Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity. 

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

The material’s unique magnetic properties also allow for transistors with built-in memory, which would simplify circuit design and unlock new applications for high-performance electronics.

“People have known about magnets for thousands of years, but there are very limited ways to incorporate magnetism into electronics. We have shown a new way to efficiently utilize magnetism that opens up a lot of possibilities for future applications and research,” says Chung-Tao Chou, an MIT graduate student in the departments of Electrical Engineering and Computer Science (EECS) and Physics, and co-lead author of a paper on this advance.

Chou is joined on the paper by co-lead author Eugene Park, a graduate student in the Department of Materials Science and Engineering (DMSE); Julian Klein, a DMSE research scientist; Josep Ingla-Aynes, a postdoc in the MIT Plasma Science and Fusion Center; Jagadeesh S. Moodera, a senior research scientist in the Department of Physics; and senior authors Frances Ross, TDK Professor in DMSE; and Luqiao Liu, an associate professor in EECS, and a member of the Research Laboratory of Electronics; as well as others at the University of Chemistry and Technology in Prague. The paper appears today in Physical Review Letters.

Overcoming the limits

In an electronic device, silicon semiconductor transistors act like tiny light switches that turn a circuit on and off, or amplify weak signals in a communication system. They do this using a small input voltage.

But a fundamental physical limit of silicon semiconductors prevents a transistor from operating below a certain voltage, which hinders its energy efficiency.

To make more efficient electronics, researchers have spent decades working toward magnetic transistors that utilize electron spin to control the flow of electricity. Electron spin is a fundamental property that enables electrons to behave like tiny magnets.

So far, scientists have mostly been limited to using certain magnetic materials. These lack the favorable electronic properties of semiconductors, constraining device performance.

“In this work, we combine magnetism and semiconductor physics to realize useful spintronic devices,” Liu says.

The researchers replace the silicon in the surface layer of a transistor with chromium sulfur bromide, a two-dimensional material that acts as a magnetic semiconductor.

Due to the material’s structure, researchers can switch between two magnetic states very cleanly. This makes it ideal for use in a transistor that smoothly switches between “on” and “off.”

“One of the biggest challenges we faced was finding the right material. We tried many other materials that didn’t work,” Chou says.

They discovered that changing these magnetic states modifies the material’s electronic properties, enabling low-energy operation. And unlike many other 2D materials, chromium sulfur bromide remains stable in air.

To make a transistor, the researchers pattern electrodes onto a silicon substrate, then carefully align and transfer the 2D material on top. They use tape to pick up a tiny piece of material, only a few tens of nanometers thick, and place it onto the substrate.

“A lot of researchers will use solvents or glue to do the transfer, but transistors require a very clean surface. We eliminate all those risks by simplifying this step,” Chou says.

Leveraging magnetism

This lack of contamination enables their device to outperform existing magnetic transistors. Most others can only create a weak magnetic effect, changing the flow of current by a few percent or less. Their new transistor can switch or amplify the electric current by a factor of 10.

They use an external magnetic field to change the magnetic state of the material, switching the transistor using significantly less energy than would usually be required.

The material also allows them to control the magnetic states with electric current. This is important because engineers cannot apply magnetic fields to individual transistors in an electronic device. They need to control each one electrically.

The material’s magnetic properties could also enable transistors with built-in memory, simplifying the design of logic or memory circuits.

A typical memory device has a magnetic cell to store information and a transistor to read it out. Their method can combine both into one magnetic transistor.

“Now, not only are transistors turning on and off, they are also remembering information. And because we can switch the transistor with greater magnitude, the signal is much stronger so we can read out the information faster, and in a much more reliable way,” Liu says.

Building on this demonstration, the researchers plan to further study the use of electrical current to control the device. They are also working to make their method scalable so they can fabricate arrays of transistors.

This research was supported, in part, by the Semiconductor Research Corporation, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), the U.S. Department of Energy, the U.S. Army Research Office, and the Czech Ministry of Education, Youth, and Sports. The work was partially carried out at the MIT.nano facilities.

There are few treatment options available for people with disorders of the esophagus. Delivering drugs directly to this part of the body is difficult, so patients are usually treated with systemic drugs, which can have unwanted side effects.

To overcome that challenge, MIT engineers developed a gel-like oral drug formulation that can coat the mucosal lining of the esophagus after being swallowed, allowing drugs to pass through the tissue.

The formulation, which includes a hydrogel and other key ingredients that promote rapid drug absorption, could be used to deliver antibodies including infliximab, used to treat a number of autoimmune diseases, or other types of antibodies or small-molecule drugs.

“There are many people with esophageal disease, and if you look at drugs for these conditions, they’re very limited in their ability to target this part of the body and it’s very difficult to develop them. We hope this platform will make it easier to develop systems that can help patients suffering from these conditions,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, and an associate member of the Broad Institute of MIT and Harvard.

Traverso is the senior author of the new study, which appears today in Nature Biomedical Engineering. Former MIT postdoc Christina Karavasili, now an assistant professor at Aristotle University of Thessaloniki in Greece, is the paper’s lead author.

Direct delivery

One of the most common disorders of the esophagus is eosinophilic esophagitis, a type of inflammation that is caused by food allergies and leads the esophagus to close up, making it impossible to swallow food. Crohn’s disease can also cause inflammation of the esophagus. 

These disorders are usually treated with systemic drugs, including infliximab, an antibody that neutralizes an inflammatory protein called tumor necrosis factor alpha (TNF-alpha). However, this drug is an immunosuppressant that can lead to a higher risk for infections and other health problems.

Delivering the drug directly to the esophageal tissue could reduce those side effects, but this is inherently challenging because drugs taken orally pass through the esophagus so quickly. Adding to the difficulty, the esophagus is lined by a layer of tissue called stratified squamous epithelium, which is very impermeable to drugs.

Injecting drugs into the esophageal tissue is another option, but that is uncomfortable for patients and inconvenient because it has to be done at a doctor’s office. There is also at least one anti-inflammatory steroid drug that is formulated as a thick mixture, allowing it to remain in the esophagus longer after being swallowed, but the drug still has some difficulty passing through the impermeable squamous layer.

In this study, the researchers set out to develop new drug formulations that would include molecules that could increase the permeability of those esophageal cells, allowing more of the drug to pass through. 

To identify molecules that would enhance permeability, the researchers designed a screening system that mimics the structure of the esophagus. This system contains esophageal tissue pressed between two vertical plates. Drug formulations can be poured into the top of the system, simulating oral ingestion. The researchers can then measure how much of the drug passes through the tissue and is collected by wells in one of the plates.

Using this system, the researchers were able to measure how different excipients — inactive ingredients that help enhance drug effects — affect the permeability of the esophageal tissue. First, they tested about 100 different compounds and identified several top candidates. Then, they tested pairs of these excipients and found that the most effective combination was a pair of bile salts called sodium chenodeoxycholate and sodium cholate.

These salts appear to work together to loosen up the cell-cell junctions that normally act as a barrier to drug molecule entry. The researchers added those bile salts to a polysaccharide-derived hydrogel, which has a viscous consistency that allows it to lightly coat the lining of the esophagus.

“The hydrogel helps the formulation remain on the esophageal surface for longer, while the bile salts help increase transport across the tissue,” Karavasili says. “Our data suggest that the bile salts temporarily loosen these cell–cell junctions, mainly by interacting with calcium ions that help maintain junction integrity. This creates a more permissive pathway between the cells, allowing larger molecules to move into the mucosal tissue more efficiently.”

Minimizing side effects

In tests in animals, the researchers showed that this formulation could be used to effectively deliver infliximab to the esophagus. They also found that the loosening of the cell-cell junctions was temporary, and the cells returned to normal within three days.

This kind of delivery could help to avoid the side effects that patients sometimes experience when infliximab is given systemically, the researchers say. 

“We were interested in delivering anti-TNFs as a model drug, but also to help people who suffer from conditions like Crohn’s disease to have options that could be delivered to the site,” Traverso says. “If we have the possibility of site-directed delivery, we may be able to mitigate systemic side effects from these immunosuppressing agents.”

The researchers are now working on further optimizing the formulation for potential testing in humans. One key goal is to ensure that the gel adheres for long enough to deliver the drugs, but not so long as to cause discomfort for patients. The researchers are also exploring the possibility of using this approach to deliver other types of drugs. 

“This is a platform to enable the development of drug-delivery systems for the esophagus, which hasn’t been possible before because the tools haven’t existed,” Traverso says.

The research was funded by the Karl van Tassel Career Development Professorship, the Department of Mechanical Engineering at MIT, the Division of Gastroenterology at Brigham and Women’s Hospital, and the U.S. Advanced Research Projects Agency for Health (ARPA-H), which notes that the views and conclusions contained in this article are those of the authors and should not be interpreted as representing the official policies of the United States government.

Debates about vaccines are a recurring feature of contemporary politics. It turns out they actually date back more than 200 years, since the development of the first smallpox vaccine. MIT Professor Thomas Levenson, one of the country’s leading science writers, explores this important history in a new book about the contours of anti-vaccination thought. Levenson identifies different types of arguments vaccination opponents have developed through history, to help shed light on our current debates. He spoke with MIT News about his new book, “A Pox on Fools: The True Believers, Grifters, and Cynics Who Convinced Us to Reject Vaccines,” published this week by Penguin Random House. 

Q: Your book is about the longer history of anti-vaccination arguments. How far back does this go, and what have those arguments been? 

A: Hesitation, skepticism, and outright opposition to vaccines is not a new thing. It didn’t just happen starting in the late 1990s. Opposition to vaccines dates back to the beginning of the vaccine era, around the early 19th century. The first kind of opposition to vaccines is this sense that it violates the moral or the natural order. If you believed that God has authority over all of us and is mindful of everything, intervening in the disease process could seem blasphemous. 

In the early 19th century, the first true vaccine, the smallpox vaccine, used material from a related disease, cowpox, that doesn’t cause human beings to fall ill but does provide immunity to smallpox. That shifted the initial focus on God’s plans to the notion that vaccination — sticking some cow-stuff into people — violated the natural order. That sort of uneasiness is easily co-opted by a broader philosophy that says: If you align yourself with nature, you don’t need to use vaccines. 

I want to emphasize that in the early history of the anti-vaccine movement, there were reasonable fears being expressed. That changes over time, because science advances and the mystery of vaccines falls away. Still, the current anti-vaccine movement includes an impulse we all have: We wish to be in control. I would never deny the value of exercise, sunlight, and sanitation, but they are not sufficient when you are faced with many pathogens, and that’s what the modern anti-vaccine movement obscures. We share this world with bacteria and viruses that do their thing no matter what we eat or how much we exercise. 

Q: One section of your book explores the argument that vaccines have been actively harmful. What is that historical trajectory like? 

A: The idea that vaccines are not just unnecessary but actively bad for you is certainly very contemporary, but it too goes back to the beginning of the vaccine era. The first true smallpox vaccine came into public use in 1798. Very soon afterward people started pointing to different harms. Most of them were spurious. They were just making things up or mistaking another infection that was already there. But there were some flaws in the early forms of vaccination. People thought it conferred life-long immunity, and that wasn’t always the case. Additionally, people mistook syphilis infections for cowpox infections and transmitted syphilis to healthy people. There were maybe 750 cases in Europe.

What is repeated over and over in the history of vaccination is that when problems became apparent, people found a way to address them. A problem with diphtheria antitoxin at the turn of the century led directly to the first U.S. regulatory body, the Division of Biological Controls. And when the first polio vaccine was released to the public in 1955, one of the five drug companies making it had shoddy production practices. Thousands got sick, a hundred died, and some were paralyzed. The flawed vaccine was identified after two weeks on sale and stopped cold, and that ended that particular problem. What came out of it was the development of an FDA vaccine division with teeth. 

This is an area where the rhetorical skill of the anti-vaccine movement is on display. Anything human beings do carries some risk. Anything you do medically. I had my hip replaced last year. That carries some risk, such as surgical site infections. Well, the risks of vaccines are incredibly small. The most common response is a sore arm the next day, and maybe feeling under the weather. There is extremely close control over manufacturing now. We have stories of great harm, but the various specific allegations of the last 30 or 35 years have proven to be incorrect. But there’s a power to an anecdote versus statistics. 

Q: This book raises an issue also explored in your last one, “So Very Small,” that the sheer success of vaccines has, paradoxically, created a situation in which people take their effects for granted and find it easier to argue against them. Can you explain this phenomenon?

A: The reason that occurs is because vaccines have worked so brilliantly well. At the turn of the century, life expectancy was much lower, 47 years in the U.S. Several top causes of death were infectious diseases, and child mortality was high. Now, life expectancy is around 80 years in every developed nation, and child mortality is a tiny fraction of 1 percent. By 1970, you had almost a complete set of vaccines against what used to be called childhood diseases. And those diseases, up until extremely recently, had essentially disappeared. And that’s amazing. 

In the 1950s, before the measles vaccine, for instance, everybody had an experience of what it meant to be at at the mercy of waves of infection. But by the 1970s, that was no longer the expected, ordinary, common experience of raising kids. So we’ve forgotten how unpleasant even an ordinary case of one of these diseases is that you recover from, much less the more severe problems and death. In 1952, there was the largest polio outbreak in U.S. history, and it was scary to let your kid go to the movies or a swimming pool. They could go to someone’s birthday party, come back, and two weeks later start feeling muscle aches and a fever, and two weeks after that were maybe paralyzed, or dead. Then in 1955 the Salk polio vaccine came out. We don’t live that way any more. 

And so, because infectious disease seems like a nonexistent threat, vaccines, even with a tiny potential of harm, are made to seem worse because we don’t realize what happens if we let our vaccine coverage lapse. Well, we’re starting to get a glimpse of it, because the measles rate in the U.S. is shooting up, and we see what happens when vaccine coverage wanes, and in particular, when we lose herd immunity. In every population, some people cannot be vaccinated: infants who are too young, some people who have had transplants and are on immunosuppressive drugs, or the elderly in whom sometimes immunity wanes. Some diseases are so infectious, and measles is famous for this, that about 95 percent of a population must be vaccinated or the disease spreads. If we’re not at that threshold, every newborn is at risk. 

We don’t know what it’s like to live with the genuine risk and fear of those diseases. If you were born in 1970, you’re 56 now, and you literally never lived in a world where these diseases were common. 

Q: One source of resistance to vaccines is not strictly medical, but political and philosophical at one level. This also has a lengthy history, it seems. 

A: Another major theme of the anti-vaccination movement is to argue the question: Who has the right to say that somebody else must put something in their body? Again, all this is not new: In the mid-19th century, in the United Kingdom, there was a requirement that children be vaccinated against smallpox, and these mandates brought immediate opposition as an infringement of liberty. 

In 1850 the country’s top doctor, John Simon, physician to the privy council in England, described the right that people claim against vaccination as the liberty of “omissional infanticide,” that you are killing kids by not protecting them. Where do I stand? This is a philosophical question. Does the state have the right to make me do something because it will make society as a whole safer? I think, “Yes.” We live in societies, we depend on each other for all kinds of things, we aren’t just atomized individuals. But I can understand those who say, “No.” I just think it’s wrong. But it’s an argument that’s winning in some places. What I realized as I worked on this book is that the argument against vaccination on philosophical grounds is a lonely view: I owe nothing to anyone, and nothing owes anything to me. I think it’s a fearful one, too.

Q: For the vaccine hesitant, for those questioning vaccines, what will they get out of this book? 

A: On social media you see some people calling vaccine-hesitant people stupid, but that’s not right. People are busy. We all have daily lives. Get the kids ready for school, pack their lunches, go to work, get home, fix dinner. All of us offload some decisions to people we trust as experts. I have a ton of sympathy and empathy both for people trying to think how to make it through an incredibly complicated world. They hear noise about how vaccines are problematic and there’s no easy way for them to get to the bottom of the issue. That’s an opening the anti-vaccine movement exploits.

I hope my book reaches people who are vaccine hesitant. It’s understandable that people might think that where there’s smoke, there’s fire. But when you get down to the bottom question: Do vaccines help human flourishing, do they support the ability of human beings to live healthy, fulfilled lives? Yes, they do. Unequivocally, they are the greatest lifesaving invention humankind has ever come up with.

Jinhua Zhao MCP ’04, SM ’04, PhD ’09 has been appointed head of the Department of Urban Studies and Planning (DUSP), effective July 1. Zhao is the Class of 1941 Professor of Cities and Transportation at MIT.

In making the announcement, dean of the MIT School of Architecture and Planning Hashim Sarkis noted that Zhao is a renowned transportation planner, educator, and scholar, and a world leader in imagining and shaping better futures for mobility.

“Jinhua is one of those rare scholars who moves seamlessly between cutting-edge research and real-world policy,” says Sarkis. “His work with governments and transportation agencies around the world is a model for what MIT’s impact can look like beyond our campus.” 

Zhao succeeds Professor Christopher Zegras, who has served as department head since 2020. Under his leadership, DUSP expanded opportunities for students to engage directly with communities and policymakers around the world and continued to strengthen its long-standing connection between research and practice. “I want to extend my gratitude to Chris Zegras for his excellent and level-headed leadership, especially in challenging times,” says Sarkis.

After earning advanced degrees at MIT, Zhao joined the DUSP faculty. He says he found the Institute’s lack of conventionality and its culture of sharing ideas across disciplines stimulating. 

“MIT is a small school in the best sense of the word,” says Zhao. “We have fewer boundaries than other universities — intellectually and physically. Our ‘infinite corridor’ literally connects us to so many disciplines.”  

Shaping mobility systems worldwide 

That connectivity has been key for Zhao’s research and programs he has founded at MIT. Respected as a global authority on mobility, his research has been put into practice across some of the world's most complex mobility challenges. He and his team have shaped policy for Transport for London, the Mass Transit Railway in Hong Kong, and Japan Railways. His research has positively impacted leading U.S. transit authorities including Boston’s MBTA, the Chicago Transit Authority, and Washington’s Metropolitan Area Transit Authority. He has guided strategic planning for mobility industry on the future of autonomous and digital mobility, and developed autonomous vehicle (AV) deployment strategy in Singapore and the Middle East.

“Every city I’ve worked with faces the same tension: The technology is moving faster than the institutions designed to govern it,” says Zhao. “My work has been about closing that gap.”

At MIT, Zhao founded the MIT Mobility Initiative, which engages mobility and transportation researchers across the Institute as well as leaders in these disciplines from around the world. Zhao hosts the weekly MIT Mobility Forum via Zoom, with each discussion open to the public. What began as a small internal list of participants has grown into a global platform, drawing more than 200 practitioners, policymakers, and researchers every week around the world. The sizeable interest in the subject doesn’t surprise Zhao.

“No single discipline owns transportation,” says Zhao. “AI and autonomous systems are reshaping urban living faster than most institutions can adapt. The question is no longer what we know. It is whether the people who need it most — municipal governments, transport agencies, federal ministries — can access it when they make decisions on transportation. This is why the forum exists.”

Zhao directs the JTL Urban Mobility Lab that unites behavioral science and transportation technology to shape travel behavior, design mobility systems, and improve transportation policies. He is also a lead principal investigator with Mens, Manus, and Machina, an MIT initiative at the intersection of artificial intelligence, the future of work, and human learning, developing the tools and strategies for how cities, institutions, and economies can be designed to ensure AI augments, rather than displaces, the people within them.

DUSP’s global agenda

“If you look at the global agenda, what are the issues people are facing?” asks Zhao. “An aging society; AI and its impact on jobs; the energy crisis; traffic congestion. These are just some of the problems people feel connected to because they are embodied in our cities and communities. I want DUSP to engage with the city leaders and share our research and insights.” 

As he prepares to step into his role as department head, Zhao says he would like the research generated within DUSP to more quickly reach those who need it most: the planners, officials, and engineers making decisions in cities right now. A transit authority grappling with AV integration; a city government rethinking aging infrastructure; a leading transport ministry navigating the policy implications of AI — these are the constituencies Zhao believes DUSP should be in active conversation with.

“We know a great deal about how cities grow, how people move, and how that will change. The question is whether the people responsible for making these changes — in city halls, transport agencies, federal ministries — can access what we know, when they need it.”

Last fall, MIT Campus Dining recruited a group of students to make short videos and share their experiences as student diners on Instagram. The MIT Dining Ambassadors program is an effort to get students talking about — and helping to improve — MIT’s food services and systems. 

One of the inaugural ambassadors, Michaela Brown, a biochemical engineering major from Kingston, Jamaica, sat down to discuss what she’s learning as an ambassador, how she has adapted to dining-hall life, the best things about her mom’s cooking, what it was like to experience American Thanksgiving for the first time, and more.

Q: How did you get involved in the Dining Ambassadors program? 

A: Last October, my friend got a job. So I was like, I need to get a job. When I read the description, I said, Wait, this involves food, and talking to people, and posting on Instagram? That’s literally what I do every day. And I wanted to do my part. 

The ambassadors program has clear goals: They want to encourage students to use the dining halls, and they want us to find genuine issues MIT can work on. I wanted to be a part of that. The food at MIT is OK, but everything can be better. And you can’t make things better in any circumstance without trying. Plus — getting paid to eat food and talk? That is good money.

Q: What did you eat growing up? 

A: I love Jamaican food. On Sunday, we do a big dinner. (Well, my mom would do a big dinner; sometimes I would wash the vegetables.) She would cook rice, peas, and vegetables with a sauce, and either fried chicken with sauce or stewed chicken. We would eat that food on Sunday, and then maybe Monday, too. We call it “Sunday-Monday” in Jamaica. 

During the week, we eat flour dumplings, boiled green bananas, and lots of plantains. Sometimes, when my mom is on a health kick, she will boil everything, but plantains are so much better when you fry them! Often, she will serve that with ackee. That’s our national food. And she will cook saltfish or mackerel mixed with coconut milk. She also makes things like corned beef or tuna. On Fridays, we usually go out. 

For special occasions, sometimes we do pork or oxtail. Or sometimes we have escovitch fish; I think you fry it and you steam it. And then we have sides like dumpling, or banana, or bami, which is fried flour. And usually we eat these with okra and pickled onions, and add a little spice with Scotch bonnet pepper. 

And curry chicken! If I am home and I smell the curry, I get so happy. I genuinely feel better about myself. If you’re buying food from a vendor, like fried chicken and rice, you would ask for curry gravy because it is very essential in Jamaican culture. 

Q: What was your first project for the ambassadors program?

A: I did a video about Thanksgiving. I was excited, because it would be my first American Thanksgiving. As a kid in Jamaica, I saw it on TV. I watched Nickelodeon. Also, we learned about it in school. But we didn’t do Thanksgiving in Jamaica. So I was excited.

In the video, I was trying to cater to students who don’t normally celebrate Thanksgiving and show them the experience from a fresh perspective. I brought my friends with me and we all ate together. And luckily everyone thought the food was good. I really wanted to show the food — the mashed potatoes, the turkey, the jelly, the ham, all those things — because I think New Vassar did it really well. I wanted to show that. 

There are a lot of international students at MIT. I didn’t know what MIT was like until I got here. I wanted to show that I came here and liked it. Even while I was missing home, I was being introduced to other cultures — like the one in America — and MIT was helping me appreciate it through food.

Also, I wanted to show the community — being with my friends, giving thanks for the people around me. I really enjoyed that, and I thought it went well. My mom loved it.

Q: What have you done since then? 

A: Usually, I just try to take pictures when I’m in a dining hall and post them on Instagram. You know — regular life.

The other major thing was the global Olympics. Each day over two weeks, they had a special theme at each of the dining halls — Latin American at New Vassar, East Asian at Simmons, African at McCormick, European at Next House, Indian at Massey, and North American and Caribbean at Baker. 

My favorite was Baker, because, well, I’m a little biased. And also, I love the burgers at Baker. 
I told my friends they had to come. A lot of the cooking staff in Baker are Haitian. They would know how food from Haiti and Jamaica should taste. I knew they wouldn’t mess it up. 

I interviewed a lot of students, including two Haitians and one of my Jamaican friends. I asked about the food, about how it compared to regular dining hall meals. They were really positive. I think they liked the change. 

Q: Do you like to cook? 

A: Not really. The summer before I came here, I was like, OK, I’m gonna learn something. 
And then I proceeded to spend the summer out with my friends, and volunteering. So I wasn’t really in the kitchen. My mom would call me to come help her, and when I stepped in the kitchen it was so hot! I was like, I can’t do this, and I went back to my room. 

So I’m not really a cook, even though I live in Burton-Connor. It’s a cook-for-yourself dorm, so it doesn’t have a dining hall. A few weeks ago, I tried to do burritos. I got the beef and the seasoning. It was actually really good! I’m looking forward to it again. It’s just really hard to find the time. 


Q: When you’re posting, who do you imagine is looking at it? 

A: My friends. And my mom. Honestly, I just try to make sure you can understand what I’m saying because sometimes my Jamaican patois comes out, and I talk too fast. I also think about how the people I’m interviewing want to be seen, because this is not their job. They don’t have to be on camera, or help me. I try to make the experience as fun as possible for them. 

Q: What have you learned doing this work?

A: Walking up to strangers and getting their permission to record them is really new to me. I have learned so much about people. The other day, I was looking at a job application and it asked: Are you comfortable talking to other people and being social? This job has prepared me for all that so well. 

It also prepared me for dealing with people who might not be open to talking. I have learned to be OK with that, just walking away and handling it well. This is a skill set that I have now, and I look forward to working more and doing more interviews. I feel like, you know, a YouTuber!

Q: What dining stories do you want to tell next? 

A: I’m not sure. Dining is different for different people. For me personally, sometimes eating is a time to get together with other people. But sometimes I go to the dining hall by myself. It’s very much a time for me to decompress. Sometimes I don’t even want anyone to sit with me. I’m just trying to be with myself, watch my show, or do the learning sequence I have due at 11 o’clock. Or I just watch my TikToks. 

Maybe I’ll do a day-in-my-life dining story next, and go for breakfast at a dining hall. I would have to wake up earlier, but I would do it. 

In his 1927 paper, “A law of comparative judgment,” the American psychologist L. L. Thurstone proposed that when people select one option among multiple alternatives, they are picking the one that has the highest value to them, even though they cannot assign a particular number to that choice. 

Thurstone was a pioneer of “psychometrics” — a field built upon the premise that mental processes, which we cannot see, can nevertheless be measured and quantified. His 1927 paper laid the groundwork for what are now called random utility models, which provide a mathematical framework for describing human preferences — information that can be relied upon, in turn, to make predictions about various hypothetical situations.

Random utility models (RUMs) are so named because they assess the “utility,” or benefit, that can be obtained from a given choice — such as deciding which book to read first among the stack of novels you brought back from the library. “These models are inherently random,” explains Gabriele Farina, an assistant professor in MIT’s Department of Electrical Engineering and Computer Science (EECS) and principal investigator at the Laboratory for Information and Decision Systems (LIDS), “because people are different. Everyone has their own preferences, and even those preferences can vary from time to time.” For example, someone who normally picks coffee over tea in the morning, and prefers tea after dinner, may, upon occasion, mix up that order entirely.

RUMs, to be sure, are frequently used within government and industry in situations of far greater consequence than the selection of a hot (or iced) beverage. The models routinely facilitate predictions regarding what people will elect to do in so-called counterfactual (“what-if”) scenarios such as: How will they get to work or school if a major thoroughfare is shut down for construction? What routes and modes of transport will they take? Or, if a city suddenly receives a windfall of $20 million, how should those funds be disbursed to maximize the common good?

Given that RUMs have been with us for almost 100 years, growing in sophistication over time, one might imagine that, at this stage, there would be little room for improvement. That, however, is not the case. 

A paper presented in April at the International Conference on Learning Representations in Rio de Janeiro, Brazil, uncovered basic facts that show there is much more to be gleaned from these models than had traditionally been supposed. The paper was authored by Yeshwanth Cherapanamjeri, a former MIT postdoc now based at Nanyang Technological University in Singapore; Farina, also core faculty in MIT’s Operations Research Center (ORC); Constantinos Daskalakis, the Avanessians Professor of Computer Science at MIT and a member of MIT's Computer Science and Artificial Intelligence Laboratory; and Sobhan Mohammadpour, an MIT PhD student in computer science based at LIDS and EECS.

The group’s findings stem, in part, from a deficiency in the way RUMs are commonly estimated in practice, which has persisted since the days of Thurstone. The data upon which the models are estimated have been largely drawn from so-called pairwise-comparisons: In a choice between items A and B — whether it pertains to movies on Netflix, competing products on Amazon.com, news stories posted on Google, and so forth — which one would you pick? One reason this approach has been so pervasive, explains Daskalakis, is that “assigning a precise numerical score, such as 4.37, to the benefit you get from a single item is very hard. Whereas comparing two things, and deciding which one you like better, is cognitively much easier to do.” But therein lies the rub, he adds. “With this way of assessing people’s preferences, looking at just two things at a time, it is impossible to find correlations between the numerous choices.”

The standard way of applying RUMs assumes that the utilities derived from A and B are independent, but they may, in fact, be linked, and that would be important to know. If someone campaigning for elective office finds out that a potential voter favors gun control, for instance, there is a reasonable chance that same person also favors government-sponsored child care. Similarly, a fan of independent movies might also be partial to foreign films, but less enthusiastic about Hollywood action blockbusters. “If a digital platform has a blind eye to the existence of such correlations, it will not be able to estimate preferences very accurately,” Daskalakis notes. “And if Netflix regularly shows you an assortment of movies you don’t care about, you might sign off and cancel your subscription.”

The MIT team proved that it is impossible to get information about correlations from two-way comparisons alone. Correlations can be discerned, however, when large numbers of people rate three alternatives in their order of preference. The same information can also be obtained from a combination of best-of-three and best-of-two choices. In practice, Mohammadpour explains, “you would get a bunch of people to rank three items. You could then utilize the method we developed for merging those individual results into one big model that can provide us with the big picture.”

Their research effort, according to Farina, is focused on the computational side of RUMs, devising algorithms that can extract preference information and figuring out how much data is needed to do so or, equivalently, how many experiments need to be run. The good news, he says, is that efficient algorithms are, indeed, possible for this purpose. The requisite number of experiments does not grow exponentially with the number of items in the catalog or database that’s under review.

“This paper provides a crucial breakthrough,” comments Emma Frejinger, a computer scientist at the University of Montreal. “It mathematically proves why traditional data collection fails and demonstrates that simply asking users for their best-of-three [choices] unlocks the ability to accurately train these powerful models. This finding provides a highly practical roadmap for collecting better data to drive more accurate optimizations.”

“Building utility models is going to remain a very active area,” Daskalakis insists. “Just as RUMs have been critical to the internet economy since the late 1990s, they are, and will remain to be, critical to the alignment of AI models going forward.” More importantly, he adds, “RUMs play a central role in the commercial viability and usefulness of large language models [LLMs].” During the training period, people are typically asked to rank the various candidate outputs of these LLMs, from which the models can gain a better sense as to the kind of text — in terms of tone, style, and content — that is preferred. 

Given that we’re constantly “besieged with a vast sea of options in so many different domains,” Daskalakis says, “you cannot possibly ask people to communicate all their personal preferences for all possible scenarios. So what you can do instead is build a model that predicts what people think about the different possible outcomes. And you have to keep improving and updating your model in an iterative process until, hopefully, you can make good predictions.”

One September day, it started to snow inside MIT’s Pierce Laboratory. 

Researchers depressurized a tank of liquid carbon dioxide (CO2), instantly freezing it and releasing solid flakes. These were blended into cement paste and pressed into discs roughly the size of a dime, each sealed with a thin layer of vegetable oil to keep water in and air out. The team trained lasers on each, observing for the first time the transient chemical reaction that might explain why CO2-injected cement paste gains its strength faster.

Injecting CO2 into cement products like concrete is one way to store it and keep it out of the atmosphere. The process has attracted commercial interest, with a growing number of companies offering CO2-injected concrete mixes. But until now, the underlying cement chemistry hadn't been directly visualized.

A new open-access paper in the Journal of the American Ceramic Society — led by Associate Professor Admir Masic and first-authored by graduate student Marcin Hajduczek, both of the MIT Concrete Sustainability Hub and MIT Department of Civil and Environmental Engineering — describes the chemical sequence that unfolds after CO2 meets fresh cement paste. Co-authors include MIT colleagues Santiago El Awad and Franz-Josef Ulm, alongside researchers from IIT Jodhpur and CarbonCure Technologies.

Previous studies had pieced together a story about CO2 injection’s chemical impacts from theory and indirect evidence; the key reactions simply moved too fast, and vanished too completely, for conventional techniques to catch them in the act. Raman confocal microscopy could — and it works on a simple principle: Illuminate a molecule with a laser, and the scattered light will reveal its identity. The light interacts with each material’s unique chemical bonds, shifting in energy to produce a distinct spectral “fingerprint.” Even the most fleeting and amorphous phases leave a readable trace.

“We’ve used Raman spectroscopy to better understand some of the most interesting materials in history, from the Dead Sea Scrolls to Ancient Roman concrete,” says Masic. “Cement paste may seem less glamorous in comparison, but pointing a laser at CO2-injected cement paste as it hardens allows us to visualize things that haven’t been seen before.”

What they saw, unfolding during 24 hours of continuous scanning, was a three-act chemical drama.

Act One: Capturing calcium

The moment that CO2 is added to the fresh cement paste, it goes to work. It dissolves into the pore solution and reacts with calcium released by the dissolving clinker, precipitating as various forms of calcium carbonate. Clinker is produced by heating limestone and aluminosilicate materials in a kiln, forming the primary ingredient ground into a fine powder to make cement. This happens within the first hour, temporarily slowing the normal hydration reaction, which requires calcium to proceed. 

In contrast, when CO2 is not present, the calcium released by the dissolving clinker remains available locally, supporting the gradual formation of the material’s binding phases as it sets.

Left without calcium, the silicates released by the clinker dissolve into the pore solution and precipitate far from their source, linking together into chains that form an interconnected silica gel network throughout the paste. This amorphous, fleeting gel sets the stage for what follows.

Act Two: The ghostly gel

Once the injected CO2 is fully mineralized — around four to five hours after mixing — normal hydration resumes. Calcium hydroxide begins to precipitate into the pore space, and when it does, it encounters the silica gel network waiting for it.

The reaction between the two phases begins immediately, producing calcium silicate hydrate (C-S-H), the compound that gives cement its binding ability. What makes this form of C-S-H distinct is where and how it forms: not clustered around clinker particles as in conventional hydration, but distributed throughout the entire matrix, wherever the silica gel had spread.

The CO2 had temporarily suppressed the paste’s alkalinity, and that lower pH was the only thing keeping the silica-gel intact. As hydration reasserts itself and produces standard hydration products, namely C-S-H and calcium hydroxide, the latter drives pH back up to typical levels in a self-reinforcing loop; the silica-gel reacts with calcium hydroxide through a so-called pozzolanic reaction. Within eight hours, the silica gel is almost entirely gone — the previously well-distributed gel network turns rapidly into additional C-S-H during this critical early window. 

“At first, the fleeting nature of the silica gel looked like a fluke in the Raman data. But it quickly became clear that its sudden disappearance was a consistent, undeniable feature of every CO2-injected sample,” says Hajduczek.

Act Three: A rewired matrix

With the silica gel consumed, the paste settles into conventional hydration, but what it leaves behind is measurably different. Because the new binder was distributed more evenly throughout the cement matrix, the resulting microstructure is stronger and more uniform at an early age. In the study, paste mixed with CO2 at 1 percent by cement weight achieved, on average, 13 percent higher compressive strength at 24 hours, compared to reference mixes.

“We’ve been injecting CO2 into cement products for years without fully understanding what it was doing inside. Now that we can see it and understand the underlying mechanism that leads to improved performance, we can start to control it. And there’s a lot of room to push,” says Masic.

The findings also refine a leading explanation for CO2-injected cement paste’s higher early age strength: the calcium carbonate crystals, previously suspected to seed C-S-H growth, turn out to be passive bystanders embedded in the silica gel template rather than reacting to form C-S-H. 

Where the chemistry goes next

Knowing the mechanism gives researchers a more specific set of questions to pursue. The silica gel template explains the distribution of the new C-S-H, but directly measuring its mechanical properties remains a next step.

On the practical side, dosage matters: Flood the system with too much CO2 and calcium gets locked into carbonate before the gel can form and react. If the paste used here forms abundant C-S-H, it could theoretically offset up to 40 percent of the carbon emissions from cement production, excluding emissions associated with the fossil fuels used in the process. In practice, however, the achievable offset is likely to be only a fraction of that value, although still potentially significant.

But even with these open questions, the ghostly gel has been caught. And now that researchers know what to look for, the chemistry that unfolds in those first eight hours is no longer invisible.

When a friend buys you a cup of coffee, it’s likely that next time, you’ll return the gesture. This type of reciprocal generosity has been well-documented in behavioral economic studies.

However, anthropologists and other social scientists have known for decades that in the context of relationships where one person has more power, status, or influence, reciprocal generosity is usually not the norm. 

Researchers at MIT have now experimentally demonstrated, for the first time, that small changes to the relationship context can dramatically change people’s actions and expectations of reciprocal generosity. 

During interactions between people of different social status, people tend to expect that generosity will flow one way, and it can be either up or down. It may be that a professor always buys coffee for her students, or that a student always offers to help carry groceries for his resident advisor. Once the precedent is established, it is expected to continue.

One interpretation of the findings is that keeping track of whose turn it is to do a favor is the exception in social interactions, not the rule. That is, it is extra work that we do when we want to maintain equal relationships.

“In many intimate relationships, hierarchical relationships, or other kinds of role-based relationships, you don’t put in the work of trying to keep track of turns,” says Rebecca Saxe, the John W. Jarve Professor of Brain and Cognitive Sciences, a member of the McGovern Institute for Brain Research, and associate dean of science at MIT. “Under this interpretation, we just follow precedent because following a precedent is easier. We all know what to expect, and we don’t have to keep track of what happened last time.”

Saxe is the senior author of the study, which appears in the journal Open Mind. MIT graduate student Alicia Chen is the paper’s lead author.

Changing expectations

Most experimental studies of generosity have been done in the context of behavioral economics and game theory. In such experiments, people are usually paired with a stranger and asked to play games that require coordination. Such studies have found that people tend to use turn-taking and reciprocity as their default strategies. These scenarios, however, are stripped from any social context that might exist between people in the real world.

Saxe and Chen wanted to see if they could measure the effects of social context by incorporating relationships into the type of experiments used to evaluate people’s expectations regarding generosity.

“Where generosity becomes hard and complicated is when it starts to occur in the context of existing relationships, because it changes the terms of the relationships,” Saxe says. “What’s expected of you is very different within a relationship than outside of one.”

To study these effects, the researchers designed experiments in which participants read stories about different types of interactions. In some of the scenarios, the subjects of the stories were described as having either symmetric or asymmetric relationships. In others, they were given specific social relationships such as aunt-niece or manager-employee.

Each story described interactions that might be seen in typical daily life, such as buying coffee for a co-worker or preparing a meal for one’s family. Participants were then asked to predict what would happen the next time the interaction occurred.

In all of these scenarios, the researchers found that people expected that generous acts would be reciprocated when they occurred between individuals in symmetric relationships such as friends, cousins, or co-workers of equal rank. However, their expectations changed for asymmetric relationships, where each person has a different social status. In those cases, people expected that any precedent that was set would continue in the future.

One possible explanation for this is that reciprocity is not the norm but an exception that only occurs in the interactions between equals or strangers, the researchers say. Many of our interactions are with people with whom we have asymmetric relationship, and to maintain those relationships, it’s simply easier to follow precedent.

“If there’s no need to keep track of our equal status, then in some ways it’s the default to fall back on following precedents,” Saxe says.

Maintaining relationships

The study showed that in asymmetric relationships, generosity could flow in either direction. Once that direction was established, it was expected to continue. For example, after an older brother bought concert tickets for a much younger brother, the study participants expected that the older brother would also buy the tickets for the next concert. 

“We found that when people know the relationship is asymmetric, they don’t expect reciprocity; they expect the same action to keep on going,” Chen says. “If the lower-rank person acts generously, people expect that to continue, and if the higher-rank person acts generously, people expect that to continue.”

Following precedents is not only easier, but keeping up these actions may help solidify and define existing relationships. For example, anthropologists have long known that gift-giving helps to construct and maintain social relationships. 

“Following a precedent can be a way of actively maintaining relationships and hierarchies, when the asymmetry of the exchange truly reflects the asymmetry of the relationship,” Saxe says. 

The researchers are now working on creating computational models that could be used to analyze different factors that people take into account when they’re considering whether someone might reciprocate a generous act. In addition to the factors examined in this study, others could include how much each person will benefit, what type of relationship they’re in, and culturally specific expectations of how people should act in different situations.

“One really powerful thing about these models is that we can build in existing theories, add things to the models, and then compare how much these extra factors, like considerations related to social relationships, matter in terms of explaining what people are doing,” Chen says. “This allows us to quantitatively compare the different theories to each other.”

The research was funded by the Simons Foundation Autism Research Initiative and the Patrick J. McGovern Foundation.

For remotely operated underwater vehicles, cloudy and turbulent waters are often a no-go. When vehicles settle on the seafloor or dig through a sandbed, they can kick up clouds of sediment that make it tough for onboard cameras to see through. Often, the only thing to do is to wait until the marine dust settles before a vehicle can safely proceed. 

But a new underwater mapping technique developed by engineers at MIT and the Woods Hole Oceanographic Institution (WHOI) may allow vehicles to see through murky, low-visibility waters. 

The method fuses visual images from optical cameras with acoustic data from sonar sensors. The combination enables a vehicle to quickly map the general shape of its surroundings using sonar, even in low-visibility waters. A vehicle can move toward certain shapes in the sonar-mapped environment, coming close enough for optical cameras to visually resolve specific objects in detail. 

The technique is akin to pairing a dolphin’s echolocation with a sea turtle’s close-range vision to see and navigate through murky water, in real-time. 

The researchers tested the method in tank experiments where they could control the water’s degree of visibility. Even in the cloudiest conditions, the system was able to see through the sediment to map the tank’s environment and visualize centimeter-scale details of objects in the tank. 

The team is further improving the technique, which they’ve named Sonar-MASt3R. They envision that the mapping method could safely guide underwater vehicles through murky environments for a range of applications, including scientific exploration, underwater construction and maintenance, and deep-sea recovery. 

“We hope that this work enables us to do more operations in those challenging, low-visibility environments, and helps provide more coverage in areas that are difficult to operate in today,” says Amy Phung, a graduate student in MIT’s Department of Aeronautics and Astronautics, who led the work. 

Phung presented a paper detailing Sonar-MASt3R this week at the IEEE International Conference on Robotics and Automation (ICRA). The paper’s co-author is Richard Camilli, senior scientist of applied ocean physics and engineering at WHOI. 

The best of both

To see underwater, scientists have generally taken an either/or approach, using either optical cameras or sonar sensors to guide the way. Optical cameras can provide detailed visual imagery of a scene, but only in waters that are relatively clear and well-lit. In contrast, sonar sensors perform just as well in clear and murky water; by emitting acoustic waves and measuring the time and angle at which they return, sonar sensors can determine the exact shape, distance, and depth of objects in the environment, though a sonar map lacks any visual detail. 

To get the best of both modes, scientists have looked to combine the two in a new approach known as “opti-acoustic fusion.” In a handful of prior works, research groups have merged sonar and optical data in mapping techniques that are mostly geared toward object recognition and reconstructing workplace environments. Most techniques require time to sync and process the data and therefore do not work in real-time, while only a few can map an environment in 3D. None have been applied to high-resolution mapping underwater in murky, turbid conditions. 

Phung, who is a student in the MIT-WHOI Joint Program, and Camilli, her advisor, aimed to develop an opti-acoustic fusion technique that would generate detailed 3D maps of underwater environments in real time and in low-visibility conditions. The team was motivated, in part, by challenges in safely recovering unexploded underwater mines.

“There can be old explosives in areas that make it unsafe for ships to be in, and the ability to get rid of those safely is best done by robotics,” Camilli says. “But a lot of these explosives are set in surf zone environments where visibility adds to the challenge of doing this safely. That’s one of many applications that our technique can be used for.”

Cloudy, with a chance of mapping

The new method, Sonar-MASt3R, builds on an existing technique, MASt3R, that was developed by researchers in France. MASt3R is an image matching algorithm that is trained to take in visual images of the same scene and quickly estimate the relative depth of each pixel in the scene. In this way, MASt3R can generate a 3D map of the environment in real-time, based on a camera’s 2D images. 

“The downside is that there is no sense of scale,” Phung says. “It will say ‘this pixel is five units closer than this pixel,’ but it can’t say whether that’s 5 meters or 5 feet.”

Luckily, sonar provides absolute measurements of scale. The timing of sonar reflections can be translated directly into a specific depth and distance of objects that the signals bounced off, as well as their shape and contour. 

In their new work, Phung and Camilli used sonar data to correct MASt3R’s scaling and generate precise 3D maps of underwater environments. Even in murky water, the method’s sonar-corrected map would enable a vehicle to know the precise location of objects, and therefore how far to safely move in for a closer inspection, which the vehicle could then do using conventional optical cameras.

The team tested Sonar-MASt3R in experiments with a tank that they filled with water, sediment, and a variety of objects such as a small boulder, a coffee mug, and a packing crate. Inside the tank, they also set up a robotic arm, onto which they mounted an underwater camera, and a sonar sensor. 

For each experimental run, they first carried out a sweep trajectory, in which the robotic arm slowly swept from one side of the tank to the other to capture sonar and visual data. With this first sweep, Sonar-MASt3R quickly creates a coarse sonar-based map of the shapes and contours of the tank and its objects. The coarse map is then used to record close-up camera images of the objects, which are used to improve the map resolution. A “keyframe” approach quickly compares each new image frame to the last keyframe. If a frame provides new information not contained in the last keyframe, the image is added as a new keyframe to the map. If it is similar, it is immediately discarded. In this way, the approach can quickly fill in the map with relevant visual detail, in real-time. 

The researchers tested their new approach underwater, testing eight different levels of turbidity, which they created by stirring up the tank’s sediment. Compared with other opti-acoustic fusion approaches, Sonar-MASt3R generated more accurate 3D maps and resolved smaller, centimeter-scale details, and in cloudier conditions. In the cloudiest condition, which the robotic arm’s cameras could not see through, its sonar sensors were able to generate a rough map of the tank’s hidden objects. This initial map enabled the arm to move safely through the murk and closer to specific objects, which its underwater camera could then visualize in more detail. 

“An analogy would be if you were to go into a china shop in the dark, and try to pick your way around to find a specific coffee mug without knocking things over,” Camilli offers. “This would allow you to do that.”

The team plans to test the approach in natural underwater conditions, where they suspect that the mapping task should be more straightforward. 

“In a tank, it’s like an echo chamber,” Camilli says. “It’s like trying to do this in a funhouse mirror setting where you get all these distortions and reverberations and ghost images that really complicates the processing. If you put it in the real world, it should be easier.”

Then, they say, Sonar-MASt3R could help scientists safely explore in cloudy, turbid, and murky underwater regions.

“The real value in this effort is so we can use this technology in mission scenarios that are untractable right now,” Phung says. “And there are plenty of untractable missions because we don’t have the observational or perception capabilities.”

This research was supported, in part, by NASA, and the National Science Foundation.

Myriam Heiman, the John and Dorothy Wilson Professor of Neuroscience at MIT, will become the director of MIT’s Picower Institute for Learning and Memory, effective July 1. She succeeds Picower Professor Li-Huei Tsai, who is stepping down after leading the institute for 16 years.

Heiman, a molecular neurobiologist and geneticist, studies the neurodegenerative diseases of the brain’s basal ganglia, including Huntington’s disease and Parkinson’s disease. Using cutting-edge techniques, including single-cell genomics and a powerful transcriptomic technique she helped invent, called translating ribosome affinity purification, she aims to understand the molecular changes that eventually lead to cell death in these diseases. 

“Myriam is an extraordinary scientist, a proven leader within MIT, and a deeply caring and generous mentor. Her research to determine why specific brain cell types are particularly vulnerable to diseases such as Huntington’s has produced studies that are both deep in their insight and sweeping in their scope,” says Nergis Mavalvala, dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics. “I firmly believe that Myriam will be an excellent leader during the Picower Institute’s next chapter.”

“I am honored to take on this role to support the institute’s exceptional scientists and trainees as they pursue discoveries that deepen our understanding of the brain and improve human health,” says Heiman, a professor in MIT’s Department of Brain and Cognitive Sciences (BCS). 

The Picower Institute is a community of 16 neuroscience labs dedicated to understanding the mechanisms that drive learning and memory and related functions such as cognition, emotion, perception, behavior, and consciousness. Institute neuroscientists explore the brain and nervous system at multiple scales, from genes and molecules to cells and synapses to circuits and systems, producing novel insights into how disruptions in these mechanisms can lead to developmental, psychiatric, or neurodegenerative disease. 

Picower Professor Susumu Tonegawa founded the institute as a center in 1994 before a transformative gift from Barbara and Jeffry Picower enabled it to become an institute in 2002. Li-Huei Tsai has served as director since 2009, but announced in March that she would step down after more than 16 years to focus on her research.

Heiman joined the Picower Institute, BCS, and the Broad Institute of Harvard and MIT in 2011, after completing her postdoctoral training at The Rockefeller University. She holds a PhD from Johns Hopkins University and a BA from Princeton University. 

“Ever since joining the institute, Heiman’s research has been guided by the principle that fundamental understanding can lead to breakthroughs in addressing disease,” Tsai says. “Myriam has made it her mission to address these kinds of urgent questions in neuroscience.”

Heiman employs sophisticated DNA and RNA analysis technologies to gain detailed insights into how brain cell states change amid disease, revealing molecular pathways that contribute to the particular vulnerability of different cell types. In 2020, Heiman published the results of an innovative in vivo screening of every mouse gene’s impact on the survival of neurons in the brain, identifying hundreds necessary for sustaining neurons and highlighting a specific gene that promoted their resilience in the context of Huntington’s disease. 

Other studies, both in mice and in postmortem human brain samples, have revealed errant immune responses in neurons and in the brain’s blood vessels that contribute to the disease’s progression. The latter finding arose in a 2022 paper, published with MIT Computer Science and Artificial Intelligence Laboratory colleague Manolis Kellis, that also provided the field one of the first cellular atlases of the brain’s vasculature.  

Her research has also produced insights into other neurodegenerative and psychiatric disorders, including ALS and frontotemporal dementia. In 2024, together with Kellis, Heiman published a paper in Cell showing the diseases have remarkable overlaps at the cellular and molecular levels, revealing potential targets that could yield therapies applicable to both disorders. Heiman’s latest research is also producing new insights into substance use disorders and schizophrenia.

Her research program has garnered many awards. In 2021, Heiman became co-recipient of a National Institutes of Health Transformative Research Award, which “promotes cross-cutting, interdisciplinary approaches that could potentially create or challenge existing paradigms” as part of the NIH’s High-Risk, High-Reward Research program. The next year she also received a prestigious NIH R35 grant to find early triggers of disease progression.

Heiman is also a dedicated teacher and mentor. In 2017, she earned the Department of BCS award for excellence in graduate mentoring; and in 2020, she received the department’s award for excellence in undergraduate teaching. In 2024, she was named one of 23 faculty across MIT who are “committed to caring” — an award given out by MIT’s Office of Graduate Education to faculty members who have served as exceptional mentors to graduate students.

Beyond MIT, Heiman serves on editorial boards and the scientific advisory board of the nonprofit Huntington’s Disease Foundation, an organization that supports research aimed at finding treatments and a cure for Huntington’s and related disorders.. 

Heiman says she is looking forward to her new role in service to MIT by leading the Picower Institute.

“I approach this role with humility and enormous enthusiasm,” Heiman says. “The Picower Institute has an extraordinary legacy, and I’m eager to do everything I can to help support the next generation of transformative research.”

A new kernel, or core program within an operating system, gives researchers a cleaner view of what’s happening inside a processor. Called Fractal and developed at MIT, the kernel has already surfaced previously unknown behavior in Apple’s M1.

When security researchers want to understand what a modern processor is really doing with the kind of detail that determines whether attacks like Spectre and Meltdown are possible, they usually run their experiments on top of an operating system that was never built for the job. They open up macOS or Linux, patch the kernel by hand, and hope the modifications hold. The approach is unstable, hard to reproduce, and on Apple’s platforms, slated for deprecation.

A team at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) decided to build something different. Fractal, an operating system kernel written from the ground up, treats the hardware itself as the object of study. Its first major use, a deep look at branch predictors — a CPU’s way of guessing what code to run next, before it knows for certain, so it doesn’t have to waste time waiting to find out — inside Apple’s M1 processor, has already turned up findings that prior work missed, including the first evidence that a class of speculative attack known as “Phantom” affects Apple Silicon.

“We’re using hardware in ways it wasn’t designed for,” says Joseph Ravichandran, the MIT PhD student in electrical engineering and computer science (EECS) who led the project. “It’s not even obvious that this is a possible thing you could do with the hardware. But we found a way to pull all these different primitives off. It’s like a microscope. If you’ve got a hand magnifying glass, you can see a little bit. But if you had an electron microscope, now we’re really talking. That’s what Fractal is. The electron microscope of operating systems.”

A clean room for chip research

The core problem Fractal solves is one that researchers have worked around for years. Modern processors keep state in many internal structures: branch predictors, caches, translation lookaside buffers, and more. To study how those structures behave across the boundary between user code and kernel code, two domains the chip is supposed to keep isolated, researchers need to run nearly identical experiments on each side of that boundary. On a general-purpose operating system, that is very difficult. The system itself manages privilege levels, address spaces, and scheduling, and it injects its own activity into every measurement.

Fractal inverts the model. It boots directly on bare metal, with no other software running, and exposes primitives that let a single experiment switch privilege levels at runtime while executing the same instructions in the same address space. The team calls the underlying technique multi-privilege concurrency, and it relies on a new construct they introduced: the outer kernel thread, which sits inside a user process’s memory but executes with kernel privileges.

The result is an experimental setup with almost no background noise. Where measurements taken under macOS or Linux are blurred by interrupts, scheduler activity, and address-space management, Fractal produces flat baselines and clean signals.

What Fractal found on the M1

Apple’s M1 implements an ARM specification called CSV2, which is supposed to prevent code running in one privilege level from steering speculation in another. Using Fractal, the MIT team confirmed that the protection works for the execute stage of indirect branch prediction: a user-mode program cannot make the kernel speculatively execute a chosen target through the indirect branch predictor.

But the team also found something the chip’s designers may not have intended. The CPU still fetches the target into the instruction cache before the protection kicks in. That fetch is observable through a side channel, which means user code can still influence what the kernel pulls into its caches across the privilege boundary. The same pattern appeared between processes assigned different address space identifiers.

The team also produced the first evidence that Apple Silicon exhibits Phantom speculation, a class of misprediction previously demonstrated only on AMD and Intel processors. In Phantom, ordinary instructions, including a no-op, can be misinterpreted by the CPU as branches, triggering speculative behavior the program never asked for. On the M1, Fractal showed that Phantom fetches succeed across both privilege levels and address spaces, though the execute phase remains blocked.

A separate Fractal experiment overturned a finding from earlier work on the M1’s conditional branch predictor, which had reported that cross-privilege training worked on Apple’s performance cores, but not its efficiency cores. The Fractal team showed that the conditional branch predictor has no privilege isolation at all, on either core type, and that the earlier result was likely an artifact of macOS quietly migrating threads between cores during system calls.

“For us, it is a true independent variable,” Ravichandran says. “You change the privilege level, nothing else changes. The only thing that could explain whether the attack succeeds or not is the privilege level.”

A tool, not a one-off

Fractal supports x86_64, ARM64, and RISC-V, and consists of more than 31,000 lines of code. The team designed it as infrastructure rather than as a single experiment, with familiar POSIX system calls, a C library, and ports of standard tools like vim, GCC, and the dash shell, so that researchers can move existing experiment code over with minimal friction.

The MIT team disclosed its M1 findings to Apple’s product security team. In an unusual reversal, Apple’s engineers also examined Fractal. 

The longer-term ambition is bigger than any single result. Ravichandran wants Fractal to become to microarchitecture research what tools like QEMU and FFmpeg are to their fields: shared infrastructure that the whole community builds on. 

“My hope is that our results as a community get significantly more reliable, significantly more accurate,” says Ravichadran. “With this reduced noise, this clarity, and this guarantee that you’re running on the right core, on the right system.”

“Fractal is a strong architecture contribution because it turns an often ad hoc microarchitectural reverse-engineering workflow into reusable research infrastructure,” says University of Southern California assistant professor Mengyuan Li, who wasn’t involved in the paper. “By reducing software noise and giving researchers tighter control across privilege boundaries, it makes difficult hardware experiments much easier to interpret.”

Ravichandran worked with Mengjia Yan, an MIT associate professor of EECS and CSAIL principal investigator, on the paper. Their work was supported, in part, by the National Science Foundation, the U.S. Air Force Office of Scientific Research, and ACE, which is part of a program sponsored by the U.S. Defense Advanced Research Projects Agency. They presented their work at the IEEE Symposium on Security and Privacy in San Francisco, California.

MIT professor of physics Pablo Jarillo-Herrero is among 10 researchers worldwide to receive this year’s prestigious Kavli Prize. 

Jarillo-Herrero is co-recipient of the 2026 Kavli Prize in Nanoscience “for foundational work that established the field of twistronics.” His co-recipients are professors Eva Y. Andrei at Rutgers University and Allan MacDonald from the University of Texas at Austin.

These three physicists are being honored for the theoretical foundation and experimental validation of a new field of “twistronics,” where superconductivity, magnetism, and other properties can be obtained by rotating two-dimensional materials such as graphene to a “magic angle.”

A partnership among the Norwegian Academy of Science and Letters, the Norwegian Ministry of Education and Research, and the Kavli Foundation, the Kavli Prizes are awarded every two years to “honor scientists for breakthroughs in astrophysics, nanoscience and neuroscience that transform our understanding of the big, the small and the complex.” The laureates in each field will share $1 million.

“Pablo’s groundbreaking research has once again been given well-deserved recognition,” says Nergis Mavalvala, dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics. “Pablo and his co-recipients have pioneered twistronics, very fundamental scientific research that has opened up a new field with myriad possibilities for novel quantum materials.”

In 2009, using scanning tunneling microscopy and spectroscopy on graphene, most commonly found as a single layer of carbon atoms arranged in hexagons resembling a honeycomb structure, Andrei and her research group demonstrated that small variations in twist angle profoundly modified the electronic structure. This demonstration — that geometric control, rather than chemical composition, could modify a material’s electronic structure — represented a fundamental advance in materials design and arguably launched the field now known as “twistronics.”

In 2011, MacDonald quantitatively explained the emergence of this electronic structure by geometries at discrete magic angles. This framework has since become the theoretical foundation of what are known as moiré materials, and has guided subsequent experimental and theoretical developments across a wide range of twisted and layered systems. 

In 2018, Jarillo-Herrero’s group observed correlated insulating phases and superconductivity in magic-angle twisted bilayer graphene devices. The resulting platform, “combining atomic-scale structural simplicity with electronic tunability, has enabled systematic investigations has had broad and lasting impact across nanoscience and quantum material research,” according to the Kavli Prize citation.

“It was a big surprise, because the technique we used, though conceptually straightforward, was hard to pull off in the lab,” said Jarillo-Herrero recently. He is also the Cecil and Ida Green Professor of Physics at MIT and a member of the Research Laboratory of Electronics. 

“I’m humbled and incredibly honored to be sharing this award with [Andrei and MacDonald],” Jarillo-Herrero noted in an essay describing his journey to the Kavli Prize. “I want to also emphasize that this award honors fundamental physics research in nanoscience. It is incredibly important for society to continue to support fundamental research: Although it often doesn’t have a direct near-term application, in the long run it happens to be the most transformative and impactful in society.”

“Pablo’s research has helped spark a revolution in condensed matter physics and nanoscience, inspiring physicists worldwide to explore superconductivity and other emergent phenomena in engineered quantum materials. This work could potentially lead to the creation of superconductors at room temperature, which would would have an enormous technological impact,” says Deepto Chakrabarty, physics department head and William A. M. Burden Professor in Astrophysics.

Jarillo-Herrero's win brings the number of all-time MIT faculty recipients of the Kavli Prize to nine. Prior winners include Nancy Kanwisher in neuroscience (2024), Bob Langer in nanoscience (2024), Sara Seager in astrophysics (2024), Rainer Weiss in astrophysics (2016), Alan Guth in astrophysics (2014), Mildred Dresselhaus in nanoscience (2012), Ann Graybiel in neuroscience (2012), and Jane Luu in astrophysics (2012).

Interpreting medical ultrasound images is a difficult task, requiring a technician to look at 2D images and mentally arrange them into a 3D representation of what the tissue looks like. 

To make that job easier, MIT researchers developed a new approach to ultrasound imaging that allows the user to visualize a 3D augmented-reality image of the object being scanned. Using a virtual-reality headset, they can see a precise 3D digital representation of what the object actually looks like, making it easier to identify and analyze.

This technique could help speed up the training process for ultrasound technicians and other health care providers who use ultrasound. It could also be deployed for use in hospitals, for tasks such as using ultrasound to place a needle in the right location for a biopsy.

“For training, this could make ultrasound more intuitive and more understandable. On the clinical side, it could be less time-consuming, more accurate, and also give health care providers more peace of mind. They wouldn’t have to wonder if they missed anything,” says Canan Dagdeviren, an associate professor of media arts and sciences at MIT and the senior author of the study.

MIT graduate students Jason Hou and Shrihari Viswanath are the lead authors of the paper, which appears today in Nature Communications Engineering. Other authors of the paper include Bowen Wu ’24 and two MIT Summer Research Program students, Cinay Dilibal, a senior at Dartmouth College, and Tanisha Shende, a senior at Oberlin College.

3D representations

Ultrasound imaging works by bouncing high-frequency sound waves off tissues in the body, which are then reflected back to an ultrasound transducer. The transducer converts these sound waves to electrical signals, which are used to create a 2D image of the tissue. Ultrasound technicians are trained to convert these images into a 3D mental representation of the tissue.

“It's a difficult skill to master, and there are long learning curves,” says Hou. “The hardest thing is this mental tomography bottleneck where you’re trained to reconstruct the 2D slices in your 3D mental space. That is a cognitive burden that can lead to inaccuracies in scanning.”

To reduce that cognitive load, the MIT team thought it could be helpful to combine two technologies: 3D ultrasound imaging and augmented reality (AR). 

Three-dimensional ultrasound imaging is occasionally used in fields such as fetal imaging and echocardiography, which is used to image the heart, but most 3D ultrasound imaging systems are expensive and not widely available. For this study, the MIT team used a real-time 3D system they developed recently for use in breast-cancer detection.

Their new system includes an ultrasound probe, slightly smaller than a deck of cards, that transmits information using a chirped data acquisition system (cDAQ). The probe contains an ultrasound array arranged in the shape of an empty square, a configuration that allows the array to take 3D images of the tissue below.

Because this system has fewer ultrasound elements than a typical 3D ultrasound system, it requires less power and is less expensive to build.

The data collected by the ultrasound probe can then be compressed and streamed into a 3D computer graphics engine called Unreal Engine, which converts the voxel data from the ultrasound image into a direct 3D representation of the object, with no loss of information. Wearing an AR/VR headset, the user can see this 3D rendering representing the internal structure, superimposed over the object’s actual location — like X-ray vision. By tilting their head or approaching from a different direction, the user can see different views of the object, making it easier to identify.

Easier to use

The researchers tested their new technology, which they call AR-VIU (augmented real-time volumetric imaging in ultrasound), with a group of 18 participants. Nine of the subjects were experts in ultrasound technology (including sonographers and physicians), and nine had never used ultrasound before.

Each user performed identification tasks using four different ultrasound technologies. In one condition, they viewed 2D images on a regular screen, which is the way that most ultrasounds are now performed. They also viewed 3D images on a regular screen, as well as two augmented reality conditions: one 2D and one 3D (AR-VIU).

In one round of experiments, users were asked to identify an object embedded in gelatin — such as a spring, a ball, or a screw — inside an opaque container that was scanned with ultrasound. In a second set, they were asked to use a pen to mark the location of “tissue phantom” — a gel-like material engineered to mimic human tissue. This simulates the task of locating the right spot for a needle during a biopsy.

The researchers found that the AR-VIU system significantly improved all users’ ability to identify and locate objects. The effect was especially strong for novices, who performed nearly as well as experts when using AR-VIU. When using the traditional 2D imaging system, experts performed much better than novices.

“Overlaying images with the anatomy and providing 3D visual context makes ultrasound significantly easier for novices to understand,” Viswanath says.

In interviews after the experiments, most of the novices reported that they preferred the AR-VIU approach, with many saying that it made the tasks easier.

“The 3D system imposes less brain drain, it’s more intuitive, and it’s easier to understand what is happening in the targeted region,” Dagdeviren says.

Many of the experts said they preferred the traditional 2D imaging because that is what they were accustomed to and had been trained to use. However, those experts also said they could see the benefits of the AR-VIU system in some situations, such as placing a needle for a biopsy or visualizing the movement of the heart wall during echocardiography.

The researchers are now working on further improving the resolution of the imaging and doing additional tests to demonstrate the accuracy of the AR-VIU technology.

The research was funded by the MIT Media Lab Consortium, the National Science Foundation, an MIT HEALS graduate fellowship, and an MIT-Tata graduate fellowship.

The rise of artificial intelligence is riding on the back of an enormous data center expansion. Data centers are projected to account for anywhere from 9 to 17 percent of total electricity usage in the U.S. by the end of the decade. Today, around a third of data center electricity is devoted to cooling the chips that run AI models.

That’s the process Ferveret is working to make more efficient. The startup, founded by Reza Azizian, a former MIT postdoc in nuclear engineering, and Matteo Bucci, MIT’s Esther and Harold E. Edgerton Associate Professor in the Department of Nuclear Science and Engineering, is adapting an approach from nuclear reactors to cool chips using no water and significantly less electricity.

The company’s cooling system submerges computer servers in a specialized liquid that absorbs heat much more efficiently than air from a fan. What makes the solution different from other liquid cooling systems are the bubbles: Ferveret’s Adaptive Phase Cooling (APC) solution produces much smaller bubbles at the surface of the server, which detach more frequently, accelerating the heat transfer process.

Ferveret is already testing its solutions with companies including CleanSpark, the data center developer and operator, as well as FuriosaAI, an AI accelerator company, and Switch, one of the largest data center operators in the U.S.

In a recent study in collaboration with the Samueli Computer Science Department at the University of California at Los Angeles, Ferveret found its APC solution led to a 15 percent improvement in computational power efficiency compared to state-of-the-art liquid cooling solutions. By combining those savings with Ferveret’s power control system to optimize operating conditions, the company says it allows data centers to get 35 percent more tokens — small pieces of text or data — from their AI models with the same amount of power.

“Our goal is to make data centers as sustainable as possible and help them use every single watt of power to generate tokens, which are the most useful outputs,” Azizian says. “Our system enables the operation of more powerful chips, it helps data centers waste a lot less energy, and it accomplishes all that with zero water consumption.”

From nuclear reactors to AI

Azizian was a postdoc at MIT in 2013 when he met Bucci, who was then a research scientist. They worked on heat transfer in nuclear reactors before Azizian went into industry, where he shifted his focus to cooling chips. Azizian first worked on Microsoft’s HoloLens augmented reality headset and then joined Nvidia, which produces the graphical processing units companies use to train and run the latest AI models. Meanwhile, Bucci continued conducting research at MIT, becoming an assistant professor in 2016.

Azizian walked into his first data center in 2017, where he was struck by the massive, noisy fans that filled the building as they cooled.

“I thought, ‘Holy crap, this is not how you cool facilities,’” Azizian recalls, noting air cooling can still take up 40 percent of the power going into a data center. “It was not an efficient way of doing things, but since it wasn’t hurting the performance, no one cared that the cooling technology was 50 years old.”

Azizian began talking with Bucci about applying their knowledge around optimizing heat transfer in nuclear reactors to data centers. Scientists have spent decades finding better ways to move heat in nuclear reactors.

“Heat transfer determines how much energy you can extract from the reactor core, which translates directly to revenue,” Azizian explains.

The founders started Ferveret in 2021. A lot has changed since Azizian walked into his first data center. Chip companies have packed more and more components onto their chips as the explosion in artificial intelligence has put a premium on squeezing as much computing capacity as possible out of limited power supplies.

That has driven data center operators to use liquid to cool chips — often through a technique known as immersion cooling that submerges chips in liquid. The most effective form of immersion cooling brings the liquid to a boil.

“Liquid is a better heat transfer medium than air. That’s why when you stick your hand into room temperature water it still feels cold,” Bucci explains. “When liquid is boiling, it becomes even better at removing heat because the phase change requires a lot of energy, which is the energy you remove from the chip. That lets you transfer large quantities of heat with minimal temperature differences between the chips and the liquid.”

Unfortunately, boiling liquid adds complexity to the system because it forces operators to capture and reliquefy the bubbles while controlling for pressure, temperature, and fluid inventory.

Ferveret’s system is adapted from a process in nuclear reactors called subcooled boiling. It uses a liquid with a low boiling point and none of the toxic PFAS “forever chemicals” that other approaches rely on. At the surface of the chip, Ferveret’s liquid produces smaller bubbles than other immersion cooling approaches. Those bubbles detach more frequently and quickly recondense in the surrounding liquid, accelerating the bubble-rewetting cycle at the surface of the chip to hasten heat transfer.

Ferveret delivers its APC system in small boxes, each of which houses one server. The founders say their modular systems make it easier to deploy the system and simplify maintenance.

“The physics enable us to get to form factors that weren’t possible in the past,” Azizian says. “Most immersion cooling solutions are large tanks that people submerge the servers in. We have a smaller, modular rack-mounted solution that makes it adaptable to the current infrastructure, so it’s easier for people to deploy our technology.”

Ferveret also offers control software that adjusts the power going to each server in real-time to further improve efficiency.

“We deliver full-stack systems that include the cooling box, the rack, the cooling distribution units, and sensors that measure the temperature and pressure,” Bucci says. “Our software monitors those sensors and optimizes the operating condition inside each box to ensure that energy consumption is minimized in the system.”

AI with fewer resources

In addition to helping data centers to run more efficiently, Ferveret is also improving sustainability by making it easier to operate data centers in remote regions with more renewable energy.

“The sun shines in places where you don’t have much water, so the advantage of us being water-free is we allow you to build data centers where you have solar energy but nothing to cool the data center down,” Bucci says. “This technology can help deploy data centers in regions where normally you wouldn’t have the resources to do so, including Africa, the Middle East, and of course parts of America. It’s a huge unlock.”

Ferveret is in talks with the large cloud computing companies known as hyperscalers, and is currently part of Nvidia’s Inception program for startups. The company plans to announce expanded partnerships later this year. From there, the founders plan to quickly scale their technology to help the AI industry continue to grow without further straining the planet.

“The computing industry is facing a huge challenge in the form of access to power, and they have a problem with access to water in many regions,” Azizian says. “That will only become more limiting as the industry grows. The main goal for these data center operators would be to get more tokens from the power they have. We’ve shown we can do that.”

It’s no secret that the last few years have seen a massive explosion in the use of artificial intelligence for general information-gathering. An even more recent trend, though, is how large language models (LLMs) like ChatGPT, Claude, and Gemini are increasingly being used for verifying and consuming news; reports from the Pew Research Center over the last year found that one-in-five U.S. teens regularly use LLMs to get their news, while one-in-four young adults have reported using them for that purpose at least once. 

A new open-access study from the MIT Media Lab should give some of those users pause: Researchers found that, over the course of a month, participants who relied on AI systems to verify facts actually got worse at detecting misinformation on their own when their chatbots were taken away.

This phenomenon, which is often referred to as the “AI dependency paradox,” has been observed in a wide range of knowledge domains, like the 2025 study that found that doctors who used AI got worse at detecting cancer on their own. The dynamic mirrors broader tech trends around so-called “deskilling” (or “cognitive offloading”) that have been well-documented for decades, from calculators weakening our math skills to Global Positioning System (GPS) technologies impacting our natural sense of direction.

In the new Media Lab study, which tracked 67 people over four weeks as they evaluated news headline-image pairs, participants were 21 percent more accurate in detecting fake news when assisted by an AI chatbot during a session — confirming previous research out of the MIT Sloan School of Management demonstrating that AI can be an effective tool in reducing people’s beliefs in false information.

However, the study showed that a new wrinkle emerged when the AI was no longer present: By week four, participants’ unassisted performance on new news items declined by 15 percentage points compared to before the study started. (Roughly a quarter of all participants actually reported feeling that they were getting better at detection, even as their performance declined.)

Dunning-Kruger creeps in

“Users get excited about these ‘magical’ LLMs, but forget that they’re just statistical models that predict the next ‘token’ in a sequence [of letters/words],” says MIT media arts and sciences (MAS) PhD student Anku Rani, co-lead author of a new paper about the research, alongside fellow MAS PhD student Valdemar Danry. “Many impressive behaviors emerge from scaling this, but it comes with real limitations, both in what the model can reliably generate and in its broader impact on the people using it.”

Qualitative analysis identified distinct behavioral patterns, with the team labeling one-fifth of all participants as "Dependency Developers” who gradually shifted from active self-reliance to passive acceptance of AI guidance.

In the post-experiment survey, one respondent explicitly acknowledged this transition, noting their passive role in the process. “While [the chatbots] did emphasize that you must check across multiple sources to make sure a story is true, they didn’t teach me much about exploring the context of the images themselves,” the participant said.

The research team said that these AI models are particularly vulnerable to mistakes in the midst of emotionally charged breaking news, as exhibited by the widespread misinformation that accompanied President Trump’s recent assassination attempt and major events during the Iranian war. (The authors also point out that the original human-created news content that’s used to train the AI models is increasingly unreliable and/or biased, further exacerbating the problem.)

The paper, which Danry and Rani presented at the 2026 CHI Conference on Human Factors in Computing Systems, was co-authored by Assistant Professor Paul Pu Liang, Senior Research Scientist Andrew Lippman, and senior author Pattie Maes, the Germeshausen Professor of Media Arts and Sciences. 

The solution: Being a coach, not a crutch

The researchers say that the results of their project suggest that the specific way in which an AI interacts with a user determines whether its impact will be “as a coach, versus as a crutch.” The study found a clear distinction between conversational strategies that simply help in the moment and those that actually support active learning and skill development.

For the latter, the Media Lab team uncovered several strategies associated with stronger independent detection later on, even if the strategies initially slowed down performance during the interaction. This included the Socratic method of the AI asking guided questions, as well as so-called “deep probing,” where the system provides gently persuasive statements if the user appears to be veering away from the correct response.

“AIs that ‘tell’ by providing direct answers are more likely to foster reliance, while those that ‘ask’ via Socratic questioning are better at engaging someone to actually learn how to discern the truth on their own,” says Danry. “But it’s very much a trade-off between speed and effort.”

Rani noted a few key limitations to the one-month study, from the small dataset of roughly 50 validated news items to the demographic focus on the United States and the United Kingdom. In the future, she says that the team hopes to do similar experiments with more geographically diverse cohorts, including low-resource communities, and is also eager to explore whether other multi-modal interaction strategies — like interacting with culturally adaptive digital twins instead of text-based chatbots — help people improve their abilities to detect misinformation. 

At a higher level, the researchers hope that the project will be something that educators can examine as they develop teaching plans that incorporate AI tools into their school curricula.

“It’s especially important to raise awareness in our schools and academic communities about the shortcomings of using AI as learning tools,” says Maes. “People need to know that if they ‘delegate’ their thinking, they’re not going to get better at that particular brand of problem-solving. Ultimately, the ability to question and analyze information is important for everyone, because it empowers us to solve problems and form our own independent opinions about the world.”

Danry adds that the rapidly-evolving field of machine learning and deep learning will require continuous education on the benefits and drawbacks of LLMs.

“There’s a lot of work to do in making sure that we don’t just fully offload critical tasks that we want to be able to keep on doing to these models,” he says. “We need to develop a new kind of AI literacy.”

The research project was supported, in part, by the Media Lab Consortium, an MIT Tata Center Technology and Design Fellowship, and a Google PhD Fellowship in Human–Computer Interaction.

Chris Zegras, professor of mobility and urban planning and the current head of the MIT Department of Urban Studies and Planning (DUSP), has been appointed chief executive officer and director of the Singapore-MIT Alliance for Research and Technology (SMART), effective Sept. 1. Zegras succeeds Bruce Tidor, professor of biological engineering and computer science, who has served as interim CEO and director since January 2025.

Established in collaboration with the National Research Foundation of Singapore in 2007, SMART is MIT’s only research center outside the United States​. Housed within the Campus for Research Excellence and Technological Enterprise, SMART serves as a key platform for collaboration between MIT and Singapore’s research ecosystem, bringing together leading experts and institutions from the United States, Singapore, and the region for world-class research and innovation.

“Professor Zegras brings a distinguished track record of interdisciplinary leadership and a deep understanding of SMART’s mission and impact,” says Anantha Chandrakasan, MIT’s provost, who announced Zegras’ appointment in a letter to the MIT community today. “His appointment reinforces MIT’s commitment to the alliance, which has advanced innovation and driven global impact, and which remains as important as ever in a time of accelerating technological and global change.” 

Zegras joined the MIT faculty in 2005 and has served as the head of DUSP since 2020. His own research spans interrelated areas critical to tackling metropolitan mobility challenges: leveraging computational technologies for understanding and modeling human behaviors and enhancing strategic planning capabilities.

Zegras brings extensive experience in interdisciplinary research and leadership and a long-standing connection to SMART, where he led collaborative research on next-generation mobility sensing and simulation systems. From 2010 to 2020, he was a principal investigator on the Future Urban Mobility interdisciplinary research group; from 2016 to 2020, he was the group’s lead principal investigator. During this time, the group spearheaded Singapore’s first-ever public autonomous vehicle trials, developed and deployed large-scale urban simulation and visualization systems, and conducted research that evolved into spinoff companies, among other activities. 

“Bringing together leading experts from the U.S., Singapore, and around the world, SMART has established itself as a unique hub for interdisciplinary collaboration and innovation that addresses pressing societal issues,” says Zegras. “Having experienced firsthand what this distinctive model can achieve, I look forward to building on this strong foundation to deepen collaboration, strengthen our innovation ecosystem, and accelerate the translation of research into meaningful real-world impact.”

SMART is built around interdisciplinary research groups, all headed by senior MIT faculty members. At present, there are six groups, focused on antimicrobial resistance; the use of living cells as personalized medicines to treat and prevent diseases; social and institutional challenges arising from the proliferation of AI and emerging technologies; new agricultural technologies; wafer-scale 3D sensing technologies; and wearable ultrasound imaging. SMART is also home to the SMART Innovation Center, which aims to get research ideas from lab to market.

MIT researchers have demonstrated a low-cost design of specialized electronic nozzles, called triaxial electrospray emitters, that could be used to manufacture time-release drug-delivery particles or self-healing materials efficiently and at scale.

Triaxial electrospray emitters use electricity to precisely dispense three liquids from microscopic nozzles to generate a steady stream with three distinct fluid layers. The liquid forms multilayered droplets, which can solidify into layered microparticles.

For instance, an array of triaxial electrospray emitters can be used to make three-layer drug-delivery nanoparticles. The outer layer might slowly erode in the stomach, revealing a second material that controls the release of a core material, which delivers medicine to a specific area of the intestines.

Developing a tiny array of electrospray emitters typically requires expensive and time-consuming microfabrication processes inside semiconductor cleanrooms, which limits their use. To overcome these drawbacks, the MIT researchers 3D-printed arrays of triaxial electrospray emitters that have 16 nozzles in an area of about one square centimeter. Each device contains an intricate network of three-dimensional microchannels that uniformly supply liquid to the nozzles. 

Their one-step fabrication process takes only a few hours to produce complex emitter arrays. 

When tested, the 3D-printed arrays generated uniform, three-layered droplets at scale. Such uniformity is key for high-throughput manufacturing of layered microparticles for applications like biosensors that detect chemical substances or artificial cells to aid in tissue regeneration.

“We couldn’t make a device like this in a semiconductor cleanroom. This is only possible because they are 3D-printed,” says Luis Fernando Velásquez-García, a principal research scientist in MIT’s Microsystems Technology Laboratories (MTL) and senior author of a paper describing this advance. “The particles these devices generate, whether they are used for a self-healing composite or to deliver medicine, can have a big impact in many applications. We want to democratize this technology so the benefits can touch many more people.”

Velásquez-García is joined on the paper by lead author Bryan Ivan Quintanar-Abarca of the Technological Institute of Monterrey in Mexico. The research appears in Virtual and Physical Prototyping.

A precise process

Electrospray emitters apply a high voltage to a liquid as it exits the device’s nozzle, producing a steady stream of extremely tiny droplets. 

Triaxial devices contain arrays of three concentric nozzles that emit three immiscible, or non-mixable, liquids simultaneously into layered droplets, which can be used to generate compound microparticles with distinct layers.

For instance, one could use a triaxial electrospray emitter to create a biosensing particle that contains three different chemical markers, one in each layer. Electrospray emitters can make smaller microdroplets much faster than other techniques.

Miniaturization is key for electrospray devices, since the smaller the emitter, the lower the voltage required to generate droplets. The output of a single electrospray emitter is modest, so arrays of emitters are required to boost droplet production without sacrificing uniformity. 

Multi-emitter electrospray devices are typically manufactured in semiconductor cleanrooms, but traditional processes limit the shapes and sizes of device components. The researchers could not find any previous reports of a miniaturized triaxial electrospray array in the open literature, highlighting the novelty of this work.

“When you build a triaxial array, you need to find a way to create geometries that have many integrated parts and extremely fine structures in the smallest footprint possible. And you need to ensure the devices will work uniformly,” Velásquez-García explains.

To do this, he and his collaborators used a 3D-printing technique called vat photopolymerization, which utilizes light to solidify extremely thin layers of liquid resin, fabricating a complex device one layer at a time. 

This extremely precise process enabled the researchers to print layers that were only 25 micrometers tall, just a fraction of the width of a human hair. In this way, they could generate the complex internal geometry needed for a triaxial electrospray emitter.

Refining the design

The array, which is slightly larger than a U.S. penny, contains a network of internal coiled channels that carry liquid to 16 nozzles. These helical microchannels help maintain a uniform spray of microdroplets across all nozzles, while keeping the device as compact as possible. 

“In a sense, the emitters in the array never learn they have company, or otherwise there would be cross-talking and causing interference between them. We achieved uniformity because of the work that went into our designs,” Velásquez-García says.

They also needed to fabricate extremely tiny channels without support structures, which could clog the device, and ensure all uncured resin was removed before the array was used.

The microchannels funnel liquid to the concentric nozzles, which must be perfectly aligned to properly emit microdroplets in a consistent manner.

“We were able to aggressively optimize the design because we could iterate in a much timelier manner. This ability to exquisitely refine designs is a key advantage of 3D printing,” Velásquez-García says.

The researchers tested multiple architectures to determine the ideal combination of liquid flow rates to maximize the stability and consistency of emitted microdroplets. They were surprised to find that the viscosity of the middle liquid plays the most important role in achieving stability in a microdroplet, since it preserves the thickness of each layer. 

In addition, the researchers found that by adjusting flow rates and voltages, they could precisely tailor the thickness of each microdroplet layer. This would allow scientists to design drug-delivery particles with ideal layers so medicine releases at exactly the right time.

“By making such intricate devices more practical, we can empower others to pursue entrepreneurial and scientific advances,” Velásquez-García says. 

In the future, the researchers want to continue refining their fabrication process and designs to achieve even smaller dimensions and integrate conductive or dielectric materials to the devices to make more advanced electrospray emitter arrays.

This research was funded, in part, by the Tecnológico de Monterrey – MIT Nanotechnology Program. 

When MIT mechanical engineering Professor Kripa Varanasi landed in New Delhi in the middle of the night in June 2024 to attend a conference, he found himself in 104-degree Fahrenheit heat. 

“This was June, and it was crazy. It was so hot for the whole meeting that I never left the hotel,” with daytime temperatures nearing 122 F.

It didn’t used to be that way. “When I grew up in India, it was not like this,” Varanasi says. “That kind of inspired me.” 

He found a way to begin tackling the issue through a grant from the MIT Climate Project that provided seed funding to develop a proof-of-concept prototype of a wearable personal cooling system. The grant was one of four that were part of a Critical Cooling initiative for which the Climate Project requested proposals last year. The projects, which received grants totaling $450,000, are now complete. All have showed promise, and are now exploring ways to further develop their concepts.

Another MIT researcher, Yet-Ming Chiang, the Kyocera Professor of Materials Science and Engineering, looked into the potential of subsurface wells with heat-absorbing materials to supply spaces with air far below peak ambient temperatures while using much less energy than evaporation-compression heat pumps. The aim would be to use such systems in both small apartment buildings and single-family homes in India and other parts of the Global South.

Meanwhile, Asegun Henry, the George N. Hatsopoulos Professor in Thermodynamics, studied the use of an alternative approach to air conditioning to be more energy efficient and eliminate hydrofluorocarbon refrigerants that are potent greenhouse gases. His approach uses a cheap, widely abundant solid “caloric” material — rubber — to obtain a cooling effect, and then uses plain water as an efficient heat transfer fluid. The initial target market is single-family houses and apartment buildings, although larger systems could also serve data centers.

And Gang Chen, the Carl Richard Soderberg Professor of Power Engineering, addressed the tendency of existing air conditioning units being expensive and power hungry. They also use refrigerants that are far more potent greenhouse gases than carbon dioxide — and the coolants are likely to leak out when the devices are ultimately disposed of, adding to their global warming contribution. To help address that, Chen’s approach is to use a completely different kind of chemical refrigerant that has no greenhouse impact.

Christoph Reinhart, the Terri and Alan Spoon Professor of Architecture and Climate who leads MIT’s Sustainable Design Lab (SDL), championed the seed fund effort and served as faculty lead. “The term ‘critical cooling’ stems from a collaboration between SDL and Harvard’s Human Rights Entrepreneurs Clinic,” he says. “It is motivated by the fact that climate change increasingly causes heat fatalities, primarily among vulnerable populations, who lack access to active cooling. The impact that MIT can have by ‘cooling people, not spaces’ is enormous.” This vision led to the creation of the grant program, where each of the teams received funding for six months to see what they could do and explore really innovative approaches to the problem.

In collaboration with the Abdul Latif Jameel Poverty Action Lab (J-PAL), led on J-PAL’s side by Senior Policy Manager Andre Zollinger, the teams started with a workshop that brought together representatives from the World Bank, leaders from the Global South and industry, and engineers with ideas to suggest.

All of the teams made progress and most produced initial prototypes, says Liana Frey, a managing director at the MIT Climate Project, and an effort will be made to further develop and fund these ideas. “We’re continuing to look at different ways of proceeding with the work.”

One of these ways is through air conditioning. Worldwide, air conditioning is only available to about 8 percent of people — and that amount already contributes between 3 and 4 percent of global warming emissions — explains Chen. Meanwhile, the need for air conditioning and other ways of addressing extreme heat is steadily growing as the planet steadily warms up, and many of the people who will be most affected live in regions with limited access to reliable or affordable power and with high levels of poverty. The market for air conditioners is expected to triple or quadruple in coming years, he says, and their contribution to global warming will grow accordingly.

Chen says that he already had some ideas, but he hadn’t had a chance to test them out in experiments, which the grant enabled him to do. After building three prototypes and testing them out, he says, “I’m not at the stage where I can say that I know this will work.” But based on the experiments, he’d like to proceed to build a further prototype. If it works as well as expected, it would make a dramatic difference in air conditioning technology worldwide, including for the intensive cooling needs of new data centers.

Meanwhile, Varanasi’s way of looking at the problem was to consider individuals, not spaces. His devices work through the same principle as how an elephant uses its huge ears to dissipate heat and cool its blood.

The wearable device only consumes about 33 watts, he says, whereas a typical room air conditioner consumes around 1,000 watts. At U.S. material prices, the prototype device would cost about $20, he says, but if sourced with local material in India, he estimates it could be produced at a cost of less than $1 each.

Such garments could be bought in large quantities by the government and distributed to communities, where local entrepreneurs could set up charging stations to recharge the devices after a night’s wear, and other locals could set up businesses to manufacture the systems. The socks themselves would be washable, separately from the cooling material itself. This could enable people to at least get a good night’s sleep even in the extreme heat, he says.

The proof of concept he built used a simulated foot containing a heater, and measured the cooling effect. “We were able to keep it in the zone that we need for the body to stay cool,” he says. “So our initial prototype that we were able to build with this funding showed that this can become a viable solution.”

The same material could be used in other ways, such as to make sleeping bags with built-in cooling, he says. The raw material is widely available, but would be treated in a way that they developed. “It was a fundamental science bottleneck that we were able to overcome, which makes it possible.”

Varanasi says he is exploring various possibilities for how to develop his novel cooling material into a commercial product. “Ultimately, to make anything work, it has to be a business, otherwise good ideas can die,” he says. “It has to be a good business and a sustainable business.”

Luckily, there’s still support for advancing this work. “There are a lot of people interested in this heat-stress question,” says Frey. “It’s just becoming more and more urgent.”

A number of MIT affiliates were recently honored for their research by the Breakthrough Prize Foundation.

Stuart H. Orkin ’67 shared a Breakthrough Prize in Life Sciences with Swee Lay Thein for their research transforming sickle cell disease and beta-thalassemia from incurable to treatable conditions through gene editing therapy. Their work identified the master switch controlling fetal hemoglobin, leading directly to the development of Casgevy – the first CRISPR-based medicine approved for any disease. Orkin, a graduate of the MIT Department of Biology, is currently a professor of pediatrics at Harvard Medical School.

Shu-Heng Shao, assistant professor of physics at MIT and a researcher in the MIT Center for Theoretical Physics — a Leinweber Institute, was recognized with a 2026 New Horizons in Physics Prize. Shao shared the honor with Clay Córdova from the University of Chicago, Thomas Dumitrescu from the University of California at Los Angeles, and Yifan Wang PhD ’16 from New York University. The four were recognized for “discover[ing] and develop[ing] the theory of ‘generalized symmetries’ in quantum field theory.” 

J. Colin Hill ’08 shared a New Horizons in Physics Prize with Dillon Brout, Mathew Madhavacheril, Maria Vincenzi, Daniel Scolnic, and W. L. Kimmy Wu for their results measuring the expansion and composition of the universe, with Hill’s focus on advancing analyses of data from the cosmic microwave background radiation left over from the Big Bang.

Hong Wang PhD ’19 received a New Horizons in Mathematics Prize for resolving or making advances on a family of notoriously difficult problems in harmonic analysis, a branch of mathematics that studies functions by decomposing them into fundamental components. 

In addition, Bryan Traynor, a former student in the Harvard-MIT Program in Health Sciences and Technology, shared a Breakthrough Prize in Life Sciences with Rosa Rademakers for discovering the most common genetic cause of both amyotrophic lateral sclerosis and frontotemporal dementia.

Founded by a group of Silicon Valley entrepreneurs, the Breakthrough Prizes recognize the world’s top scientists in life sciences, fundamental physics, and mathematics. The laureates were honored at a gala ceremony in Los Angeles on April 18.

A supermassive black hole lies at the heart of every galaxy, including the Milky Way. When a black hole is active, it pulls material in as a whirpool of high-temperature gas and dust. As this cosmic material piles up and falls onto a black hole, it lights up its vicinity, radiating a huge amount of energy. 

The most energetic supermassive black holes are known as quasars, and they are some of the most active and luminous objects in the universe. These voracious systems take in so much material that the energy they emit can outshine all the light in the surrounding galaxy. The pattern of light from a quasar can give scientists clues to how active supermassive black holes shape the galaxies around them. 

Now astronomers at MIT and elsewhere have detected a quasar flickering from the very early universe. The scientists traced the light from the quasar back to the “cosmic dawn,” just 850 million years after the Big Bang. The discovery represents the earliest flickering quasar detected to date. 

“Although there have been a lot of quasars found in the cosmic dawn, this is the first time we actually see one flickering,” says Gene Leung, a postdoc in the MIT Kavli Institute for Astrophysics and Space Research. 

The quasar’s flicker enabled the researchers to determine that, surprisingly, the ancient quasar’s whirpool of gas and dust, known as an accretion disk, resembled a flat pancake, similar in shape to that of more modern-day quasars. 

Their findings add to a longstanding mystery in cosmology: Why do supermassive black holes exist so early in the universe’s history? Physicists have assumed that a flat accretion disk reflects a relatively mature black hole that is in a calm and stable state. Black holes that are just starting to form, like those in the very early universe, should be more unsettled systems, with accretion disks that appear more puffy and chaotic. 

The flat accretion disk around this very early quasar heightens the mystery of how supermassive black holes can grow and mature in a very short amount of cosmic time. 

“I think what this suggests is that  all the messy, very rapid growth phases that we expect all black holes to go through at some point happen very, very early on, before we see them as these very bright luminous quasars,” says Anna-Christina Eilers, assistant professor of physics at MIT. “That’s the picture that’s emerging.”

Eilers, Leung, and their colleagues report their results in a paper appearing today in Nature Astronomy. Their co-authors include members of MIT Kavli and multiple other institutions. 

Past a pinprick

A supermassive black hole can be billions of times more massive than the sun. These gravitational giants are the central “engines” of most galaxies, helping to regulate a galaxy’s star formation and growth. 

“Without supermassive black holes, no galaxy would look the way it does today,” Eilers says. “Black holes play a major role in shaping how galactic ecosystems look.”

It was long assumed that it should take more than a billion years for the first galaxies to settle and mature, so scientists didn’t expect to see supermassive black holes in the very early universe. But observations since the early 2000s showed otherwise. Scientists have spotted more than 200 supermassive black holes in the universe’s first billion years. Such objects were detectable because they were in an extremely active quasar phase, giving off enormous blasts of radiation that could be seen from Earth, 13 billion light years away. 

These earliest quasars were observed as pinpricks of light, which signal the existence of a supermassive black hole at early times. But from these bright and distant dots, scientists aren’t able to tell much more about the black holes and their cosmic dawn environments. To do so, they need to catch a quasar’s “flicker.”

“People have known that quasars in the nearby universe can flicker,” Leung says. “The flickering comes from fluctuations in the way the gas is being fed into the black hole. And how a quasar flickers tells us something about the structure of a black hole’s accretion disk, and the kind of ‘bites’ that the black hole is eating.”

Mapping a flicker

Leung and Eilers looked to detect a flickering quasar from the early universe in hopes of learning more about the shape and structure of the earliest supermassive black holes. To do so would be a technical challenge: The further back in time and space an object is, the more distorted its light appears. This effect is due to the expanding universe, which effectively stretches, or “redshifts” light to redder, longer wavelengths. The same stretching occurs in time: Any flicker that naturally occurs over several weeks, for instance, would appear stretched out, flickering only every few months when seen from billions of light years away. 

To spot a flickering quasar from the cosmic dawn, the team needed to observe the distant universe at redder wavelengths, and specifically within the infrared spectrum, and over long timescales of many years. 

“This was the technical challenge we had to overcome,” Eilers says. “We needed data at longer, infrared wavelengths taken repeatedly over very long timescales.” 

The team ultimately found a flicker in data collected by NASA’s Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) mission — a space-based infrared telescope that scanned the entire sky over a total of about 14 years. Former MIT postdoc Kishalay De, who is now a faculty member at Columbia University, had launched a project to re-process archival data from NEOWISE. Based on the re-processed data, the team unearthed a signal, from just 850 million years after the Big Bang, which was confirmed to be the earliest flickering quasar. 

“We saw the quasar flickering randomly over the 14-year period, much like a candle’s flame flickers without a fixed pattern,” Leung notes. 

They estimate that the quasar is as bright as 12 trillion suns, and it is flickering by about 20 percent, meaning that it fluctuates up and down, by a brightness of about 2 trillion suns. 

The researchers also tracked how the quasar’s light flickered over several different wavelengths. The wavelength of light reflects a certain temperature of the material that is emitting the light. The closer material is to a black hole, the hotter it is. Researchers can therefore use wavelengths of light to map the shape and structure of material within the accretion disk around a black hole. 

Using NEOWISE data, the team analyzed the quasar’s flicker to determine the shape of the accretion disk surrounding the central supermassive black hole. They found that the disk is surprisingly thin and flat — a structure that astronomers mostly see around nearby, older black holes, that have had much longer to settle and mature. 

“This provides direct evidence that the same feeding processes and structures observed in the nearby universe were already in place at very early times, despite very different cosmic environments, which had never been seen before,” Eilers says. 

“This means something happened even earlier on that led to these systems to look so mature,” Leung adds. 

The team hopes to peer even further back in cosmic time to catch a quasar’s earlier, premature development. Then, scientists can start to piece together the conditions that brewed up the first supermassive black holes. 

This research was supported, in part, by NASA.