sure things will be even more screwed up by the time they’re sitting where you are. But what a terribly messy time to be graduating from college. The attacks on speech, on science, on higher education, on trans rights, on the federal workforce, on the rule of law … they’re coming from inside the house.

Meanwhile, the world is getting hotter faster. And the sudden acceleration in the abilities of artificial intelligence, communication, and biotechnology promise huge opportunities, and massive disruption.

So, if I were you, I would want some advice! But as previously mentioned, I am a TikTok-er who will now forever be known as the first person to ever say the word “butthole” during an MIT commencement speech. So the advice — some of it — is going to come from you. I asked you, in my survey, what you would say to your classmates from a stage like the one I am now on. And here’s a selection.

One of your classmates wrote:

I always forget which Green brother is Hank and which is John!

There is no one definition of success. The idea you have in your head of what success is, it’s going to change, and you should let it.

Is one of your classmates 45 years old?

And here’s another 45-year-old hiding among you:

Open a Roth IRA.

Jeez! Did your dad fill out my survey for you? Seriously though, you should.

Here’s one of my real favorites:

Collaborate and help each other, be brave in reaching out, and be forgiving in your interactions.

Even if it probably won't work, try anyway.

Don’t start with the solution, start with the problem.

Now a lot of you might be thinking right now: Did he just make us write his Commencement speech for him? And the answer to that is, well, at least you know that Claude didn’t write it.

I’ve had a good time here focusing on the ludicrous aspects of my career, and I do want to emphasize its ludicriousness.

I’ve done TikTok dances to Elmo remixes, and I’ve also published two best-selling science fiction novels. I’ve written fart listicles, and I’ve interviewed presidents. I’ve made multiple videos about giraffe sex, and I’ve sold multiple companies. I helped build an educational media company that provides videos for free to everyone with an internet connection, and our content is used in most American schools.

And yes, that was the section I put in so your parents could feel better about me being here. I left it as long as I could.

I am good at having an idea I believe in and then just doing it, consequences be damned, and that has served me well, though it has not always been relaxing.

And I did that all on the uncertain and rapidly changing ground of online video and social media over the last 20 years. So perhaps I do have something to say to a class of graduates heading out into an uncertain and unstable world.

If I could attribute my success, whatever it is, to anything besides luck, it’s that I literally can’t stop believing that there is any better use of time than learning something new.

And curiosity doesn’t just expand the number of tools you have and how well you’re able to use them, it expands your understanding of the problem space.

And so maybe the advice is very simple. Just be curious about the world and you’ll have everything you need for the future and, look, it is almost that simple.

There’s a really important question I asked y’all in my survey that I haven’t mentioned yet. I asked, “What’s giving you hope?”

And though one of you wrote “Macallan 12,” most of you, in your response, talked entirely about people: my friends, my family, my peers, over and over.

People who care. People who focus on improving life in their communities. People who are standing up for what they believe in. People who see big problems and have the determination to fix them.

At a school like MIT, I imagine that the focus can definitely be on the building and less on the people. This is an institute of technology, not of humanities. But I read the humanity in your answers.

And this brings me back to the simplicity of curiosity leading you both toward understanding problems and acquiring new tools. Because your curiosity is not out of your control. You decide how you orient it, and that orientation is going to affect the entire rest of your life. It may be the single most important factor in your career.

And my guess is that it’s going to be really easy to be focused on the problem of just building ever more powerful tools. That’s exciting stuff and also it can be surprisingly uncomplicated. But even though the problem space is much bigger than just “build bigger tools,” it is surprisingly easy to simply never notice that.

The most powerful mechanisms that steer our focus are … I’m just going to say this … not always designed for our best interests, or the best interests of our world. Social content platforms are great at steering our curiosities and they are, often, designed to make us afraid, to keep us oriented toward impossible problems, or toward the hottest rifts in society.

Meanwhile, the capitalist impulse is very good at keeping us oriented toward the problems that can be most easily monetized, and that means an over-weighting toward the problems that the most powerful and wealthy people are interested in solving.

If we let ourselves be oriented only by those forces, guess what problems we will not pay any attention to. All of the everyday solvable problems of normal people.

I desperately hope that you remain curious about our world’s intensely diverse and massive problem space. Solveable problems! That are not being addressed because our world does not orient us toward them. If you can control your obsessions, you will not just be unstoppable, you will leave this world a much better place than you found it.

This is not about choosing between financial stability and your ideals. No. There is money to be made in these spaces. This is simply about who you include in your problem space, about what you choose to be curious about.

So with that in mind, here’s my advice, from my heart and from my experience.

First, don’t eat grass.

Second, more importantly, one of the problems you will solve is how to find joy in an imperfect world. And you might struggle with not feeling productive unless and until you accept that your own joy can be one of the things you produce.

Third, ideas do not belong in your head. They can’t help anyone in there. I sometimes see people become addicted to their good idea. They love it so much, they can’t bring themselves to expose it to the imperfection of reality. Stop waiting. Get the ideas out. You may fail, but while you fail, you will build new tools.

And fourth, because people are so complex and messy, some of you may be tempted to build around them and not for them. But remember to ask yourself where value and meaning come from, because they don’t come from banks or tech or cap tables. They come from people.

People things are the hardest work, but also often the most important work. Orient yourself not just toward the construction and acquisition of new tools, but to the needs of people, and that include you, it includes your friends and your family. I think we can sometimes feel so powerful and like the world is so big that throwing a birthday party or making a playlist for a friend can seem too insignificant when placed against the enormity of AI and climate change and the erosion of democracy. But those thoughts alienate you from the reality of human existence, from your place as a builder not just of tools, but of meaning. And that’s not just about impact and productivity and problem solving, it is about living a life.

Do. Not. Forget. how special and bizarre it is to get to live a human life. It took 3 billion years for the Earth to go from single-celled life forms to you. That’s more than a quarter of the life of the entire universe. Something very special and strange is happening on this planet and it is you.

The greatest thing you build in your life will be yourself, and trust me on this you are not done yet, I know I’m not. But what you will be building is not just a toolkit. You will be building a person, and you will be doing it for people.

When I asked you what you did at MIT, you said you built, but when I asked you what was giving you hope, you did not say “buildings” you said “people.” So, to the graduating Class of 2025, go forth, for yourself, for others, and for this beautiful, bizarre world.

Thank you.

MIT Corporation elects 10 term members, three life members

The term members will serve between three and five years on MIT’s board of trustees.

The MIT Corporation — the Institute’s board of trustees — has elected 10 full-term members, who will serve three- or five-year terms, and three life members. Corporation Chair Mark P. Gorenberg ’76 announced the election results today.

The full-term members are: Wes Bush, Ruby R. Chandy, Hala Fadel, Jacques Frederic Kerrest, Michelle K. Lee, Bianca Lepe, Natalie M. Lorenz Anderson, Sebastian S. Man, Hyun-A C. Park, and Thomas Tull. The three life members are: Orit Gadiesh, Jeff Halis, and Alan Leventhal. Gorenberg was also re-elected as Corporation chair.

Stephen P. DeFalco ’83, SM ’88, the 2025-2026 president of the Association of Alumni and Alumnae of MIT, will also join the Corporation as an ex officio member. He succeeds Natalie Lorenz-Anderson ’84.

As of July 1, the Corporation will consist of 80 distinguished leaders in education, science, engineering, and industry. Of those, 24 are life members and eight are ex officio. An additional 31 individuals are life members emeritus.

The 10 term members are:

Wes Bush, former chair and chief executive officer, Northrop Grumman Corporation

Bush has worked in the aerospace and defense industry since starting at COMSAT Labs under MIT’s co-op program. After graduation, he first worked at The Aerospace Corporation, then became a systems engineer at TRW’s Space Park facility in 1987. Prior to Northrop Grumman’s acquisition of TRW in 2002, he led numerous space program activities, served as vice president of TRW Ventures, and was the president and chief executive officer of TRW’s U.K.-based Aeronautical Systems business. At Northrop Grumman, Bush served as the president of the company’s space technology sector, then as its chief financial officer. He became president of the company in 2006, served as chief executive officer from 2010 through 2018, and became chairman in 2011.

Ruby R. Chandy ’82, SM ’89, CEO, Luminas Advisory Services

With 20 years of public company board experience, Chandy currently serves on the boards of Dupont, Thermo Fisher Scientific, and Flowserve. She is on the advisory board of Pritzker Private Capital and serves on boards of its portfolio companies. She was formerly president of the industrial division and a corporate officer at Pall Corporation, which was acquired by Danaher Corporation. Prior to Pall, she served as chief marketing officer at Dow Chemical, Rohm and Haas, and Thermo Fisher Scientific. She has extensive general management experience at Dow Chemical, Thermo Fisher Scientific, Boston Scientific, and Millipore. Chandy also currently serves on the Board of the NACD Philadelphia Chapter, the Board of Trustees for Cristo Rey Philadelphia High School, and the MIT Sloan Executive Board.

Hala Fadel MBA ’01, managing partner, Eurazeo

Fadel is a member of the management committee of Eurazeo and leads the investment committee of the growth equity team. Prior to joining Eurazeo in 2022, she built Comgest’s inaugural private growth equity program. She also spent nearly 15 years at Comgest as a portfolio manager within the European growth equities team, leading investments in technology, as well as in health care and consumer goods. From 2014 to 2022, she served as co-founder and managing partner of Leap Ventures, an early-stage technology venture capital firm that invests in Europe and the Middle East. While there, Fadel led several early-stage tech investments in France, Sweden, and the U.K. She started her career as an investment banker in mergers and acquisitions at Merrill Lynch in London.

Jacques Frederic Kerrest MBA ’09, vice chair and co-founder, Okta; managing partner and founder, Windproof Partners; senior advisor to Blackstone

As Okta’s chief operating officer from 2009 to 2023, Kerrest was responsible for Okta’s day-to-day operations, drove Okta’s corporate priorities, accelerated innovation across the company, worked closely with customers, partners and prospects, and served as a key liaison with the investor community. He oversaw corporate strategy, corporate development, strategic partnerships, and Okta’s social impact arm, Okta for Good. Previously, he worked in sales and business development at Salesforce.com, and in venture capital at Hummer Winblad Venture Partners. Kerrest also served as the chair and co-founder of Herophilus, a neurotherapeutics drug development company acquired by Genentech Roche. He is the author of “Zero to IPO,” a guidebook to building startups.

Michelle K. Lee ’88, SM ’89, CEO and founder, Obsidian Strategies, Inc.

Prior to founding Obsidian Strategies, Lee was vice president of the Machine Learning Solutions Lab at Amazon Web Services. She also served as the U.S. under secretary of commerce for intellectual property and director of the U.S. Patent and Trademark Office from 2015 to 2017 and was the first woman to serve in this role in the country’s history. Before entering public service, she served as an executive for eight years at Google. Lee also held the appointment of the Herman Phleger Visiting Professor of Law at Stanford University from 2017 to 2018. She began her career as a computer scientist at the MIT Artificial Intelligence Laboratory and Hewlett-Packard Research Laboratories.

Bianca Lepe PhD ’24, data scientist, City of Boston

Lepe’s PhD research focused on computationally guided vaccine design for tuberculosis and the development of a surface functionalization platform for M. tuberculosis to study host-pathogen interactions. As a Graduate Student Union member and REFS conflict coach, she supported fellow researchers, helped resolve conflicts, and represented student concerns. She also served as a student leader on the Graduate Student Council and the Corporation Joint Advisory Committee, where she facilitated dialogue on critical issues and advocated for people-centered solutions. Lepe has professional experience in technology policy consulting, venture capital, and biotech strategy. She recently joined the City of Boston’s analytics team as a data scientist, where she collaborates on projects to improve the city’s decision-making and operations.

Natalie M. Lorenz Anderson ’84, chief operations officer and board director, 247Solar, Inc.

Before joining 247Solar, an MIT startup commercializing a modular, scalable thermal energy solution, Lorenz Anderson was a partner at Booz Allen Hamilton, where she was a senior vice president and subject matter expert in cybersecurity, privacy, risk management, IT, and advanced technologies in the defense, national security, and civilian agency domains. She has served on several advisory and corporate boards with MIT roots, including Gigavation, Embr Labs, and Lutron, and is a former board member and current advisory board member for Ocean Power Technologies. Lorenz Anderson has also been a limited partner of Safar Partners LLC and is a former board director and vice president of the Girl Scouts Nations Capital Board.

Sebastian S. Man ’79, SM ’80, chair and chief executive officer, Chung Mei International Holdings Limited

Since 1990, Sebastian S. Man has helmed Chung Mei International Holdings Limited, which was co-founded in 1963 by his family and is a leading manufacturer of domestic kitchen electrics and air treatment products for major international brands. He is affiliated with several trade organizations, including as honorary vice president of the Hong Kong Electrical Appliance Manufacturers Association and a board director of the Pacific Basin Economic Council. He is also a council member with the Better Hong Kong Foundation and a member of the Vision 2047 Foundation. Man has been an executive committee member of the International Chamber of Commerce and the Hong Kong China Business Council. He is also an executive committee member of the Young Presidents’ Organization Gold HK and the North Asia Chair of the Chief Executive Organization.

Hyun-A C. Park ’83, MCP ’85, president, Spy Pond Partners, LLC

Park started her career working for MIT professor Tunney Lee at the Massachusetts Division of Capital Planning and Operations, and then worked on the Central Artery (“Big Dig”) project. From there, she went to Cambridge Systematics, where she was in charge of a business line focused on transportation asset management. Park recently chaired the Technical Activities Council of the Transportation Research Board, where she led a group of chairs that oversaw more than 200 committees and 6,000 volunteers on research activities related to all modes of transportation and a wide range of transportation topics. She also served as co-chair of the Women’s Transportation Seminar’s Public Art Project that resulted in the installation of a new public art piece at Boston’s South Station.  

Thomas Tull, co-chair, TWG Global

In addition to his role at TWG Global, Tull founded and chairs the United States Innovative Technology Fund, and is the founder, chair, and CEO of the private holding company Tulco, LLC. Previously, he founded and served as CEO of the media company Legendary Entertainment, which produced films like “The Dark Knight” trilogy, “Inception,” and “Jurassic World.” Tull is part of the ownership groups of the Pittsburgh Steelers and the New York Yankees, and he is deeply committed to philanthropy and advancing innovative solutions to global challenges through the Tull Family Foundation. He serves as an advisor to the chief innovation and strategy officer at MIT, is a member of the MIT School of Engineering Dean’s Advisory Council, and recently served as a Visiting Innovation Scholar at MIT.

The three new life members are:

Orit Gadiesh, partner and chair emeritus, Bain and Company Inc.

Gadiesh joined Bain and Company in 1977 and served as chair from 1993 to 2025. She is currently based at the group’s London headquarters and remains active in client and advisory work in North America, Europe, and Asia. She has counseled top-level management in structuring and managing portfolios, developing and implementing global strategy, designing both cost reduction and growth programs, embedding technologies in organizations, and more. Gadiesh currently serves on the World Economic Forum board of trustees, the International Business Leaders Advisory Council to the Mayor of Shanghai, and the board of governors at Tel Aviv University, as well as on the advisory boards of the James Martin 21st Century School of Oxford University and the Peres Institute for Peace and Innovation.

Jeff Halis ’76, SM ’76, president and CEO, Tyndall Management, LLC

Halis founded Tyndall Management, an investment firm specializing in publicly traded securities, in 1991. Prior to that, he held positions in the finance and investment industry working for Citibank, Merrill Lynch, and Sabre Associates. He is a former director of several publicly traded companies, including Enstar USA, Inc., KinderCare Learning Centers, and PriceSmart. His civic involvement included his membership on the state of New York’s financial control board, the investment committee of the New York State Common Retirement Fund, and the Citizen’s Budget Commission. He has also been on the boards of WNET, CaringKind, and Bridge Over Troubled Waters.

Alan Leventhal, former U.S. ambassador to the Kingdom of Denmark

3 Questions: Hank Green on science, communication, and curiosity

“There’s no better use of a day than learning something new,” Green reflected before delivering MIT’s 2025 Commencement address.

Hank Green, prolific content creator and YouTuber whose work has often focused on science and STEM-oriented topics, is delivering today’s OneMIT Commencement address. Green, along with his brother John, has built the educational media company Complexly, racking up over 2 billion views for the their content, including the channels SciShow and CrashCourse. MIT News talked with Green in advance of his commencement remarks.

Q: MIT’s president, Sally Kornbluth, often talks about the value of curiosity. How much of curiosity do you think is natural, or alternately, how do you keep cultivating your sense of curiosity?

A: There’s a line in my talk today, something like, if I could attribute my success to anything besides luck, it is always believing that there is no better use of a day than learning something new. And I don’t know where that came from. I feel like everybody is like that. I have an 8-year-old son and he’s like that. My wife texted me last night and said, “He wants to know what dark matter is.” Well, wouldn’t we all?

I don’t know exactly know how to cultivate that, but I do have strategies for orienting [toward] that. … The reality is that it’s very easy to orient my curiosity toward what would make me the most money or what makes me feel better than other people. I’m very aware of this as founder and host of SciShow, that people might watch because they want to feel superior to people who don’t know stuff. And that’s a motivation, and at least it’s oriented toward knowing more stuff, but it’s not the best motivation. I think one of the great powers people can have is being able to orient your curiosity around what your values are, and how you’d like to see the world change. And that’s something that I have worked a lot on.

Q: It seems like you’re not just learning about new things, but also, in the process, aren’t there a lot of new challenges in figuring out how to communicate things best?

A: Tons! I mean the thing about it is that the communications landscape changes very fast. Five years ago, TikTok wasn’t really a thing. When I heard about it, I thought, “You can’t do science communication in a minute. That’s impossible. All you can do is dance videos.” And then I saw people doing it and said, “Well, you can.”

I’m also working on a book-length science communication project right now. When I say book-length, it’s a book about the biology of cancer. And that process, it doesn’t end there, but for me that’s the largest, longest communication you can do.

[But alternately] my friend Charlie made one of the first science TikToks I saw. It’s a skit about how vaccines work, where one character was a vaccine and one was an immune cell. That was probably 30 seconds long and it’s probably better than any way I would have communicated about vaccines in the midst of the Covid epidemic on the new platform, pre-bunking fear about vaccines from the very beginning, very simply explaining what they are in a way that’s very accessible and not going to turn anybody off.

Q: What are you talking about in your remarks today?

A: Yeah, I mean we are in a super-weird moment with regard to the amount of power humanity has. We’ve been in moments like this before, where the amount of power at our fingertips increases exponentially very quickly. The nuclear age is the big one in terms of the speed of that change. But it feels like biotechnology and AI and communications are all adding up to being a really big deal.

The thing I kept coming back to was — I didn’t put this in the talk, but it inspired the talk: Okay, so we had a period of time where humans powered the world through muscle. And now human muscle is not the [most] important part of how we build. Intelligence and dexterity are important, but in terms of calories expended, [that’s done] by machines. If we end up in a world where that [also] becomes more the case for intelligence, what do we still have a monopoly on? A lot of people would still answer that question with “Nothing,” I guess.

I think that’s really wrong. I think we’ll still have a near-monopoly on meaning, and what we mean to each other. So, what I wanted to get at is, all the stuff that we do, all the things that we build, at the root, the base, we do it for people in some way. It might be a playlist for your friend, or the Human Genome Project, but all of that, we’re doing for people. And so keeping [ourselves] oriented toward people, and not building around them as an obstacle but building for them, is the thing I’ve wanted to be focused on.