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Scene at MIT: A nanoscientist graduates with her very good boy

Vinny, an unofficial member of the Strano Lab at MIT, dressed up to celebrate Commencement alongside his human, Michelle Quien PhD ’26.

“I’m originally from Moorestown, New Jersey, a suburb of Philadelphia. While my degree is in chemical engineering, I consider myself a materials scientist, and I’m passionate about using innovative materials to propel next-generation technologies. When I started my bachelor’s degree at Cornell University, I was introduced to polymers and nanotechnology and even got to partake in some meaningful industry experiences in the medical device field. While the work I did felt impactful, I felt like I lacked a sense of driving innovation, and so I decided to pursue a PhD at MIT.

My doctorate in Michael Strano’s lab has focused on a novel material at the intersection of polymers and nanomaterials. This material, called 2DPA-1, is like a combination of graphene, the strongest and most conductive material, with Kevlar, which is what makes up bulletproof vests. My thesis has been pivotal in establishing the characterization tools for this material so that future researchers can optimize its properties for different applications. Going forward, I’ve signed an offer letter with a startup that is making portable nuclear reactors for areas without stable grid electricity. I’ll work on various problems surrounding the materials that make up the reactors. 

I always knew that I wanted my dog, Vinny, to have a doctoral gown for graduation. He’s been with me throughout my entire PhD and has been a pivotal member of my research group, helping everyone by being cute and reducing their stress. I couldn’t find any specific vendors online, and I love learning crafts to make custom items (crochet, knitting, and embroidery to make my own clothes; bookbinding to make my own journals and my physical thesis; and pottery to make my own mugs and dishes), so I thought: Why not try to sew a gown for him? I watched and read a few tutorials, used the sewing machines at Metropolis, and hand-sewed the finishing touches. I’m a bit of a perfectionist and could keep working on it, but I know that Vinny looks cute regardless of what he wears. I am so delighted and grateful that Vinny was part of my ceremony. He’s been such a pivotal part of my PhD journey, and my life as a whole. I can’t imagine a finer end to my time at MIT!” 

—Michelle Quien PhD ’26, graduate of the Department of Chemical Engineering

At a spirited Commencement ceremony, the Class of 2026 is urged to “run toward the hardest problems”

Lisa Su ’90, SM ’91, PhD ’94, Advanced Micro Devices CEO, tells graduates to apply “purpose, judgment, and courage” in their lives.

After years of study and instruction, MIT’s Class of 2026 received one last piece of guidance this afternoon en route to picking up their diplomas and starting the next chapter of their lives.

“Run toward the hardest problems,” said Lisa Su ’90, SM ’91, PhD ’94, the chair and CEO of semiconductor powerhouse Advanced Micro Devices (AMD) and the featured Commencement speaker at today’s OneMIT ceremony. “Hard problems really teach you what you’re capable of.”

Su’s career as one of the world’s leading technology executives has long been intertwined with MIT. She holds three degrees in electrical engineering from the Institute, along with another distinction: Building 12, home of the MIT.nano facility, was named after her in 2022. 

A central theme of Su’s address involved learning by taking on difficult challenges. At MIT, as she put it, she acquired “not the confidence that I would always know the answer, but the confidence that even when I didn’t know the answer, I could figure it out.”

Speaking before a large and appreciative audience in MIT’s Killian Court, Su also urged MIT’s new class of graduates to lead purposeful lives, with a sense of the greater good and an eye toward addressing societal challenges. 

“The world does not just need people who know how to use powerful tools,” Su said. “It needs people who know what to use them for. People with a sense of purpose. Judgment. Courage.”

Science: Curiosity on a Mission

The OneMIT ceremony is an Institute-wide Commencement event with a featured speaker and other traditional elements. MIT’s Commencement week also includes specific ceremonies in which undergraduates, and graduate students in the Institute’s five schools and the MIT Schwarzman College of Computing, walk across stage to receive their diplomas. 

After Su spoke, MIT President Sally A. Kornbluth delivered a charge to the graduates, discussing the Institute’s core values, especially the ideas of excellence and curiosity. She also emphasized MIT’s role in making advances that benefit the nation and society at large, from medicine to energy, agriculture, and other areas of need. 

“A few of those values that will serve you wherever you go,” Kornbluth observed, while noting MIT’s commitment to “the highest standards of intellectual and creative excellence” in its work. She observed that the Institute lives this ethos, by spurning legacy admissions and “back-door” admissions for donors’ families, among other merit-based practices.

“MIT is custom-made for people whose curiosity never sleeps,” Kornbluth said, offering that “curiosity is also our intellectual rocket fuel — and that fact is enormously important for our society as a whole.”

She added: “At MIT, we know that curiosity-driven science is the path to new knowledge,” Kornbluth said. “The kind that spawns world-changing innovations. Curiosity is the force that transforms deadly cancers into treatable conditions. That turns fusion energy from a dream to a reality. That uncovers new ways to grow more food using less of every resource.”

Indeed, Kornbluth emphasized, “We like to say that science is curiosity on a mission.”

“The responsibility to work with others”

MIT students earned a total of 1,165 undergraduate and 2,817 graduate degrees this academic year. The OneMIT ceremony began with the annual alumni parade, which has come to feature graduates from the 50th anniversary class. In this case the undergraduate class of 1976 had the honors, entering with processional entry music from the Killian Court Brass Ensemble, conducted by Kenneth Amis. 

In another annual component of the OneMIT ceremony, Thea Keith-Lucas, the Chaplain to the Institute, delivered the invocation. The Chorallaries of MIT sang “The Star Spangled Banner” at the outset of the event. Near the conclusion, they sang the school song, “In praise of MIT,” and another Institute anthem, “Take Me Back to Tech.”

By tradition, speakers at the OneMIT event also included Teddy Warner, president of MIT’s Graduate Student Council, and Heba Hussein, president of the undergraduate class of 2026.

“As MIT graduates, we have the responsibility to work with others to generate, disseminate, and preserve knowledge to bear on the world’s greatest challenges,” Warner said. “We cannot solve global problems without global cooperation or with limited techniques. I implore everyone to apply the cooperative, interdisciplinary skills used every day at MIT to effect positive change in all areas of the global community.”

In her speech, Hussein reflected on the many ways her classmates supported each other during their time at MIT. “As we move forward, I urge you to continue to carry care,” Hussein said. “Care for our work, for each other, and for the people far beyond MIT whose lives are connected by what we choose to do.

Following the students’ remarks, Stephen DeFalco ’83, SM ’88, president of the MIT Alumni Association, issued a welcome to the new graduates. 

MIT: “Where I really learned to solve problems”

For her part, Su recounted that when she first came to campus, she was “pretty sure I was good at math.” Then, drawing laughs from the audience, she recalled stepping into two MIT first-year courses, 6.001 and 6.002. 

“Within about two weeks, I realized there were a lot of people at MIT who were very, very good at math,” Su said. 

She stuck with it, and, as she told the crowd today, “Along the way, I started believing in myself. … What I realize now is that MIT was teaching me something much bigger than semiconductor device physics.” Referring to MIT’s enduring motto of “mens et manus,” or “mind and hand,” Su underscored the importance of both thinking through problems and working to solve them in practical terms. 

“When I was a student, I thought it was just a motto,” Su said. “Now I think it captures exactly what makes MIT so special. MIT teaches you to think deeply. But it also teaches you to build. To test ideas. To keep going when the first experiment — or even the fifth experiment — doesn’t work. And over time, you start believing that you can solve problems that once felt impossible. I carried that feeling with me long after I left campus.”

Su’s remarks specifically credited the mentorship of MIT electrical engineer Dimitri Antoniadis, one of her PhD advisors, who today is the Ray and Maria Stata Professor Emeritus of Electrical Engineering and Computer Science and in whose lab she worked as a doctoral candidate. 

“That was where I really learned how to solve problems,” Su said. 

After receiving her PhD from MIT, Su worked at Texas Instruments; IBM; and Freescale Semiconductor. In 2012, she joined AMD, which she has helped revitalize as a global leader in the semiconductor space. In 2014, she was named president and CEO of the company. Under her guidance, AMD has both grown and diversified its products, with expanding reach in high-performance computing, among other areas. 

Su has received many awards and honors in her career, including the IEEE’s Robert Noyce Medal in 2021; she was the first woman to be awarded the honor. 

In her remarks, Su referenced the many technology advances of recent decades, and noted the potential for new changes due to artificial intelligence. Su outlined her hope that AI can “accelerate discovery in every field,” including medicine and health care, suggesting it could help assemble more information than ever in valuable ways.

“This I think is the promise of AI at its best,” Su said. “It makes each of us more capable. Medicine. Science. Energy. Climate.”

At the same time, Su observed, “Technology itself does not decide what the future looks like.” Rather, she noted, people do: “For everything AI can do, AI cannot decide which problems are worth solving. It can’t make the hard judgments when the data is not there. It can’t take responsibility for the outcome. These are actually our responsibilities. And they matter more now than ever.”

“The commitment to act ethically”

In her charge to the graduates, Kornbluth also encouraged the MIT class of 2026 to  apply their knowledge and skills in socially beneficial, responsible ways.

“I mentioned excellence and curiosity, two of MIT’s core values,” Kornbluth said. “But I hope we also hold, together, another core value: the commitment to always act ethically, with integrity, and with consideration for our fellow human beings.”

She added: “I have no doubt that … with your uncommon talent, you can do it! And if you keep that goal in sight, I know you will do great things for the world. Congratulations — and warmest best wishes to all of you for a happy life and a fulfilling career.”

Commencement address by Lisa Su ’90, SM ’91, PhD ’94

“Technology itself does not decide what the future looks like,” the chair and CEO of Advanced Micro Devices told the Class of 2026.

Below is the text of Lisa Su’s Commencement remarks, as prepared for delivery today.

Good afternoon.

President Kornbluth, Chairman Gorenberg, trustees, faculty, families, friends … and most importantly, the MIT Class of 2026.

Congratulations.

You earned this. 

Standing here feels different than I expected.

I've given a lot of talks over the years … but this one is personal. And as Murphy’s Law would have it, I somehow managed to lose my voice this week … so please bear with me if my voice sounds a little rough.

I came to MIT in the fall of 1986. My parents dropped me off at Next House. I was 17 years old. Born in Taiwan, raised in Queens … and pretty sure I was good at math.

Then I walked into 6.001 and 6.002.

Within about two weeks, I realized there were a lot of people at MIT who were very, very good at math.

I remember staring at those first problem sets thinking … man, these are super hard.

I had never really pulled all-nighters until freshman year …  it was a new experience, but it was a lot of fun doing it together with your classmates. 

MIT has this incredible way of pushing you further than you thought you could go.

You wrestled with the problem.

You blew up a circuit or two.

And then, somehow … the thing worked.

And suddenly, you realized you could build something real.

And, that’s when I started feeling like an engineer.

One of the best parts of MIT is UROP.

The opportunity, as an undergraduate, to work on real research.

That changed my life.

My first UROP was in Professor Hank Smith’s lab in Building 39 … making X-ray lithography mask blanks for a graduate student.

To be clear, at the time I had absolutely no idea what that actually meant.

But I got to put on my first bunny suit, walk into the clean room, and start building devices on little 2-inch wafers.

I learned very quickly to be careful because those wafers were delicate, and I definitely did not want to be responsible for breaking them.

I ran a bunch of experiments. Most of them didn’t work the way we expected. So, we adjusted. And tried again.

It was the coolest thing ever.

For the first time, I wasn’t just learning about technology in a classroom. I was part of a team trying to discover something new.

I remember thinking: wow, we can build things this small?

Things tiny enough to fit on a die the size of a coin … but powerful enough to change the world.

And that is when I fell in love with semiconductors.

Later, I had the privilege of working with Professor Dimitri Antoniadis, who became my PhD advisor.

That was where I really learned how to solve problems.

I remember spending weeks in the clean room fabricating devices, then bringing my wafers up to the test lab, only to discover they didn’t behave the way I expected at all.

So, I’d go back to Dimitri’s office, and we’d figure out what experiment we should try next.

Looking back, that was probably where I grew the most at MIT.

Because little by little, I went from a new grad student learning about the field…to someone doing original research and actually contributing something new to the field. 

And along the way, I started believing in myself.

Not the confidence that I would always know the answer.

But the confidence that even when I didn’t know the answer yet…I could figure it out. 

What I realize now is that MIT was teaching me something much bigger than semiconductor physics.

Mens et manus.

Mind and hand.

When I was a student, I thought it was just a motto.

Now I think it captures exactly what makes MIT special.

MIT teaches you to think deeply.

But it also teaches you to build.

To test ideas.

To keep going when the first experiment — or even the fifth experiment — doesn’t work.

And over time, you start believing you can solve problems that once felt impossible.

I carried that feeling with me long after I left campus.

When I joined IBM, I found myself starting all over again.

IBM had hundreds of thousands of employees. I was 25 years old wondering how I could possibly make a difference in a company that big.

But I learned something important very quickly: engineering doesn’t care how old you are.

It cares whether your ideas work.

And one of my mentors told me something that I’ve never forgotten:   

Run toward the hardest problems.

At the time, I didn’t fully understand what that meant. 

But over time, I realized this was the best advice I ever received.

Hard problems teach you what you're capable of. 

Fast forward a bit … 12 years ago, I got a chance to put that lesson to the test.

I had the opportunity to become CEO of AMD.

AMD had enormous potential, but the company had been through some tough years.

Some of my mentors thought taking the job was risky.

But for me, this was my dream job.

This was what I’d been training for all those years.

The opportunity to work at the bleeding edge of technology on problems that really mattered.

The first thing we had to figure out was what we wanted to be when we grew up.

We made a long-term bet that high-performance computing would be the most important technology of the future.

We gave our talented team the room to think big. 

Over the next several years, we built technology to enable the most powerful computers in the world.

And, through all of it, I used every skill that MIT ever taught me … And then some. 

I call it the engineer’s instinct. 

The ability to face what seemed like an unsolvable problem, break it down, and methodically work through it step by step.

But, at AMD, I learned something else. 

The engineer’s instinct is even more powerful when it becomes shared by a team. 

And the greatest satisfaction of my career has been bringing people together to do something more than any of us thought was possible.

Which brings me to today.

Over the last few decades, we’ve experienced several major technology shifts.

The internet changed how we communicate.

Mobile computing changed how we live.

Cloud computing changed how we work.

And now we are at the beginning of the AI wave.

To me, AI is different from those earlier technology waves. 

It is not just a tool that can help us do things faster. It is deeper than that. 

It has the potential to accelerate discovery in every field and help us solve problems we have never been able to solve before.

To make it personal, one of the areas that excites me most is medicine and healthcare. 

We’ve all experienced firsthand what it feels like when someone you love is sick.

And even with incredible doctors and the best care, you realize how hard it is for any one person to bring together all of the knowledge that exists in the world to help in that critical time of need. 

AI can help us change that. 

It can help doctors and researchers bring the world’s best expertise to each patient … and deliver care with the best chance of a successful outcome.

That is the promise of AI at its best.

It does not replace people.

It makes each of us more capable.

Medicine. 

Science. 

Energy. 

Climate. 

We may discover more in the next ten years than we have in the last thirty.

Now let me be clear. 

Technology itself does not decide what the future looks like. 

People do.

For all the promise of AI …

AI cannot decide which problems are worth solving.

It cannot make the hard judgment calls with imperfect information.

It cannot take responsibility for the outcome.

These are our responsibilities.

And they matter more now than ever. 

That is why this is such an extraordinary moment to graduate from MIT.

Because the world does not just need people who know how to use powerful tools.

It needs people who know what to use them for.

People with a sense of purpose. 

Judgment.

Courage. 

People who look at a hard problem and say: I know this is important, and we can figure this out.

And that is exactly who you have become here. 

So here is what I want to leave you with.

I am fortunate in many ways.

I am fortunate to have great parents.

I received an extraordinary education.

I have had the chance to work with great people.

But I also believe I’ve been very lucky in my career.

When people ask me for career advice, I often tell them: work hard … but also understand that luck matters.

And, over time, I’ve come to believe that the best people find ways to make their luck.

Luck is not just being in the right place at the right time.

It is taking the risk to work on something hard. 

It is challenging yourself.

Choosing problems at the edge of what you know.

Surrounding yourself with people who make you better.

And believing that, yes … you can change the world.

So be ambitious about the problems you choose.

Run toward the hardest ones.

And trust your engineer’s instinct.

That is how you make your luck. 

I want to take a moment to acknowledge all the families and loved ones here in the audience today.

None of these graduates got here alone.

Thank you for believing in them, supporting them, and helping them reach this moment. 

This achievement belongs to you too. 

And to the Class of 2026…

Remember … somewhere in the years ahead, you’re going to walk into another room where you have absolutely no idea what you’re doing.

You’ve done this before.

Go figure it out.

As one MITer to another … I am incredibly honored to be here with you today.

Congratulations, Class of 2026.

New laboratory at MIT aims to advance quantum research for the nation

The Quantum Systems Laboratory will catalyze quantum innovation and be open to government, academic, and industry researchers.

On May 28, MIT President Sally Kornbluth and Massachusetts Governor Maura Healey announced plans for a new laboratory to accelerate the development of next-generation quantum technologies that will enable Massachusetts to remain a national hub for quantum innovation.

Speaking at the Samberg Conference Center on campus, the leaders introduced the Quantum Systems Laboratory (QSL) at MIT, a shared-use facility that will catalyze quantum development in the region and help keep America at the forefront of a technology seen as critical for a range of industries.

“Quantum technologies have the potential to drive transformative change in fields from computing, security, and navigation to health sciences, defense technologies, and space exploration,” Kornbluth said. “Greater Boston has the greatest concentration of quantum talent of anywhere in the world, so it has been clear to us for some time that if we could magnify all of that talent with the right facilities — a shared quantum toolbox — we could establish Massachusetts as a national hub for quantum innovation and help catalyze the next generation of quantum technologies.”

The Quantum Systems Laboratory will join a state-of-the-art quantum computer with the components needed to make it a scalable, practical technology for solving complex, real-world problems. Such components include peripheral hardware such as sensors and quantum interconnects, which are physical channels that transfer quantum information. Located at MIT’s Building 39, the facilities will be open to researchers both from and beyond MIT. 

Thanks to a $25 million investment from the state, announced today, which will match a portion of the federal funding for quantum research already underway at MIT, the Institute is now in a position to move forward as early as this summer with construction on the QSL facility. The Commonwealth’s investment adds to MIT’s own financial commitment, as well as generous philanthropic support from Thomas Tull.

“This is good news for MIT, good news for Massachusetts, and frankly, good news for the world that we’re working together to make this happen,” Healey said. “The return on investment is clear: We know the Quantum Systems Laboratory will be a first-of-its-kind center for the shared study and development of quantum science and technology. It’s going to unleash the great power of scientists and innovators from around the state and across the world, and also be a place for collaboration, both for academic and commercial ventures. It will offer incredible opportunities for both scientific progress and economic growth. It’s a testament to MIT’s unrelenting, unyielding belief in the power of openness and collaboration to advance science.”

The new lab will be the physical home for the MIT Quantum Initiative (or QMIT) announced by President Kornbluth in December. It also complements advanced facilities already used for quantum research at MIT, such as MIT.nano and MIT Lincoln Laboratory’s SQUILL foundry, both of which share the mission of democratizing access to world-class facilities. SQUILL and MIT.nano have already made a major impact on the quantum industry through research, startups, and new standards for creating and transmitting quantum information.

“I want to emphasize that just as MIT.nano is a facility for all, there will be many people from beyond MIT that come to use this equipment” at QSL, Kornbluth said. “This is a hub to make Massachusetts the center of the world for quantum. These resources are rare enough that we have to make sure they are available to our colleagues at the University of Massachusetts, Harvard, and beyond. Our plan is to mobilize all the talent in the area through this facility.”

Leading in quantum innovation is important for the prosperity and security of the country, but quantum research requires meticulously controlled environments. The new facilities will give scientists access to the cutting-edge quantum hardware and specialized experimental capabilities needed to achieve the full transformative potential of quantum science and engineering.

The new laboratory’s underlying mission is to return broad scientific, workforce, and economic benefit to the public.

For example, quantum technologies provide significant opportunities in the fields of life sciences and defense technologies, which are $50-billion contributors to the local economy, with dozens of startups working in the area. The new lab is designed to create new job opportunities in the form of academic research, startups, and more. Construction on the QSL facility alone is anticipated to create over 150 full-time, on-site jobs, plus another 75 to 100 jobs across the Commonwealth in supply chain and professional services supporting the project.

Startups from MIT are also a key driver of the region’s entrepreneurial ecosystem; in 2015, Sloan Professors Edward Roberts and Fiona Murray published a report detailing how the Institute’s alumni entrepreneurs have created more than 30,000 active companies, employing 4.6 million people and generating annual global revenues of $1.9 trillion, a figure greater than the gross domestic product (GDP) of the world’s 10th-largest economy, as of 2014. The QSL facility will provide the necessary equipment and facilities for startups working on quantum technologies, thereby strengthening the region’s innovation economy. 

Sally Kornbluth’s charge to the Class of 2026

MIT’s president asked graduates help the world understand the importance of curiosity — “our intellectual rocket fuel” — to society as a whole.

Below is the text of President Sally Kornbluth’s Commencement remarks, as prepared for delivery today.

Technically, as MIT’s president, it’s now my job to deliver a “charge” to the graduates. 

But this year, I faced that assignment with a serious case of humility. You’re entering a world that I’m certain you’ll navigate better than I could.

So, for your “charge,” I decided to draw on a special resource: the collective wisdom of our alumni.

I talk with a lot of MIT graduates — around the world, across the country, on our faculty.

They each put it their own way. But nearly all of them talk about how MIT changed their lives. It wasn’t a subject they studied, or a skill they acquired. It was the whole MIT experience! Of living and working here, together, and of belonging to a community with our distinctive passions and values.

So, as you go out into the world, I want to emphasize a few of those values that will serve you wherever you go. The banners in Lobby 7 feature our whole MIT Values Statement.  Let’s focus first on the two words at the top: Excellence and Curiosity.

Now, “excellence” is an easy thing to say. Most companies claim it. Probably every university too. But I have never seen a community live its commitment to excellence the way it’s done at MIT.

It’s easy to measure in the outward accomplishments of our faculty and graduates: the prizes, the discoveries, the inventions. The architecture and the industries. The companies and cures. 

But you also feel it here, every day — when everyone you meet in the hallway wants to tell you about what they’re working on – and it just blows you away. 

As members of this community, we strive to hold ourselves to “the highest standards of intellectual and creative excellence.” Just as important, we inspire each other to reach for those standards too!

(As one timely metaphor: This week 400 of you apparently felt that earning a degree from MIT wasn’t hard enough – so you also had to jump out of a plane!)

As an institution, we support these standards of individual excellence with a systematic focus on merit. For instance: No legacy admissions. No back-door admissions for donors. 
Because we value “potential over pedigree.”

A long-ago colleague had a sign in his office. It said, “If you take a lick of the lollipop of mediocrity, you will suck forever.” 

Now, let me be clear — I’m talking about self-discipline, not self-regard.

In the work we do, a conscious commitment to excellence is not the same as arrogance. 

In fact, it’s kind of the opposite.

The American poet Walt Whitman captured this idea. As he wrote, 

“I like the scientific spirit — the holding off, the being sure, but not too sure, the willingness to surrender ideas when the evidence is against them: This … keeps the way beyond open [and] … gives the whole man a chance to try over again.”

So I hope, wherever your life and work lead you, that you’ll strive to sustain our MIT standards of excellence. 

And I also hope, in the spirit of Whitman, that you’ll “accept the risk of failing as a rung on the ladder of growth.” Because, in all the fields you’ve studied, the willingness to try, and fail, and try again is the golden path to breakthroughs!

Now, for curiosity.

A few months ago, I was interviewed by a journalist who understands the current challenges for higher education. 

He described me as “inexplicably ebullient.”

(He doesn’t see me every day!) 

But honestly, if I’m ebullient in leading this community, it’s entirely explicable! 

MIT is custom-made for people whose curiosity never sleeps. Which describes our faculty, our staff, our alumni — and every one of you.

Feeding that curiosity is an incredible source of pleasure. You don’t need me to encourage you in this life-long feast!

But I do hope I can count on you to help the world understand that curiosity is also our intellectual rocket fuel — and that this fact is enormously important for our society as a whole.

At MIT, we know that curiosity-driven science is the path to new knowledge – the kind that spawns world-changing innovations. 

Curiosity is the force that transforms deadly cancers into treatable conditions, that turns fusion energy from a dream to a reality, that uncovers new ways to grow more food using less of every resource. 

We like to say that science is curiosity on a mission.

But we also know that the “curious” path to those deep discoveries can look like a wandering road.
 
(Years ago, after a long conversation about my PhD work, my own grandmother once asked, “Wait, you’re not trying to cure cancer in humans, you’re trying to give it to chickens?”)

Luckily, over eight decades, the United States had the foresight to see the value of discovery science. It invested public money with steady patience, knowing that the “practical payoff” could be 20, 30, 40 years away. 

Today – as many of you know from experience in your own labs — US investment in curiosity-driven science is in sharp decline. 

The tragedy here is that shrinking the pipeline of basic discovery research means choking off the flow of future solutions, innovations and cures – and shrinking the supply of future scientists.

So I hope you will join in a great shared effort to sustain the work of scientific curiosity — on a mission to serve.

A final thought: Every one of you here possesses uncommon talent. And with great talent comes great responsibility. 

I have no doubt that, like our alumni, you will be top-flight performers in your fields: Innovators. Engineers. Scientists. Doctors and designers. Entrepreneurs, investors and astronauts. Pioneers in whatever realm you chose. 

I mentioned Excellence and Curiosity, two of MIT's core values. 

But I hope we also hold, together, another core value — the commitment to always act ethically, with integrity, and with consideration for our fellow human beings. 

After more than six decades on Earth, I know that living up to this standard requires constant reinforcement and awareness! You will face many temptations, and opportunities to lose focus on that north star. 

And you simply have to resist. 

I have no doubt that, with your uncommon talent, you can do it!

And if you keep that goal in sight, I know you will do great things for the world. 

Congratulations — and warmest best wishes to you for a happy life and fulfilling career!

MIT researchers develop a low-cost technique to get lithium out of rocks

The low-temperature process could unlock cleaner lithium from America’s abundant hard rock while minimizing waste.

Demand for lithium has surged in recent years as lithium-ion batteries power increasingly more of our world. And yet, even as places like the U.S., Europe, and Australia have abundant lithium resources within their borders, China dominates global lithium refining. The biggest hurdle to tapping into the U.S. and Australia’s lithium is getting it out of hard rock minerals in a form that is useful.

Extracting lithium from hard rock today is an energy- and waste-intensive process that is often far more expensive than getting lithium from brine water, which also has major environmental drawbacks. Currently, lithium hard rock extraction involves baking the rock at over 1,000 Celsius and chemically leaching it to extract lithium. The rest of the rock is discarded.

Now, a team of researchers from MIT and elsewhere has developed a low-temperature process for extracting battery-grade lithium from the most common type of lithium-bearing mineral. The process uses a liquid reagent to dissolve the rock into the useful forms of its constituent parts: not just battery-ready lithium salts, but also smelter-grade alumina and cement-ready silica. After the minerals are extracted, the solvent and reagent can be recovered and used again so waste levels approach zero.

The researchers estimate the closed-loop process is half the cost of traditional lithium hard rock extraction and could make it cost-competitive with extracting lithium from brine water.

A paper describing the process was published today in Science. The researchers have already begun commercializing the technology through an MIT spinout, Rock Zero.

“By 2040, we need to quadruple production of lithium globally, which amounts to hundreds of new lithium producing assets,” says author Camden Hunt, a former project manager in MIT’s Center for Electrification and Decarbonization of Industry. “Hard rock is abundant; you can find it everywhere. But most hard rock refining is done in China. Our central thesis is if you can find an easier way to crack the rock, get lithium out, and make battery-grade lithium salts, you can change the lithium market. It aligns with the recent push to onshore production of critical minerals in the U.S.”

Joining Hunt on the paper are former MIT postdoc Benjamin Mowbray; PhD candidate Kalyn Fuelling; MIT undergraduate Jacqueline Prawira; Khashayar Jafari, a former senior research scientist at the MIT green cement spinout Sublime Systems; and Yet-Ming Chiang, MIT’s Kyocera Professor of Materials Science and Engineering.

From bathrooms to batteries

The research has its roots in a bathroom renovation. About 25 years ago, as Chiang made a trip to a hardware store to look for something that would turn clear glass blocks translucent, he stumbled on a glass etching cream that works by “eating away” at the surface of the glass. The active ingredient turned out to be ammonium fluoride.

More recently, as Chiang was brainstorming ways to chemically break apart the most abundant lithium-bearing mineral, spodumene, he thought back to that etching cream. Spodumene, like glass, consists mostly of silica. Conventional chemistry-based methods for extracting metals from ores preferentially dissolve more reactive elements and leave behind a silica-enriched residue because of the strength of silicon-oxygen bonds. By designing their process to use a mixture of water and ammonium fluoride, the researchers are able to dissolve silica first, reversing the process.

The researchers showed they could dissolve spodumene rock at room temperature, which represented a breakthrough over traditional processes requiring extreme heat. But it was still only the first step to a closed-loop system that produced useful materials.

“Dissolving silica is the hard part in mining,” Mowbray says. “The next question was how do we apply it to impactful mineral processing problems?”

The mineral spodumene is mainly made up of three components: lithium, aluminum, and silica. Mowbray and Hunt, who both have their PhDs in chemistry, began exploring ways to refine those components separately after they were broken apart in the ammonium fluoride solution.

First, the researchers isolated lithium fluoride, a useful input for common electrolyte materials used in batteries. Chiang, who has founded several battery companies over his multi-decade career at MIT, next asked the research team if they could isolate lithium hydroxide and lithium carbonate, two lithium salts useful for making battery cathodes. The researchers went back to the lab and found they could make both by developing new processes, some of which involved adding carbon dioxide or sodium carbonate. Chiang tasked the research team with a similar challenge for the aluminum part of the rock, which was isolated using a high-temperature separation technique, and then silica, which was isolated by precipitation.

“First our goal was to produce these products, then there were additional steps of characterizing their purity and properties and making sure our products met the specifications for target markets,” Mowbray explains. “For the lithium salts, we identified the purity specifications for battery-grade lithium carbonate, the most widely used lithium salt. For the silica, we wanted it to be used as a cement additive, so we did cement reactivity tests and eventually created cubes of cement from it for strength testing using industrial methods. For aluminum, we targeted smelter-grade aluminum. If any product didn’t meet the target specs, you’d end up with a waste stream.”

The researchers then developed a process to reuse the ammonium fluoride and water that starts the reaction.

“We’re able to dissolve the rock with the spodumene in it, and that liberates all the elements, including the aluminum and lithium,” Chiang says. “The silica is in the solution, but on the way to making ammonium fluoride, ammonia gas also comes off. If that ammonia gas is then reapplied, it precipitates the silica again. That sequence gives us back the starting ammonium fluoride. That’s why it’s a circular process.”

The researchers successfully processed 17 different spodumene rock sources, showing its widespread applicability using rocks around the world.

“You’ve heard of nose-to-tail eating?” Chiang says. “We refer to this as nose-to-tail mining. Our researchers came to MIT to look for impactful problems to work on in sustainability. With their skill sets, it was just a matter of setting them loose on this problem. We went through all these steps, and for each one, I’d just say, ‘Can you do this next step?’ And a week or two later they’d say, ‘Okay, we’ve shown we can do that.’ That’s how this entire process got built.”

Scaling the process

Chiang further challenged his research team to evaluate the commercial feasibility of their new system.

“Once we had these core operations worked out, Yet encouraged us to do some math,” Mowbray explains. “Is there enough spodumene in the world to supply 100 terrawatt-hours of battery production? The follow up was: If you supply all the world’s batteries with this process, what are the volumes of the co-products? Do they match global commodity markets? Then we started looking at the cost of the reagents, the cost of the energy, equipment. We started gaining conviction that this could have a big impact.”

The work has special significance for Mowbray, who grew up in a historic mining town in rural British Columbia.

The researchers worked with MIT’s Technology Licensing Office to spin out their company, Rock Zero, which is now located at The Engine and scaling up the system.

“We believe this approach is the lowest-energy, lowest-cost way of getting lithium not only out of hard rock, but period,” Chiang says. “That’s what’s motivating us to scale this. It will enable the energy transition through batteries that use lithium. This was one of the goals of The Climate Project at MIT — to work on projects that, within a short number of years, could transition from the lab to commercialization and impact.”

The work was supported, in part, by the Department of Energy Advanced Research Projects Agency-Energy (ARPA-E), the MIT Climate Grant Challenges program, and the National Science Foundation. The work made use of MIT.nano facilities.

A new sensor could enable earlier detection of bladder cancer

Using a catheter coated with carbon nanotubes, researchers can detect biomarkers produced by cancer cells in the bladder.

Every year, about 85,000 Americans are diagnosed with bladder cancer. While treatment is often successful, bladder cancer has one of the highest rates of recurrence of any cancer: Following treatment, about 50 percent of patients develop tumors again within the next five years. This makes it one of the most expensive cancers for society to treat.

MIT researchers have now developed a new way to regularly monitor those patients, which could enable regrowing tumors to be detected much earlier. Using a catheter coated with specialized nanosensors, the team showed that they could detect very low levels of a protein produced by bladder cancer cells and image their location in tissue.

The researchers calculate that this sensing approach is nearly 50,000 times more sensitive than urinalysis, an approach that has been used to monitor bladder cancer in patients. In an animal study, they showed that fluorescent signals produced by the sensors can be used to pinpoint the location of the tumor within the lining of the bladder, providing a chemical image.

“It’s like a camera for molecules instead of light,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT. “If you have a billion nanosensors in an array, you can use them to make a chemical image that helps you locate their source.” 

Strano is the senior author of the study, which appears today in the journal Nature Nanotechnology. Wonjun Yim, a Schmidt Science postdoc, and Hohyung Kang, an MIT postdoc, are the lead authors of the paper. Other authors include MIT graduate student Marco Machado, undergraduate student Maeve McGinnis, and postdoc Byungha Kang.

“Chemical images”

The new detection approach is based on carbon nanotubes — hollow, nanometer-thick cylinders made of carbon that naturally fluoresce when exposed to laser light. Over the past 10 years, Strano’s lab has shown that these nanotubes can be customized to sense different molecules by coating them with “synthetic antibodies” — polymers that can be designed to interact with a specific target.

When the target analytes are present, their interaction with the synthetic antibodies causes the carbon nanotubes to shift the wavelength or change the fluorescent intensity that they produce. Strano’s lab has previously developed about two dozen different sensors that can detect different targets, including hydrogen peroxide, riboflavin, and viral proteins.

For the new study, the researchers designed a sensor that could detect a protein known as nuclear matrix protein 22 (NMP-22), which is already FDA-approved for use as a biomarker for bladder cancer. NMP-22 can be detected in urine samples, but it is often significantly diluted, degraded, and cleared after secretion. This means that tumors can only be detected once they have reached more advanced stages.

To enable earlier detection, the MIT team sought a way to deploy their sensors inside the bladder, where they could detect NMP-22 near the tumor at locally elevated concentrations. The device they designed consists of a urinary catheter coated with nanotubes that can sense NMP-22. The catheter also contains a tiny device known as a ball lens, located within the tip of the catheter. 

This lens rotates 360 degrees, emitting laser light and then absorbing the fluorescent light emitted by the nanosensors. By analyzing the color and location of these fluorescent signals, the researchers can map the location of any biomarker that is detected.

These chemical images can reveal not only whether the biomarker is present, but also the location of the cancerous cells.

“If you are scanning over a region of tissue, you would like to know not just that there is a signal indicating that a tumor is there, but also its location so that you can treat it or perform a biopsy,” Strano says. “Before an early-stage tumor breaks through the urothelium so that it’s visible, it’s under the surface but still emitting chemical signals that can be imaged. When a chemical hits the catheter, we don’t just detect its presence, but we collect a map that pinpoints its location.”

Tests in animal bladders showed that this type of detection can be 180 times more sensitive than performing a conventional urinalysis because it detects biomarkers directly where they are produced in the bladder, rather than measuring them later in dilute fluids such as urine, where their concentration is much lower. This high degree of sensitivity would allow the sensors to detect signals from a tumor as small as 16 square millimeters, the researchers say.

Earlier detection

Researchers in Strano’s lab are now working on designing a more compact version of their prototype imaging system, so that it could be used more easily at a doctor’s office. They also hope to incorporate their sensors into a type of catheter known as a cystoscope, which has a camera attached and is used to visualize tumors in the lining of the bladder. 

Currently, patients who have been treated for bladder cancer undergo cystoscopy annually, or in some cases even more often, to monitor for cancer recurrence. The new MIT diagnostics should be able to detect recurring tumors earlier than cystoscopy, making them easier to treat and cutting down on the costs of treatment and monitoring, the researchers say.

“What we’re looking for is something that could be faster and more effective. It could be used right in a doctor’s office, and it could make that screening more efficient and less invasive, with much lower cost. The goal is to be able to detect potential tumors much earlier,” Strano says. 

“This paper is exciting because it shows how diagnostics can be more effective when the sensor is brought to the individual,” says Daniel Heller, a professor of physiology and pharmacology at Weill Cornell Medicine, who was not involved in the research. “Strano and colleagues demonstrated that a carbon nanotube-based nanosensor technology can be used to monitor a cancer right where it is, improving the speed of cancer detection, and potentially enabling the improvement of cancer treatment.”

This approach could also be integrated with endoscopy to detect other types of cancer or other diseases, such as cardiovascular or gastrointestinal diseases, by swapping out the nanosensors attached to the catheter.

“The beauty of polymer chemistry is that if we understand the molecular structures of target biomarkers and the design principles of binding sites, we can develop new sensors tailored to different diseases,” Yim says. “You can imagine if these sensors were integrated onto the catheter, they could reveal invisible biomarkers that current endoscopic procedures miss, opening the door to detecting many other diseases in the future.”

The research was funded by the Bridge Project of the Koch Institute and Dana-Farber/Harvard Cancer Center, a Schmidt Science Fellowship, the MIT UROP Program, Mathworks Inc., and a National Science Foundation Graduate Research Fellowship.

Media Advisory: MIT to establish regional quantum hub

With $25 million investment from the Commonwealth of Massachusetts, MIT to build a new shared-use facility to serve as a statewide quantum toolbox.

• MIT and the Commonwealth of Massachusetts announced plans to establish the Quantum Systems Laboratory (QSL) at MIT, which will be open to researchers across the region. 
• With the new funding from the state, which will match federal funding for quantum research already underway at MIT, the Institute aims to begin construction on the QSL facility this summer. 
• The QSL will host specialized facilities that will enable Massachusetts scientists to undertake impactful work applying quantum research across practical domains, including life sciences and national defense.

Quantum technologies promise transformative changes in fields from computing, security, and navigation to health sciences, defense technologies, and space exploration. But how do we ensure Massachusetts stays on the leading edge of our nation’s coming quantum leap? Doing so is vital to the prosperity and security of our Commonwealth and country, serving to protect and advance America’s technological leadership in a world that has been upended by geopolitical rivalries.   

On Thursday, May 28, Governor Maura Healey joined President Sally Kornbluth at MIT to announce a new effort aimed at establishing Massachusetts as a national hub for quantum innovation and catalyzing next generation quantum technologies. MIT and the Commonwealth of Massachusetts announced plans to establish the Quantum Systems Laboratory (QSL) at MIT, a new shared-use facility that will serve as a quantum toolbox for the region, aimed at accelerating quantum research, innovation, and growth in this critical field.

The QSL seeks to be the first facility in the world to bring together state‑of‑the‑art quantum computers with quantum sensors and peripherals, joined by quantum interconnects (physical channels that transfer quantum information). The facility will provide researchers from MIT and other institutions hands‑on access to significant quantum hardware and specialized experimental capabilities that are necessary to achieve the full transformative potential of quantum science and engineering. 

Thanks to a $25 million investment from the state, which will match a portion of the federal funding for quantum research already underway at MIT, the Institute is now in a position to move forward as early as this summer with construction on the QSL facility, positioning the region to dominate the next generation of quantum research, according to Institute officials. The Commonwealth’s investment adds to MIT’s own financial commitment, as well as generous philanthropic support from Thomas Tull.

“Greater Boston has the greatest concentration of quantum talent anywhere in the world, working on a range of potential applications. Through the new Quantum Systems Laboratory, we will help position Massachusetts to lead the next era of quantum technologies,” says Kornbluth. “This facility will serve those at the edges of our wildest imaginations in physics and quantum computing, yes. But it will also equip the talent in our region -- and ultimately, our nation -- to push our knowledge to new limits, and new innovations.” 

The QSL will be located at Building 39 on the MIT campus and will serve as a multi-disciplinary quantum hub with modern experimental infrastructure. Because quantum research involves the creation and study of coherent phenomena in systems that are isolated from the rest of the universe, it must take place in a highly controlled environment. Work is already underway in Building 39, with significant investments by MIT, to upgrade the physical infrastructure for these unique demands. The state’s support will supercharge this work and allow for the transformation of the lab into a hub for scientists across the region working on next-generation quantum technologies, startup applications, defense and health tech, and more. 

“Our region has unparalleled strengths in science-intensive innovations and tough tech breakthroughs that combine engineering, science, and computing,” notes Anantha Chandrakasan, MIT’s provost. “With the new Quantum Systems Laboratory, we aim to arm Massachusetts with the compute power and integrated platforms needed to lead the coming era of quantum technologies.”

By the numbers 

The QSL will host specialized facilities that will enable Massachusetts scientists to undertake impactful work applying quantum research across practical domains. As a shared-use facility, the QSL is being developed with the underlying mission of returning broad scientific, workforce, and economic benefit to the public. 

For example, quantum technologies provide significant opportunities in the fields of life sciences and defense technologies, which are $50 billion contributors to the Massachusetts economy, with dozens of startups working in the area. During a time of increased economic anxiety and labor market concerns, investing in foundational quantum facilities will infuse our region with new job opportunities, in academic research institutions, startups and more. Construction on the QSL facility alone is anticipated to create over 150 full-time, on-site construction jobs, plus another 75 to 100 jobs across the Commonwealth in supply chain and professional services supporting the project. 

Startups from MIT are also a key driver of the state’s entrepreneurial ecosystem; in 2015, Sloan Professors Edward Roberts and Fiona Murray published a report detailing how the Institute’s alumni entrepreneurs have created more than 30,000 active companies, employing 4.6 million people, and generating annual global revenues of $1.9 trillion, a figure greater than the gross domestic product (GDP) of the world’s 10th-largest economy, as of 2014. The QSL facility will provide the necessary equipment and facilities for startups working on quantum technologies, thereby strengthening the region’s innovation economy. 

“The new QSL will introduce modern experimental infrastructure to quantum research at MIT and beyond, allowing us to scale experiments and expand into critical domains in disciplines such as biology and chemistry, where we see enormous innovative potential,” explains Ian Waitz, MIT’s vice president for research. “As the new physical home of the MIT Quantum Initiative (or QMIT), the QSL will serve not only as an on-campus incubator, but more broadly, a regional hub to catalyze quantum innovation, growth, and investment in this critical R&D sector for the Commonwealth.” 

One floor of the facility will allow for development of radio-frequency (RF) electronics for controlling and interfacing with quantum systems. The QSL will also support researchers in the creation of customized quantum experiments with advanced high-frequency packages, which are required to protect quantum data in real-world applications. The facility will also develop the associated THz electronics needed by advanced quantum systems. 

A history of future-focused plays

Nearly a decade ago, MIT made a similarly big bet on nanotechnology, developing MIT.nano — a state-of-the-art, shared-use facility with more than 200 tools and instruments that support nanoscale discovery and innovation through imaging, fabrication, characterization, and prototyping. Set in the heart of campus in the Lisa T. Su Building, MIT.nano is home to a thriving research community, an industry consortium, and a startup accelerator. More than a fifth of the 1,500 users of MIT.nano come from outside of MIT, and half of the companies in its START.nano accelerator have had non-MIT founders.

The QSL will also complement the capabilities of MIT Lincoln Laboratory’s SQUILL Foundry, a quantum fabrication hub for superconducting qubit systems that serves researchers across Massachusetts and the nation free of charge.

MIT Corporation elects 10 term members, two life members for 2026

The term members will each serve five years on MIT’s board of trustees.

The MIT Corporation — the Institute’s board of trustees — has elected 10 full-term members, who will serve five-year terms, and two life members. Corporation Chair Mark P. Gorenberg ’76 announced the election results today.

The full-term members are: Kate A. Bergeron, Elizabeth Choe, Kevin B. Churchwell, Stephen P. DeFalco, Bennett W. Golub, Pearl S. Huang, Steve Isakowitz, Adrianna C. Ma, Pamela Melroy, and Alex Morcos. The life members are Eran Broshy and Ray A. Rothrock. Gorenberg was also re-elected as Corporation chair.

David L. Fung ’85, the 2026-2027 president of the Association of Alumni and Alumnae of MIT, will also join the Corporation as an ex officio member. He succeeds Stephen P. DeFalco ’83, SM ’88.

As of July 1, 2026, the Corporation will consist of 75 distinguished leaders in education, science, engineering, and industry. Of those, 22 are life members and eight are ex officio. An additional 33 individuals are life members emeritus.

The 10 new term members are:

Kate A. Bergeron ’93, MBA ’13, vice president of hardware engineering at Apple, Inc.

Bergeron joined Apple in 2002 as a senior mechanical engineer and has served as vice president of hardware engineering since 2014. Previously, she was senior director for ecosystem products and technologies and senior director of Macintosh product design. Bergeron co-developed the course MIT D-Lab: Design for Scale, which she co-taught from 2013 to 2017. Earlier in her career, she worked as a mechanical engineer at EM Designs and at the Palo Alto Design Group (now Flextronics International Ltd.). She has regularly been named by Business Insider as one of the most powerful female engineers in the world and was elected to the National Academy of Engineers in 2022.

Elizabeth Choe ’13, PhD ’25, director of AI strategy for translational medicine at AstraZeneca 

At AstraZeneca, Choe oversees the deployment of biomedical deep-learning models for cancer drug development and leads upskilling programs for biologists and clinicians. As an MIT PhD student, she worked on brain cancer therapies at the Koch Institute for Integrative Cancer Research. Between her undergraduate and graduate studies, she worked in digital media in several roles: leading MIT+K12 Videos, producing media for National Geographic and the National Institutes of Health, designing global online teacher training programs at the MIT Media Lab’s Learning Initiative, and serving as assistant director of communications in the Office of Undergraduate Admissions. Throughout her graduate studies, she was actively involved in campus leadership, serving as a graduate resident advisor and participating in the Graduate Student Council, the Presidential Search Committee, and other groups.

Kevin B. Churchwell ’83, CEO of Boston Children’s Hospital

At Boston Children’s Hospital, Churchwell leads an organization dedicated to advancing child health through clinical care, research and innovation, medical education, and community engagement. Since joining the hospital in 2013 as chief operating officer and executive vice president of health affairs, he led a transformation that significantly reduced safety events affecting patients and employees. Earlier, Churchwell served as CEO of Nemours/Alfred I. duPont Hospital for Children in Wilmington and CEO and executive director of Monroe Carell Jr. Children’s Hospital at Vanderbilt University Medical Center in Nashville. He is currently a professor of pediatric anesthesia and the Robert and Dana Smith Professor of Anesthesia at Harvard Medical School.

Stephen P. DeFalco ’83, SM ’88, executive chair of Creation Technologies

Before assuming his current role, DeFalco served as chairman and CEO at Creation Technologies, an electronics manufacturing services provider, for six years. Prior to that, he was a partner at Lindsay Goldberg Private Equity, following a role as president and CEO of Crane Currency. DeFalco has also held CEO roles at MDS, a global life sciences company; Senseonics, a diabetes care company, where he is still chairman; and PathoGenetix. He was also president of PerkinElmer Instruments, a strategy consultant at McKinsey and Company, and a product development leader at IBM.

Bennett W. Golub ’79, SM ’82, PhD ’84, co-founder of and senior advisor at BlackRock

In 1988, Golub was one of eight people to start the global asset management company BlackRock, Inc; he stepped down from his day-to-day activities in 2022 to assume a part-time role of senior policy advisor. Formerly, he served as chief risk officer with responsibilities that included investment, counterparty, technology, and operational risk, and he chaired BlackRock’s Enterprise Risk Management Committee. Beginning in 1995, he was co-head and founder of BlackRock Solutions, the company’s risk advisory business. He also served as the acting CEO of Trepp, LLC. and as vice president at The First Boston Corporation (now Credit Suisse).

Pearl S. Huang ’80, CEO and president of Dunad Therapeutics, Inc.

Huang has decades of experience spanning the biotech and pharmaceutical industries, with oversight across early drug discovery and development, translational research, and alliance management. Prior to Dunad, she was CEO and president of Cygnal Therapeutics, founded by Flagship Pioneering, where she was also a venture partner. Earlier, she held leadership roles as senior vice president of therapeutic modalities at Roche; vice president and global head of discovery partnerships with academia at GSK; and vice president, oncology franchise integrator, at Merck. She was also a founder and acting chief scientific officer of Beigene. 

Steve Isakowitz ’83, SM ’84, former CEO and president of the Aerospace Corporation

Throughout his career, Isakowitz has worked across the public and private sectors to advance U.S. leadership in space. At the Aerospace Corporation, he led a strategic transformation of the organization to address the rapid commercialization of the space sector, the emergence of space as a warfighting domain, and the need for faster, more agile technical execution. Before that, he held leadership positions as chief technology officer at Virgin Galactic, and later president of the company’s space ventures business; chief financial officer at the U.S. Department of Energy; and deputy associate administrator for exploration at NASA. He also served in roles at the Central Intelligence Agency and the White House Office of Management and Budget. 

Adrianna C. Ma ’95, MEng ’96, operating partner at Index Ventures

At Index Ventures, Ma oversees operations, facilitates the investment process, and is responsible for fundraising and capital partnering. Previously, she was a managing partner of the investment firm the Fremont Group, a managing director of General Atlantic, and a technology mergers and acquisitions banker at Morgan Stanley. At the Fremont Group, she oversaw a portfolio of actively managed funds, public securities, and private co-investments; chaired the investment committee; and assisted with Fremont’s direct private equity investments. During her 10 years at General Atlantic, she led investments in, and served on the boards of, growth-stage technology companies around the world. At Morgan Stanley, she focused on technology-related mergers and acquisitions.

Pamela Melroy SM ’84, president and managing partner of Melroy and Hollett Technology Partners

As deputy administrator of NASA, Melroy was responsible for laying the agency’s vision and representing NASA to the executive office of the president and others. Before retiring from the U.S. Air Force in 2007, she logged more than 6,000 flight hours as a co-pilot, aircraft commander, instructor pilot, and test pilot. She is a veteran of Operation Desert Shield/Desert Storm and Operation Just Cause. As a NASA astronaut, Melroy served as pilot on two space shuttle missions and was the mission commander on a third. She later took on a number of leadership roles, including at Lockheed Martin, the U.S. Federal Aviation Administration, the U.S. Defense Advanced Research Projects Agency, and Nova Systems, and as an advisor to the Australian Space Agency.

Alex Morcos ’97, ’98, MEng ’98, co-founder of Chaincode Labs

Morcos co-founded Hudson River Trading in 2002, where he spent 10 years helping to build the quantitative trading firm. In 2014, he and fellow co-founder Suhas Daftuar started Chaincode Labs, a research and development center for Bitcoin, with a focus on open-source software and education. Recently, he applied his interest in emerging technologies to help found Fulcrum Science, a public good initiative to use AI to accelerate scientific research.

The two new life members are:

Brighter MRI signals

New MRI sensors developed at MIT sensitively detect target molecules in the brain and body.

When doctors and scientists want to see inside a body, magnetic resonance imaging (MRI) is a powerful tool. MRI can noninvasively capture detailed images of the body’s muscles, organs, and bones. It can monitor blood flow to generate a map of brain activity. And with new sensors developed by bioengineers at MIT, MRI can track the kinds of molecules that make our brains and bodies work.

In the May 13 issue of the journal Nature Biomedical Engineering, a team led by Alan Jasanoff, the Eugene McDermott Professor in the Brain Sciences and Human Behavior at MIT, reports on their new sensors, which can brighten or dim MRI signals in response to specific molecular targets. The probes are designed to amplify the effect that each target molecule has on MRI signal, dramatically improving sensitivity over previous small-molecule sensors. Jasanoff, who is also an associate investigator at the McGovern Institute for Brain Research, says the approach his team used should enable the development of MRI sensors that detect neurotransmitters and other important molecules in the brain.

“We want to be able to measure distinct chemical signals like neurotransmitters, neuropeptides, and metabolites as they fluctuate across the whole brain,” Jasanoff says. “These chemicals are important ingredients in neural computations, and we want to use the types of probes that we developed to detect these signals dynamically.”

Jasanoff explains that researchers have struggled to use MRI to sensitively detect small molecules in the brain because the amount of any given neurochemical is low. Sensors can be designed to change the brightness of an MRI signal in the presence of specific molecules — but it takes a lot of contrast agent to achieve this. If every molecule of contrast agent needs its own target molecule to activate it, low concentrations of the target molecule limit the sensors’ visibility in an MRI scan. “The signal change that you see in the imaging will be very modest,” Jasanoff says. “It won’t let us detect physiological events.”

The Jasanoff team’s new sensors, whose development was led by postdoc Sayani Das and graduate student Jacob Cyert Simon, overcome this problem. To generate a greater signal change in response to target molecules, the researchers designed probes in which a single target molecule impacts not one contrast agent, but many.

To achieve this, Das and Simon packaged an MRI contrast agent inside tiny sacs called liposomal nanoparticles. Each nanoparticle is packed with many molecules of gadolinium, a magnetic material that brightens the MRI signal that arises from hydrogen atoms in water. Inside their protective sacs, gadolinium has no effect on MRI signal, unless water molecules can easily get in and out.

Das and Simon built water channels into the walls of their gadolinium-filled nanoparticles, engineering them so that their opening depends on the presence or absence of a target molecule. When the channels open, more water enters and the gadolinium brightens the local MRI signal, lighting up that spot in a scan.

The researchers call their target-responsive sensors liposomal nanoparticle reporters, or LisNRs (pronounced “listeners”). They designed LisNRs that let water in only in the presence of their target molecule. The water channels in these nanoparticles stay blocked until they encounter their target, which can knock aside a channel-blocking bit of protein. 

Once the channel blocker is displaced, water enters and MRI signal brightens. They also made LisNRs that dim the MRI signal in the presence of the molecule they are designed to detect. These have a channel that stays open until the target molecule comes along and blocks it, keeping water out. Jasanoff lab members Vinay Sharma, Samira Abozeid, and Gregory Thiabaud played key roles in understanding and optimizing these interactions, and collaborators in the laboratory of Masayuki Inoue at the University of Tokyo helped the group engineer channels with higher potency.

In experiments led by postdoc Miranda Dawson, Jasanoff’s team used their LisNRs to detect a molecule called biotin in the brains and bodies of living rats, illustrating the probe’s amplifying effects. “We showed that we could detect micromolar-scale levels of biotin with about tenfold greater sensitivity than we would have if we’d used a more conventional, one-to-one type sensing approach,” Jasanoff says. He adds that the team’s modeling suggests that with further development, they may be able to achieve even greater sensitivity gains.

The group showed that the new sensors can be delivered systemically, reaching various organs and spreading throughout the brain. This makes them promising tools for brain-wide imaging, as well as imaging targets in the peripheral nervous system or other tissues.

A next step will be engineering LisNRs that respond to the specific neurochemicals that Jasanoff and his team hope to study. “There are something like 100 neurochemicals in the brain that we’d love to detect, in principle,” he says. They’ll start with dopamine and glutamate — two important and relatively abundant molecules that mediate communications between neurons.

This research, including support for postdoctoral fellows and graduate students involved in the work, was funded, in part, by Lore Harp McGovern, the Yang Tan Collective at MIT, the K. Lisa Yang Brain-Body Center at MIT, the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, and the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT.

Place-based pathways to a viable future

Living Climate Futures Symposium explores climate challenges and solutions at the community level.

Aiming to transition away from fossil fuels and avert the worst consequences of climate change, world leaders aspire to achieve net zero global greenhouse gas emissions by 2050 and cap global warming at 1.5 degrees Celsius. But actions to meet such targets and minimize adverse impacts on lives, livelihoods, and infrastructure are not one-size-fits-all; they will require different approaches in different places. 

To better understand the patchwork causes and effects of the climate crisis and elements of viable solutions to it, researchers in MIT’s Living Climate Futures (LCF) initiative — 20 MIT faculty and affiliates from across the Institute — collaborate with frontline communities in diverse physical and socioeconomic landscapes around the world. 

Funded by the MIT Human Insight Collaborative (MITHIC) and based at the MIT School of Humanities, Arts and Social Sciences (SHASS), LCF is a multi-disciplinary research hub and community of practice; focuses on how climate change impacts people’s everyday lives; and creates knowledge and research collaborations with community organizations. 

At MIT on April 23-25 — just after Earth Day — LCF showcased several of these collaborations at its second Living Climate Futures Symposium, which brought together community environmental organizations with MIT researchers and students to explore how climate change challenges and responses to them are playing out in locations from New England to Mongolia. 

“Across the next two days, we’ll have conversations about community-based work and scholarly research that’s aimed at understanding the structural causes and social effects of climate change as it’s experienced in people’s everyday lives,” said MIT professor of anthropology and MITHIC faculty co-lead Heather Paxson in remarks at the start of the first full day of the conference. “I’m really excited for this symposium, and for where Living Climate Futures can go from here.”

Resisting environmental harm: Confronting data centers

A session on data centers, energy concerns, and community health in Greene County in Western Pennsylvania highlighted how stakeholders are attempting to proactively avert long-term threats to the environment and public health in and beyond their neighborhoods. Nicholas Hood, senior organizer at the Center for Coalfield Justice (CCJ), which has worked to improve policy and regulations on fossil fuel extraction and use in the region since 1994, described local environmental and health impacts of these activities, including fracking, which has increased water pollution, asthma, and lymphoma. “We have coal mines, these old oil wells, and fracking on top of that, and now we’re going to add data centers,” he said. “So, ask yourself, do you think we want that?”

CCJ community advocate Jason Capello noted that market forces compel data center developers to build as cheaply as possible in places where they believe the population is unlikely to raise concerns about adverse environmental and health impacts. These impacts include pollution from on-site water-based cooling systems, diesel generators and mini-power plants that run on natural gas, and fine particulate matter-linked illnesses such as childhood asthma, heart attacks, stroke, and lung disease. But in a subsequent presentation, Livia Garofalo, a cultural and medical anthropologist on Data and Society’s Trustworthy Infrastructures team in Philadelphia, showed that many communities have pushed back against data center project proposals. “Through protests, canvassing, petitions, and public hearings, communities have been able to resist and even stop data center projects,” she said. 

To help communities resist or limit the impact of proposed data center projects, Michael Cork, a postdoc in biostatistics at the Harvard T.H. Chan School of Public Health, described a tool he has developed to estimate emissions, model how pollution would spread, estimate who will be exposed, and assess likely health and economic impacts. To further explore how communities can respond to such projects, MIT associate professor of anthropology Amy Moran-Thomas and Stanford University postdoc Anjuli Jain Figueroa facilitated an educational game conceived by Northeastern University associate professor of sociology and health science Sara Wylie. 

The game helped teach participants how often-overlooked community stakeholders can negotiate community benefit agreements (CBAs), or plans that specify project developers’ commitments to address their concerns and provide local improvements such as jobs and affordable housing. Gathered around several tables, symposium participants worked together to identify potential pros, cons, and trade-offs of allowing a data center to be built in a fictitious community. Offering another avenue for community advocacy, Moran-Thomas also moderated a workshop led by public anthropologist Ieva Jusionyte on how to write op-eds that inspire change.

Repairing environmental harm: More than a matter of money

A session on global perspectives and methodologies for potential climate reparations focused on the context for and definition of the term. Veronica Coptis, senior advisor at Taproot Earth, a U.S.-based nongovernmental organization, described her view of climate justice as a movement about reducing not only excessive greenhouse gas emissions, but also changing the systems that have produced them, all while building a world where everyone can live, rest, and thrive in the places they love. “[Taproot Earth’s] mission is building power and cultivating solutions with frontline communities to advance climate justice through Black liberation, Indigenous sovereignty, and democracy,” said Coptis.

Eliane Lakam, global policy and partnerships specialist at Taproot Earth, described a two-decades-long process, sparked by Hurricane Katrina’s devastation of marginalized communities on the U.S. Gulf Coast, that led to a Global Climate Reparations Working Statement at the Global Climate Reparations Governance Assembly of 200 climate leaders in Nairobi, Kenya, in 2024.

Urban agriculture: Reclaiming and revitalizing degraded land

A session on advancing urban agriculture in a changing climate featured a panel of four organizational representatives of various growing spaces in Greater Boston, many of which were formerly vacant lots and garbage dumps that were repurposed as farms and gardens. The panel included Sabrina Pilet-Jones, urban farm manager at Haley House; Cecilia Del Cid, director of food justice and youth programs at GreenRoots; Olivia Golden, urban agriculture educator at UMass Extension; and Matthew Ellison, assistant farm manager at the Urban Farming Institute. 

The panelists showed how their efforts to grow food locally in an urban setting are challenging past and ongoing environmental inequality in myriad ways. These include preserving and expanding green spaces, increasing access to fresh produce, empowering their communities to become actively engaged in how their food is grown, building community connection and pride, and inspiring young people to grow food in their neighborhoods. They framed their organizations’ youth education programs as gateways for enabling the transfer of knowledge from elders to young people, promoting a strong work ethic and healthy lifestyles, and identifying pathways to livelihoods that address food access and sustainability. To provide participants with an opportunity to learn about urban agriculture and do some volunteer farm labor, the symposium offered a field trip to The Food Project in Roxbury. 

Rural and urban adaptation: Responding to a changing climate

A session on climate change as a place-based phenomenon explored how communities are responding to a changing climate on Mongolian grasslands, in the greater Southwestern United States, and along the Boston Harbor. 

Munkh-Erdene Gantulga, a PhD candidate in geography at the School of Geography and the Environment at the University of Oxford, described his studies at the National University of Mongolia on how pastoralists at two field sites are protecting their livelihoods as more-frequent severe weather events increase livestock mortality and pasture degradation. Perceiving climate change as a lack of rainfall, hotter temperatures, and inadequate grass growth, herders at the two sites are either migrating to greener pastures or applying three strategies: not milking their animals so as to boost survival of mothers and their offspring; selling off parts of their herds; or specializing in more climate-resilient animals, such as camels. A separate screening of the film “If Only I Could Hibernate” dramatized the environmental and economic obstacles faced by youth in Mongolia. 

Breanna Lameman, an Indigenous data sovereignty doctoral scholar and graduate research associate at the University of Arizona, and Nekai Eversole, wildlife biologist and program lead with Climate Change Program - Navajo Nation Department of Fish and Wildlife, described how traditional Diné ecological knowledge and innovative technologies are helping Navajo Nation communities to adapt to hotter temperatures, long droughts, and harsher soil conditions. Lameman cited Diné concepts of restoring balance and maintaining kinship with the natural world as essential to the local response. “This reminds us that the plants, animals, water, and soils are relatives, not resources, and that we all need to work together,” she said. “Watching the stars, observing the winds, the plant cycles, and animal behaviors, really helps us predict seasonal shifts better than any app out there.” Eversole noted that this mindset is combined with innovative technologies ranging from hydroponics to wetland restoration structures. A separate screening of the film “Climate Voices” and Q&A with director Leslie Jonas, MLK Jr. Visiting Scholar and Elder Eel Clan member of the Mashpee Wampanoag Tribe, explored perspectives from Native experts and climate scientists working on the front lines.

Elisa Guerrero, community engagement manager at the Stone Living Lab and Sustainable Solutions Lab at the University of Massachusetts Boston, highlighted two examples of adaptation measures to protect vulnerable Boston Harbor infrastructure from sea-level rise, coastal storms, and storm surges: testing seawalls designed to mimic natural habitat for how well they slow down wave action and preserve marine biodiversity, and monitoring salt marshes to better understand the factors that degrade and promote their health. A separate Stone Living Lab tour enabled symposium participants to visit a living seawall, nature-based flood protection infrastructures, and a community-based flood sensor project as Boston tries to address rising sea levels.

Training the next generation in community-oriented research

In addition to highlighting LCF’s role as a research hub linking MIT researchers and students with community organizations in the United States and around the world, the symposium also sought to draw attention to efforts to train the next generation in this approach. The Saturday session “Experiential Learning, ‘Anthro-Engineering,’ and Learning to Do Community-Oriented Research” showcased some of the interdisciplinary classes that LCF supports. MIT students who participated in these classes engaged in activities ranging from building chicken coops with a Boston farming collective while learning about urban agriculture to exploring how to decarbonize the steel industry in Pittsburgh and Southeast Chicago while creating well-paying green jobs to spending time in Ulaanbaatar’s ger districts (informal residential areas) while working with Mongolian collaborators on non-coal methods for heating homes. 

Student panelists shared highlights from their learning experiences through presentations, activities, artwork, and written accounts from their travel notebooks.

“People have always been part of why I chose to study engineering,” said nuclear engineering PhD student Alina Jugan. “But learning how to integrate a human perspective, and one that accounts for multitudes of realities, is essential. The first step in making a solution is learning what the real problem is and how people experience it. This is what ‘Anthro-Engineering’ teaches us.”

Panel and symposium co-organizer Laura Frye-Levine, a research scientist at the MIT Anthropology Section and affiliate of the MIT Center for Sustainability Science and Strategy, concurred. “In building relationships in place-based contexts, the students on this panel demonstrate the value of engaging with social and cultural expertise in addressing climate change,” she said. “These projects are fantastic examples of collaborations that hold promise for MIT’s approach to developing climate solutions.”

Lessons in resilience from frontline community groups 

In a session entitled “Xa xah Xechnging: A Sacred Obligation in a Time of Climate Chaos,” panelists from Se’Si’Le and Children of the Setting Sun Productions — two Indigenous-led environmental organizations from the U.S Pacific Northwest that have collaborated with LCF on experiential learning activities — described how they draw upon cultural, spiritual, scientific, legal, and other resources in their efforts to heal and restore the planet amid political and corporate opposition. At the core of their work is a perspective in which everything has a spirit, and is thus worthy of love, honor, respect, dignity, pride, and compassion.

Sundance chief Rueben George, a board member of Se’Si’Le, recounted how this perspective energized the campaign he led against the development of the Trans Mountain Pipeline, a fossil fuel megaproject on Tsleil-Waututh Nation territories in British Columbia. “We just shared facts about what it is, and we led with our culture,” said George, who is also chair of Salish Elements, an Indigenous-run company that produces green hydrogen. “That’s the biggest, most important thing, is we always led with our culture.”

At an earlier session, representatives of organizations that participated in the 2022 Living Climate Futures symposium, ranging from GreenRoots to Se’Si’Le, said that they draw strength from the wisdom of ancestors, a growth mindset, and communal bonds among people who seek a better future for the places they call home. Kurt Russo, co-executive director of Se’Si’Le, noted: “I come back to the indomitability of the human spirit.”

Additional photos can be viewed here.

Designing a career, on and off the track, at MIT

Senior Krystal Montgomery explored design courses to shape a career in web development. As a national champion in track, learning to balance athletics and academics was key to her success.

You will never catch Krystal Montgomery running to class. Literally. She is that fast.

The MIT senior — a Course 6-3 (Computer Science and Engineering) major and Course 4 (Design) minor — was recently named the New England Women’s and Men’s Athletic Conference Women’s Track Athlete of the Week — for the second time. Montgomery ran a national top 10 time in the 800 meters at the Friar Invitational in Providence, Rhode Island, in April. Her time of 2:10.67 was the fastest Division III runner in the field, ranking her eighth nationally. She beat that time with a personal best (2:09.51) at the FIRE Meet hosted by Williams College in early May. 

Montgomery also runs the 400 meters or 800 meters on the relay team; last year, she and her teammates were national champions in the 4x400m race, which helped MIT win its first NCAA Division III Outdoor National Championship. 

Her success running at MIT was hard-fought. After a stellar undergraduate first year and earning a place at the NCAA Division III finals, she suffered an injury at the NCAA Division III Indoor Championships. Unable to compete at the start of her second year, the increasing demands of her coursework and interviewing for internships took a toll.

“Sophomore year was super tough, academically,” says Montgomery. “I think the mental load affected my athletic performance. I was thinking that I would quit after my sophomore year and just focus on school. Then I started dropping times and thought that maybe I could improve if I just stuck it out.”

What Montgomery found was a new way to focus on herself that positively impacted her work on and off the track.

“It’s definitely been a journey of learning how to be more mentally tough throughout the last four years,” she says. “I think that has kind of helped both my academic and athletic performances. My junior year was great. I just kept pushing myself and continued to drop my times. I kind of learned how to balance my life. I prioritized sleeping and eating and tried not to be too stressed about schoolwork so I could lock in on race day.”

Supporting creative energy

Montgomery says she was a “pretty crafty person” before attending MIT. The former president of her high school’s chapter of Girls Who Code, she knew she was going to major in computer science. It was her love for building, making, and creating that led her to explore design courses. In her first year, Montgomery took her first design class 4.021 (Design Studio: How to Design), with Paul Pettigrew. 

“That was an amazing experience because I got to use the workshops and the labs in the architecture department,” she says. “It was just crazy to have all these materials at my fingertips that I could build with. I learned how to laser cut; spray paint; powder coat; and cut metal, wood, and fabric. I found it all really interesting, and what I made encouraged me to take more of these classes.”

Montgomery says she realized that pursuing her interest in design while majoring in computer science would allow her to foster her “creative energy” throughout her time at MIT.

In her junior year, Montgomery took class 4.031 (Design Studio: Objects and Interaction) with associate professor of the practice in architecture Marcelo Coelho. She enjoyed it so much she took another of Coelho’s courses, 4.043 (Design Studio: Interaction Intelligence) — twice.

The course provides a foundation in technical skills such as physical prototyping, coding, collecting data, and deploying neural network models. The end result is developing interactive prototypes that can be deployed and experienced by real users. Montgomery enjoyed the process of working with a new group of classmates and partnering to create a prototype in each class. 

“[Coelho’s] classes have been a great combination of designing a physical object and learning how to code, which brought in my computer science background,” says Montgomery. “It gave me the opportunity to combine both fields creatively.”

Moving forward

Montgomery says she hasn’t fully wrapped her head around the fact that her time at MIT is ending. It’s all been good: friends, clubs, courses. 

“My last two years, I chose to focus on memories instead of being stressed over a lot of things,” she says. “I feel like I chose each of the things I did intentionally, so I put my time in things that I’ll carry with me past college.”

Before Commencement, Montgomery will join her teammates in her final meet: the NCAA Division III Outdoor Track and Field Championships. At last year’s championships, Montgomery and her teammates took first place in the women’s 4x400m relay. 

After Commencement, Montgomery will move to Austin, Texas to work as a software developer at Apple, and she will keep competing in track as an unattached athlete, potentially transitioning to marathons later in her career. 

“I’ve seen a lot of post-grads from MIT continue to train and compete in track meets and perform even better than they did in college,” says Montgomery. “I don’t know when I’ll make the switch to longer-distance running. For now, the sweet spot is the 800 meters.”

Ten from MIT accept 2026 Fulbright awards

This year, over half of MIT’s Fulbright applicants won awards. The current students and alumni will embark on research projects abroad in 2026-27.

Ten MIT affiliates — including undergraduates, graduate students, and alumni — have accepted Fulbright grants to conduct research in countries across the world. Five other students declined their awards to pursue other opportunities, and another student is still deciding. In total, 16 of MIT’s 30 Fulbright applicants won awards this year. 

Funded by the U.S. Department of State with annual appropriations from Congress, the Fulbright U.S. Student Program offers year-long opportunities for American-citizen students and recent alumni to conduct independent research, pursue graduate studies, or teach English in over 140 countries. This past February, MIT was recognized by the Fulbright Program as the nation’s No. 1 “Top Producing Institution” among special focus STEM universities. 

MIT students and alumni interested in applying to the Fulbright U.S. Student Program should contact Julia Mongo, Fulbright program advisor, in the Distinguished Fellowships office in Career Advising and Professional Development.

Jessica Chomik-Morales SM ’25 earned her master’s in science writing at MIT, where she previously spent three years as a post-bac cognitive neuroscience researcher in the labs of professors Nancy Kanwisher and Laura Schulz. For her Fulbright in Spain, she will research the science of science communication at Universitat Pompeu Fabra’s Center for Brain and Cognition in Barcelona. Her project will investigate how narrative features in science writing interact with reader characteristics to shape comprehension, trust, and engagement. Chomik-Morales is the creator, host, and producer of “Mi Última Neurona,” an MIT-sponsored Spanish-language neuroscience podcast that has featured more than 60 scientists from Latin America, the United States, and Spain. She is currently producing “Lab Notes on Love,” an audio miniseries for Scientific American. She is committed to making science communication more inclusive, empirically grounded, and emotionally resonant.

Stella Gassman will graduate this month with a BS in biological engineering and a concentration in women’s and gender studies. For her Fulbright year, she will conduct microbiology research at the University of Copenhagen in Denmark. At MIT, Gassman researched the vaginal microbiome and mucosal membranes, with a particular focus on bacterial vaginosis. Important moments of her research journey included time at an MGH gynecology clinic and at the FRESH clinical trial site in South Africa, where she gained firsthand perspectives on the human context behind her laboratory samples. Gassman also interned at Pfizer Oncology, developing an in vivo tumor model to test preclinical compounds. She volunteered in the MGH Emergency Department and served on the Biological Engineering Undergraduate Board. After Fulbright, she hopes to attend medical school to bridge scientific discovery and human impact.

Chen Li SM ’25 graduated from MIT with a master’s in system design and management. She has developed generative artificial intelligence tools for patient engagement at Novo Nordisk in Copenhagen through MISTI Denmark and applied AI to help prevent gait freezing in Parkinson’s patients through the MIT–Mexico program. As a research assistant in the MIT Global Teamwork Lab, her thesis used large language models and statistical methods to build a 3D urban design platform to study teamwork behavior. She also served as a teaching assistant for data mining courses at MIT Sloan School of Management and the MicroMasters program. As a Fulbright Iceland-NSF Arctic Research Award recipient, Chen will explore how AI and systems thinking can be applied to support health and well-being in Arctic communities. She plans to pursue a PhD in information and systems science following her Fulbright experience.

Liam Moser will graduate this week with a PhD in geophysics from the Department of Earth, Atmospheric and Planetary Sciences’ MIT-WHOI Joint Program. His research has focused on understanding the structure and dynamics of subduction zones, where one tectonic plate dives beneath another, generating the Earth’s largest earthquakes and creating volcanic arcs. During his PhD, Moser helped found the annual MIT-WHOI Geophysics Retreat, promoting interconnectedness between MIT and the Woods Hole Oceanographic Institution (WHOI). He also taught incoming graduate students in the MIT-WHOI Summer Math Review for five years, organizing the review for the final two years of his PhD. Moser was awarded a Fulbright Iceland-National Science Foundation Arctic Research Award for a postdoctoral fellowship at Reykjavík University, where he will use earthquake recordings to study the structure and dynamics of the Hengill volcano and geothermal area.

Lilia Ould-Hammou is a senior majoring in mechanical engineering with a concentration in controls, robotics, and instrumentation. As a recipient of the Fulbright U.S.-Korea Presidential STEM Initiative Award, she will conduct research at Seoul National University’s Wearable Robotics Laboratory. Her work will involve advancing adaptive exosuit control for balance recovery. She plans to improve her language skills while exploring Korea’s history and culture. At MIT, Ould-Hammou has worked in the d’Arbeloff Robotics Lab on soft modular robotic straps, served as a tutor in the MIT Women’s Technology Program, and competed as a thrower on the MIT track and field team. After her Fulbright fellowship, she will pursue a master’s degree in robotics at Johns Hopkins University.

Bryan Sperry ’23 graduated from MIT with dual bachelor’s degrees in physics and mechanical engineering, focusing on renewable energy systems. Since graduating, he has worked at VEIR as a systems integration engineer, designing superconducting power transmission lines. As a Fulbright Brazil grantee, he will study pathways to improve climate resilience and energy equity in urban power grids alongside the Cenergia Lab at the Federal University of Rio de Janeiro. After Fulbright, he plans to enroll at Columbia University to complete a master’s in urban planning to continue working on urban disaster preparedness.

Sophie Thompson is a senior majoring in chemical engineering. For her Fulbright research in Sweden, she will test the performance of recycled carbon fiber composites at the Swedish School of Textiles in Boras. Thompson has researched natural fiber-reinforced composites for prosthetic socket use in low-resource environments with the Herr Lab in the MIT Media Lab, worked on immunoengineering technology at the Massachusetts General Hospital, and interned at the textile recycling startup MacroCycle Technologies. She also completed a summer research internship at the Weizmann Institute in Israel through MISTI. She serves as captain on the MIT lightweight women’s rowing team, and has held leadership roles with the MIT chapter of the American Institute of Chemical Engineers, TEDxMIT, and MIT Hillel. After Fulbright, Thompson will pursue a PhD in molecular engineering at the University of Chicago.

Claire Underwood is a senior studying chemical-biological engineering. As a recipient of a Fulbright Portugal award, she will conduct research at the University of Minho in Guimaraes, studying high-throughput fabrication techniques for cell-embedded microtissues with applications in drug discovery. At MIT, Underwood worked in the Hammond and Olsen labs exploring interactions between biology and polymeric systems. For the past two years, she has focused on lipid nanoparticle drug delivery for cancer treatment, and is excited to continue investigating biomaterials and biomimetic systems. She was also a member of the varsity volleyball team and active in her sorority Alpha Phi, Cru, and Athletes in Action. After Fulbright, she will pursue a PhD in chemical engineering at the University of Texas at Austin.

Sophie Vulpe is a senior majoring in physics and mathematics. Her Fulbright will take her to the Extreme Light Infrastructure-Nuclear Physics (ELI-NP) institute in Măgurele, Romania, where she will develop advanced data-processing algorithms for a new monoenergetic gamma ray spectrometer. She looks forward to strengthening her computational and experimental skills and connecting with her Romanian heritage. At MIT, Vulpe worked with Professor Mikhail Ivanov on characterizing black hole quasi-normal modes using tools from the mathematical field of representation theory. Passionate about expanding access to physics through education and outreach, she was co-president of the Undergraduate Women in Physics group, a mentor in the physics mentorship program, and a teaching assistant in the Experimental Study Group. She was also a member of Dancetroupe and the Musical Theater Guild. After Fulbright, Vulpe plans to pursue a PhD in physics. 

Josephine Wang will graduate this month with a BS in computer science. For her Fulbright grant to Switzerland, she will conduct research at EPFL in Lausanne with the NeuroAI Lab. Her work will explore whether brain-inspired language models can develop functionally specialized clusters analogous to cortical organization, and how targeted disruptions to those clusters affect language-related behavior. At MIT, Wang’s research has focused on computational models of cognition, movement, and human behavior. She has most recently worked in the Seethapathi Motor Control Group, where she developed a computer vision pipeline for world-grounded pose estimation in children and examined how computational models can support pediatric gait analysis. Outside of research, Wang enjoys traveling, trying new cuisines, and learning French.

Bridging real human movement with digital technology

MIT.nano Immersion Lab collaborates with Emerson College students to advance the art of virtual production.

“Avatar,” the highest-grossing film of all time, took viewers to a new world, Pandora, and it advanced filmmaking to its own new world: developing the field of virtual production. 

Leveraging a wide range of technologies such as performance capture, LED virtual environments, and advanced 3D imaging technologies, virtual production is changing the landscape of modern cinema. While millions of people have seen “Avatar,” only a fraction of that number understand the magic behind the scenes. Exposing filmmaking students to this magic is what MIT Media Lab alumnus Daniel Pillis SM ’24 is all about.

“Motion capture, like that in 'Avatar,' bridges real human movement with digital technology,” says Pillis. “In this digital age, and as artificial intelligence becomes more involved in film studios, technology that enables the authenticity of human expression and performance is becoming increasingly important.” 

That is what Pillis, now an assistant professor at Emerson College, teaches his students in his filmmaking courses. To bring the lesson to life, each semester the class travels across the river to MIT, where Emerson undergraduate and graduate students use the capabilities of the MIT.nano Immersion Lab to create their own virtual productions.

Donning full-body motion-capture suits that pair to the 28-camera OptiTrack system in the Immersion Lab, the students become their own avatars — generating virtual characters that dance, fight, or play the guitar like The Beatles. They see their animation data immediately on a computer screen and can change or add to their character’s movements in real time. Later, they take their data back to Emerson to build into short films for their final projects.

“It has been truly gratifying to support this course and to see the curiosity and ingenuity students have brought to the stage,” says Talis Reks, who manages the MIT.nano Immersion Lab. “This class highlights the range of what our lab can offer, extending well beyond research and into art and the performing arts."

The MIT.nano Immersion Lab — there’s really nothing else like it

Pillis first learned about the MIT.nano Immersion Lab during his time as a graduate student in Professor Hiroshi Ishii’s Tangible Media group at the MIT Media Lab. Working with colleague Georine Pierre SM ’24, the two collaborated on a Haitian folklore dance project, creating a motion capture-driven simulation of Haitian folkloric dance traditions, specifically the sacred Yanvalou dance. They built a living archive using the capabilities of the Immersion Lab that let participants dance with an interactive AI-driven ancestral avatar animation.

When he became faculty at Emerson, Pillis knew the Immersion Lab was a perfect fit to elevate his students’ experiences. “The level of high-end film production that the Immersion Lab supports is out of reach for so many students who would benefit from this technology in their practice,” explains Pillis. “The facility is unique, well-equipped, and even accessible to those outside of MIT — there really is nothing else like it in the Boston area.”

With the type of mechanical character animation the Immersion Lab technology allows, the final projects end up light-years beyond what these students thought they could achieve, continues Pillis. And they’re having fun. “They really get into it,” says Reks. “These students are not necessarily trained as actors, but the moment they see themselves as virtual characters, the realistic, granular movement enabled by motion capture, they get fully into performing.”

Rewarding professionalism

In the past two years, over 60 Emerson College students have used the Immersion Lab for Pillis’ class. Emerson undergraduate student Nick Forsch received an EVVY Award nomination for his project. The Emerson version of an Emmy, EVVYs are awarded to students whose projects are judged and selected by a panel of industry experts looking for creativity, quality, and professionalism.

“Being able to use the MIT.nano Immersion Lab really elevated my project,” says Forsch who created “Enter,” a short film about a human transported into a digital world to meet an artificial intelligence. “I was excited to submit it for an EVVY, knowing the technology behind my work was on a professional level.”

Another undergraduate student, Evan Costa, recently created a virtual recreation of The Beatles on “The Ed Sullivan Show,” capturing a version of each musician’s performance and reconstructing a simulation of 1950s television. Costa will be joining the MIT Learning Engineering and Practice Group, led by principal research scientist John Liu in the Department of Mechanical Engineering, this summer to continue exploring virtual production as an intern.

“Having the opportunity to gather motion-capture data within the Immersion Lab gave me more than advanced technology for my project; it provided insight into an often-unseen world of creativity,” says Costa. “Modern storytelling exists across a wide range of mediums, from film to video games, and witnessing the inner workings of this process has deepened my passion for virtual production.”

In the coming academic year, Pillis and Reks plan to leverage advanced Immersion Lab technologies to teach facial animation, hand and finger tracking, multi-modal data capture, and further advances in interactive generative motion capture as they gear up for the next set of productions.

A day in the life of MIT Sloan Fellow Alecia Asiamigbe

The MBA student and entrepreneur is learning to lead a more resilient future with her renewable energy company.

“I came to MIT Sloan intent on joining a vibrant ecosystem for entrepreneurship and leadership development,” says Alecia Asiamigbe, an MIT Sloan Fellow and MBA student in the MIT Sloan School of Management who is graduating this week.

Before coming to MIT Sloan, Asiamigbe worked as an energy and infrastructure professional with over 20 years of leadership experience, delivering complex energy infrastructure solutions.

It was MIT Sloan’s work to embed sustainability in new ventures that attracted Asiamigbe. Additionally, the MIT Sloan Fellows program gave her the opportunity to earn an MBA in one year. “I was anchored to my choice by the Disciplined Entrepreneurship framework and the potential to focus on climate and energy entrepreneurship.”

Currently, Asiamigbe is working to build out a sustainability-focused venture, Resilient Grid, a renewable energy company that aims to convert organic waste into sustainable natural gas able to produce reliable, dispatchable renewable power in fuel import-dependent markets. Its modular systems reduce reliance on imported fuels, lower energy costs, and stabilize grids where solar and wind alone are insufficient. By capturing methane, diverting waste from landfills, and producing useful byproducts, it delivers measurable impact across energy security, emissions reduction, and circular economic development.

“My work in sustainability is deeply rooted in my need to give back to the community and to be an agent for systems-level change. We must solve the dual challenge of providing access to opportunities to innovate and build for those not currently in the loop, while also stopping the damage currently being done to the planet. Knowing that we want better for our grandchildren, what will we do differently?”

The following photo gallery provides a snapshot of what a typical day for Asiamigbe has been like at MIT.

One stage at a time

Associate Professor Sara Brown, an accomplished theater set designer, teaches MIT students to create and think visually.

In a theater, the first thing the audience sees, and looks at the longest, is the stage. Even so, set design is something most of us know little about. Why does a set have its form and elements? How does it suit the performance? 

Consider a set that designer and MIT Associate Professor Sara Brown created in 2015, when the Brooklyn of Academy of Music adapted the canonical Japanese Noh play “Hagoromo,” turning it into a chamber opera with dance. 

Noh plays have a traditional structure and a crucial final transformation. In “Hagomoro,” an angel loses her cloak; a fisherman only reluctantly returns it, after the angel performs a ritual dance; the angel then ascends to the heavens. To focus on the main characters, Brown’s design featured three high walls surrounding center stage, with musicians and a chorus elevated behind them. 

“That set was a framing device more than anything else,” says Brown, who is also associate head of MIT Theater Arts within the Music and Theater Arts Section. “It lifted the musicians to a different plane, almost a heavenly place, so we have a heaven-and-Earth contrast. It allows the dancers to be seen against a plain backdrop. I didn’t want to lose their bodies in a sea of other bodies.”

For a formal play structure, then, Brown created a formal setting, with vertical layering suggestive of its contents. The trickiest part was lighting: Brown worked with the lighting designer Clifton Taylor to cut vents in the high walls for more light, while a rigging structure allowed them to spotlight dancers.

“Solving for those things is what makes the design,” Brown says. “There’s an artistic idea that underbeds everything, and there are practical considerations, which are as important, to make the piece work the way you want.”

Brown has designed sets at many major venues, tackling everything from “Carmen” to “Death of a Salesman” and debut productions. She ranges broadly across theatrical genres, while teaching classes that get MIT students thinking visually, intellectually, and creatively.

“Every play you’re working on should have something you grab onto as a creative challenge,” Brown says. That challenge is a collective one; it involves working with directors, performers, and design teams focused on lighting, sound, media, and costumes.

“In theater-making, you have to work in a community,” Brown emphasizes. “You might bump up against some rough edges, but you develop strategies to work with everybody with dignity, and that’s important.”

For her extensive work and teaching, Brown received tenure at MIT last year. 

Minnesota kind

Brown grew up in Minnesota, where her parents made sure the whole family grasped the value of humility. 

That experience, says Brown, has given her “a voice I carry with me that channels my family. The worst thing you could be where I grew up was too big for your britches. So it’s a voice that says, ‘What are you doing and what is the value of this?’ Because of my upbringing and my family, it’s a kind voice, but it is a self-reflection I try to carry with me.”

Brown received her BA from Gustavus Adolphus College in Minnesota, then earned an MFA from the University of Virginia. At MIT, she has successfully combined professional set design with classroom teaching.

When Brown agrees to design the set for a production, the first thing she does is read the work in question. Then she sits down with the director to talk about it.

“Usually I’ll talk to the director after my first read of the play,” Brown says, citing the influence of a prominent U.S. set designer, the late Skip Mercier. “He said the only thing he brings to the first meeting is a love of the play. That is a great approach. You come understanding the material, wanting to find something within it you love and are excited to work on. You’re not closed; you’re there to discover what you have in common.” 

Indeed, Brown emphasizes how much she appreciates the collaborative aspects of theater. Inevitably, directors, designers, and actors will not agree on everything, but from sorting through those varying viewpoints, a production emerges. 

“It’s about serving the whole instead of being your personal project,” Brown says. “There will always be tension, but the idea is that through that tension, something is going to result that will be better than anything you could do by yourself.”

Brown does have some creative tendencies that reappear across productions. She will often opt for simplicity and adaptability on stage. For a production of “Pride and Prejudice” in Hartford, Connecticut, Brown designed a circular space at the front of the stage, with a slightly elevated rear area containing a piano and columns, allowing the set to shift among the many social settings of the work. 

Remarkably, another set Brown designed was actually used for two different plays running at the same time: “Death of a Salesman” and “Skeleton Crew,” a 2008 play about a closing auto plant in Detroit.

“A throughline in my work is that I gravitate to things that appear to have a simplicity and integrity or formalism, and then reveal different aspects of themselves, so they change over time,” Brown says. “But there is something essential in them. I’m drawn to simplicity, something without a lot of noise.”

“Where the good stuff is”

Still, Brown is always open to new challenges. She once designed the set for the contemporary play “The Lily’s Revenge,” which has five acts and requires the audience to move around in the theater.

“You have to figure out how to reconfigure the space in many different ways with the available materials and it has to feel like a big transformation,” Brown says. “Sometimes you’re working on things and don’t understand the totality of it [the production] until you step back and see it all together.”

Much as Brown works on a variety of theater projects, she also works with a variety of MIT students, from any given course of study, in the classroom. 

“It’s everybody, which is great,” Brown says. “There are students who did high school theater and people who have never seen a play.”

While teaching classes in the theater arts program — which include classes on set design, the foundations of design, and drawing for designers — Brown has also served as a faculty advisor for MIT Morningside Academy of Design, an interdisciplinary hub for design on campus. 

“There’s an underlying process of design that does unite disciplines,” Brown says. Consider set design and architecture, for instance:

“Sometimes in theater you’re trying to make spaces that actually express an inefficiency. You’re creating obstacles for people onstage,” Brown says. By contrast, architects might be trying to get people to flow efficiently through buildings. Still, she adds, “It’s the same process, with different results.” Besides, architects do try to design common spaces, whether atriums, lounges, or meeting rooms, where people stop and interact, mirroring set design to an extent.

In any case, Brown notes, when she is working with MIT students in design classes, she is often “reversing the idea that there’s something external you’re seeking that is the right answer, which I think they’re used to doing in other realms of education.”

Instead, in theater, whether it’s Brown’s own professional work, or a first-time design for a student, she says, “This is a process where you have to mine your interior life and think about what you want to bring out in this event that’s going to happen onstage. That can be scary, but that’s where the good stuff is.”

Featured video: MIT teachings, free to the world

A new film explores how the launch of MIT OpenCourseWare 25 years ago has helped to shape how knowledge is shared.

A new short film from MIT Open Learning explores the origin, influence, and global reach of MIT OpenCourseWare, reflecting on its role in establishing MIT, in 2001, as the first higher education institution to make educational resources freely available to learners across the world.

Part of MIT Open Learning, MIT OpenCourseWare helped spark a global movement that continues to shape how knowledge is shared across the world. The film, titled “The Courage to Be Open: MIT OpenCourseWare and the Democratization of Knowledge,” captures both the vision behind this work and the lasting impact it has had on expanding access to learning at scale.

Video by MIT Open Learning | 15 minutes, 22 seconds

MIT students study plasma physics beneath Alaska’s aurora

Student-led expeditions use distributed instruments to observe auroral structures and probe space plasma in real-world conditions.

For many graduate students, waking up at noon after a 4 a.m. bedtime is a sign of a night well spent. For a group of MIT students, it was simply the start of their workday — timed not to the sun, but to the aurora.

Their goal was simple: to study plasma phenomena using the aurora borealis as a natural laboratory. The process, less so; working largely in darkness in Fairbanks, Alaska, the students conducted experiments in temperatures that dipped as low as -25 degrees Fahrenheit, using red headlamps for visibility. The sun set before 3 p.m., and even at its warmest, temperatures barely reached 20 F.

The aurora provides a rare opportunity to observe plasma behavior directly, as charged particles that interact with Earth’s magnetic field produce visible, large-scale structures in the night sky. As Fairbanks is situated beneath a region of especially frequent auroral activity, it is one of the most reliable places in the world to observe these phenomena, though the conditions come with real constraints. 

For one thing, the extreme cold directly impacted the instrumentation. “Our laptops went from full battery to nearly empty in 10 minutes because of the cold,” says Leonardo Corsaro, a PhD student in physics at the Plasma Science and Fusion Center (PSFC) at MIT. “We were trying to transfer data as fast as possible before everything shut down; it was a race against time!”

The challenges extended beyond the cold itself. “The cold can be managed,” says Leon Nichols, a PhD student in physics at PSFC. “With good planning, you can stay comfy in -20 F. The real difficulty was movement when deploying cameras far away from the roads. Walking through thick snow can burn up to 900 calories in an hour. We used cross-country skis to access some of the more remote terrain that would have taken hours to reach otherwise.”

But the conditions were more than worth it: During their time in Alaska, the group witnessed the strongest solar storm in the past two decades, bringing the aurora to life in ways few will ever experience. “It felt like we were the only ones there,” Sydney Menne, a PhD student in nuclear science and engineering, recounts, “removed from the Earth and just entirely surrounded by the aurora, fully immersed in it.” 

The team was granted access to observation facilities at Poker Flat Research Range through the University of Alaska Fairbanks Geophysical Institute. Over the course of the trip, students deployed multiple all-sky camera systems across distances of up to 100 miles, enabling simultaneous observations of auroral structures from different locations. These cameras, which capture 360-degree images of the night sky, were paired with magnetometers to correlate visual auroral features with changes in Earth’s magnetic field. 

By combining spatially distributed imaging with magnetic field measurements, the team aimed to capture how auroral structures change across space, with the long-term goal of supporting three-dimensional reconstructions of the aurora. This year’s campaign also expanded the measurements beyond imaging, using muon detectors to explore possible correlations between visual auroral activity, magnetic field changes, and particle detections, offering a potential window into how high-energy particles in the upper atmosphere relate to visible auroral activity.

Despite decades of study, many aspects of the aurora remain poorly understood, and each observation offers an opportunity to better characterize the behavior of plasma in near-Earth space. The team also observed a pulsating aurora, a relatively rare phenomenon in which strips of light stretching across the sky blink on and off multiple times per second. By combining instruments not traditionally applied to these problems and deploying low-cost systems at scale, the team is exploring new approaches to studying these phenomena. Insights from these observations can help improve our understanding of space weather, including how solar activity affects satellites, communications systems, and power infrastructure on Earth.

For some participants, the experience reshaped how they think about plasma physics itself. Corsaro explains, “In my research, it is easy to associate these phenomena with colorful plots and simulations, losing touch with the physical process. Seeing structures in the aurora, electric currents and flows forming and shifting overhead, brought a sense of reality to those concepts, and served as a reminder that real plasmas are far less neat and intuitive than theory suggests.”

The experience is part of a broader effort. This group of students represented the third iteration of the Geophysical Plasma Observation Expedition (GPOE), a project involving MIT students from the Plasma Science and Fusion Center, along with collaborating departments, that sends a cohort to Fairbanks, Alaska, each year. Faculty members now provide support for the expedition, while continuity is maintained through its student-driven structure, with each cohort including a mix of returning and new participants. The expedition is organized and led entirely by students and operates on an intensive, compressed timeline. Students are responsible not only for data collection, but also for instrument design, site selection, logistics, and post-processing, completing a full research cycle within a matter of months.

This year’s cohort included graduate students Leonardo Corsaro and Leon Nichols of PSFC; Sydney Menne of the Department of Nuclear Science and Engineering; and Noah Wolfe and Oleksandra “Sasha” Lukina of the Laser Interferometer Gravitational-Wave Observatory (LIGO) Laboratory and the MIT Kavli Institute for Astrophysics and Space Research. The group was accompanied by Professor Matthew Evans, professor of physics at MIT, who is affiliated with the LIGO Laboratory and the Kavli Institute. 

“This is an opportunity to go from concept to data analysis in just a few months,” says John Ball, a PhD student in nuclear science and engineering at PSFC. “That kind of compressed scientific cycle is rare, especially in our field.”

The program itself has relatively recent and somewhat unusual origins. It began in 2023, when graduate student Shon Mackie, frustrated by the lack of hands-on plasma diagnostic opportunities, noticed the solar cycle was approaching its peak and saw an opportunity to study plasma phenomena more directly. He drafted a short proposal to PSFC leadership, and the response from then-Director Dennis Whyte was two lines: “Sounds cool, literally! PSFC will fund this.” 

Since its launch in 2023, GPOE has evolved from a single-camera effort into a multi-instrument, multi-site campaign with growing participation, with each cohort building on the work of previous years by refining instrumentation, expanding observational coverage, and improving data collection strategies. 

This hands-on, student-driven approach has also created opportunities to extend the experience beyond MIT. In 2024, the program expanded to include a new outreach collaboration with the MIT Museum and the MIT Nord Anglia Collaboration, bringing approximately 65 high school students from around 20 schools worldwide to MIT to help design and build components of the all-sky camera systems used in the field. Working within a set of technical constraints, students developed and tested designs, ultimately producing 13 cameras that were deployed during the Alaska expedition.

The program has also begun to produce results beyond the expedition itself. Students have presented their work at major conferences, including the American Geophysical Union, and published findings in peer-reviewed journals such as Earth and Space Science. The group’s low-cost all-sky camera and magnetometer design is now being adopted by other research teams and community science initiatives, extending its impact beyond MIT.

Beyond its scientific goals, participants emphasized the broader impact of the experience. 

“Standing outside at midnight in Alaska, staring up at sheets of glowing plasma stretching thousands of kilometers across the sky, really brings home just how small and delicate our own place in the universe is,” says Ball. 

As the program continues to grow, students hope to expand both its technical capabilities and its reach, including more permanent instrumentation and expanding outreach partnerships. For many involved, the expedition represents not just a research opportunity, but a reminder of the scale and immediacy of the phenomena they study.

“Science is an adventure,” Corsaro says. “This kind of work reminds you why you became a scientist in the first place.”

MIT economist Whitney Newey awarded Erwin Plein Nemmers Prize in Economics

Newey has been a leading figure in econometric theory for more than four decades, shaping both research and training in the field.

MIT economist Whitney Newey PhD ’83, the Ford Professor of Economics, emeritus, has received the 2026 Erwin Plein Nemmers Prize in Economics.

The biennial Nemmers prizes from Northwestern University recognize top scholars for their lasting contributions to new knowledge, outstanding achievements, and the development of significant new modes of analysis.

The university cited Newey — whose research has focused on econometrics — for producing “a body of work that has shaped the field of semiparametric econometrics, guided both econometricians and empirical researchers over several decades, and helped lay the foundations for modern machine learning-based inference.”

Newey will interact with Northwestern faculty and students through programming scheduled to occur during the 2026-27 academic year. The prize also includes a $300,000 award.

“I am delighted, deeply honored, and very grateful,” says Newey of the honor. “I am thrilled to have worked on and now work on ideas and approaches that are important for modern, machine learning-based inference and modern empirical economics more generally, most of this with such capable collaborators. This prize will expedite this work.”

Newey has been a leading figure in econometric theory for more than four decades, shaping both research and training in the field. He has done pathbreaking work on variance estimation, nonparametric simultaneous equations, consumer surplus estimation with general heterogeneity, and debiased machine learning.

“My colleagues and I are thrilled to see Whitney’s incredible career recognized with this high honor,” says Jonathan Gruber, the Ford Professor of Economics and head of the Department of Economics. “His research has given birth to many of the econometric methods that are now second nature to economists, and those of us in his orbit also know him as a source of sage, comprehensive, and generous advice. Whitney symbolizes, through both his pathbreaking research and his great generosity, what has made MIT economics so great for so many years.”

Newey is a distinguished fellow of the American Economic Association, a member of the American Academy of Arts and Sciences, and a fellow of the Econometric Society. He is also a fellow of the International Association of Applied Econometrics, of CEMP at Jinan University, and an international fellow of the Centre for Microdata Methods and Practice (CEMMAP) at University College London. He earned a BA and a PhD in economics from Brigham Young University and MIT, respectively.

Newey was named a 2020 Distinguished Fellow by the American Economic Association. He has been a fellow of the Center for Advanced Study in the Behavioral Sciences and received a Sloan Foundation Research Fellowship. He has served as co-editor of Econometrica — a journal produced by the Econometric Society — and as program co-chair for the World Congress of the Econometric Society. He has also served on the Econometric Society’s Executive Committee. He previously taught economics at Princeton University and at MIT, and also previously served as the head of MIT’s Department of Economics. He has been a visiting scholar, professor, and lecturer at institutions across the world.

The rules neurons follow to make sense of what we see

Brain cells take in many signals through thousands of circuit connections. A new study discerns the rules that turn inputs into a functional arrangement for neurons that process vision.

Even in the primary visual cortex, a brain region named for its specialized role in processing basic features of what the eyes see, not every neuron ends up answering the call to process properties of visual input. Maybe that’s because each neuron receives a wide variety of inputs via thousands of circuit connections, or “synapses,” and has to opt to respond to the visual information versus something else. In a new study in mice, neuroscientists at The Picower Institute for Learning and Memory at MIT reveal how neurons that perform visual processing bring order to this input to get the job done.

Neuroscientists are keenly interested in what inputs, from among so many choices, will compel neurons to participate in the brain’s computations and functions, says senior author Mriganka Sur, Newton Professor of Neuroscience in the Picower Institute and MIT’s Department of Brain and Cognitive Sciences. Neurons ultimately participate in brain circuits by “firing” an electrical action potential.

“The configuration of inputs, the kind of organization, the assembly of neurons that modulate each other to generate an action potential is the essence of how brain circuits process information,” Sur says. “These (visual cortex) cells are a microcosm of this very profound and big picture of neuroscience.”

In the open-access study in iScience, led by postdoc Kyle Jenks, the research team achieved their findings by meticulously imaging how not only neurons’ cell bodies, but also their individual synapses, formed on protrusions known as dendritic spines, responded as mice viewed moving images. They did this imaging for not only visually responsive neurons, but also for unresponsive neurons that nevertheless have visually responsive spines. That allowed them to analyze many key properties that might influence where a particular synapse forms, and how it influences responses at the cell body.

“This pulls together a lot of things that have been looked at in isolation and looks at them in one collective paper,” Jenks says. “We can compare how the neuron and the spines on that neuron respond to the same stimuli, and we can do this for both visually responsive and unresponsive neurons.”

In visual cortex layer 2/3, Jenks and the team genetically engineered neurons such that their individual dendritic spines would glow when surges of calcium indicated increased activity by the synapses on the spines. The scientists did the same for the cell body, or “soma,” to keep track of how the cell responded and even signaled its overall responses back out to the synapses. This way, as the mice watched black and white gratings at varying angles drift by their eyes in different directions, the scientists could keep track of each spine’s and each cell’s overall response to that patterned visual input.

In all, they tracked 11 neurons that responded to the visual input and 11 others that seemingly ignored it. That enabled them to find several rules:

Distance from the soma matters: On cells that responded to visual input, the responses of individual spines were much more likely to correlate with the activity of the soma the closer the spine was to the soma. In the same vein, the soma’s signal back out to spines, which is believed to influence the spines’ alignment with the soma’s preferences, was more likely to be detectable closer to the soma than farther away. 

Local clustering: On neurons that responded to visual input, spines formed distinct little enclaves of correlated responses with each other. Specifically, spines within 5 microns (five one-millionths of a meter) acted in concert. But then, right outside that 5-micron boundary, spines were less likely than chance to join in that activity. Sur speculates that these isolated pockets of activity sharpened the response from each enclave.

“Apical” vs. “basal:” The neurons the team studied have two distinct kinds of dendrites. Apical dendrites, which are very long and protrude from the top, or “apex,” of the neuron, tend to get a wide variety of inputs from across the cortex. Basal dendrites, which are shorter and extend out from the bottom, typically get more raw visual input. While basal dendrites indeed received more visual input than apical dendrites overall, Jenks found that apical dendrites on visually responsive neurons had significantly more visually responsive spines than those on non-responsive neurons. And both types of dendrites equally obeyed the rules above about distance from the soma.

Orientation selectivity matters most: Jenks, Sur, and the team used statistical modeling to determine which of many factors (the stimulus selectivity, reliability of the response, a spine’s distance from the soma, apical versus basal, etc.) most explained how correlated a spine’s responsiveness was with that of the soma. By a wide margin, how selective a spine was to the orientation of its preferred grating was the most important single factor.

“Our results reveal that synaptic inputs to excitatory layer 2/3 neurons in mouse (visual cortex) are not randomly arranged, but organized and distributed in a manner that correlates with multiple factors including somatic responsiveness, somatic tuning, branch type, distance from the soma, local correlations, and stimulus selectivity,” the researchers wrote.

The team’s findings can help advance studies of vision in the brain in multiple ways, Jenks and Sur say. Certain genetic mutations that affect how neurons connect in circuits can affect visual cortex neurons and vision, Sur says. Documenting these rules provides researchers with a baseline to compare against when examining the effects of such mutations. Jenks adds that the findings could inform efforts to model how neurons integrate synaptic inputs in their computations.

In addition to Sur and Jenks, the paper’s other authors are Gregg Heller, Katya Tsimring, Kendyll Martin, Asrah Rizvi, and Jacque Pak Kan Ip.

The National Institutes of Health, the Simons Foundation Autism Research Initiative, and the Freedom Together Foundation provided support for the study.

MIT affiliates elected to National Academy of Sciences for 2026

Six MIT faculty, along with 10 additional alumni, are recognized by their peers for their outstanding contributions to research in the natural and social sciences.

The National Academy of Sciences (NAS) has elected 120 members and 25 international members for 2026, including six MIT faculty members and 10 additional alumni. 

Among MIT professors, Bengt Holmström, Michale Fee, Gareth McKinley ’91, Keith Nelson, Fan Wang, and Catherine Wolfram ’96 were elected in recognition of their “distinguished and continuing achievements in original research.” 

Additional alumni who were elected include Christopher J. Chang PhD ’02 (Chemistry); Cynthia J. Ebinger SM ’86, PhD ’88 (Earth, Atmospheric and Planetary Sciences); Andrew Gelman ’85, ’86 (Mathematics and Physics); Richard L. Greene ’60 (Physics); Chuan He PhD ’00 (Chemistry); Pardis C. Sabeti ’97 (Biology/Life Sciences); Robert J. Shiller SM ’68, PhD ’72 (Economics); Daniel M. Sigman PhD ’97 (EAPS); Eero Simoncelli SM ’88, PhD ’93 (Electrical Engineering and Computer Science); and Salil P. Vadhan PhD ’99 (Mathematics).

Membership in the National Academy of Sciences is one of the highest honors a scientist can receive in their career. The NAS is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — with the National Academy of Engineering and the National Academy of Medicine — provides science, engineering, and health policy advice to the federal government and other organizations.

Bengt Holmström is the Paul A. Samuelson Professor of Economics, emeritus. He received his doctoral degree from the Stanford Graduate School of Business in 1978 and held faculty positions at Northwestern University and Yale University before joining the MIT faculty in 1994 with a joint appointment in economics and management.

Holmström is best known for his foundational research on the theory of contracting and incentives, for which he received the 2016 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (together with Oliver Hart of Harvard University). His extensive contributions to contract theory as applied to the theory of the firm, corporate governance, and liquidity problems in financial crises have had wide-ranging impacts, while bringing contract theory into mainstream economic thought.

In addition to the Nobel, Holmström’s research has been recognized with the Stephen A. Ross Prize in Financial Economics and the Grand Cross of the Order of the Lion of Finland. He is a member of the American Academy of Arts and Sciences, the Econometric Society, and the American Finance Association. Holmström is also an elected foreign member of the Royal Swedish Academy of Sciences and a member of the Finnish Academy of Sciences and Letters.

Michale S. Fee is the Glen V. and Phyllis F. Dorflinger Professor of Neuroscience, head of the MIT Department of Brain and Cognitive Sciences (BCS), and investigator at the McGovern Institute for Brain Research. His research explores how the brain learns and generates complex sequential behaviors. Using the zebra finch as a model system, Fee investigates the neural mechanisms underlying birdsong — a behavior that young birds learn from their fathers through trial and error, much as human infants learn to speak through babbling. His research extends far beyond birdsong — the neural circuits controlling birdsong learning are closely related to human brain circuits disrupted in Parkinson’s and Huntington’s diseases. Insights from Fee’s research could reveal new clues to the causes and potential treatments of these complex brain disorders.

After receiving his BE with honors in engineering physics at the University of Michigan in 1985, Fee studied applied physics at Stanford University, where he carried out his PhD thesis work in the laboratory of Steven Chu. In 1992, he began working as a postdoc in David Kleinfeld’s lab in the Biological Computation Research Department at Bell Laboratories. Four years later, he became a permanent member of the technical staff at Bell Labs and began working on the mechanisms of vocal sequence generation in the songbird. In 2003, he became an investigator at the McGovern Institute and a faculty member in BCS. In 2021, he was appointed BCS department head, continuing the department’s tradition of being led by scientists whose exemplary work makes MIT a world leader in brain science. Fee is a member of the American Academy of Arts and Sciences and a recipient of multiple undergraduate and graduate teaching awards at MIT.  

Gareth H. McKinley ’91 is the School of Engineering Professor of Teaching Innovation in the Department of Mechanical Engineering at MIT, former associate head and interim head of the department, and co-founder of Cambridge Polymer Group. McKinley’s research interests include non-Newtonian fluid dynamics, microfluidics, extensional rheology, field-responsive materials, super-hydrophobicity, drag reduction, and the wetting of nanostructured surfaces. His work focuses on understanding the rheology of complex fluids such as surfactants, biomaterials, gels, and polymers, which are ubiquitous in foods and consumer products. 

McKinley has made outstanding contributions to viscoelastic fluid mechanics, understanding flow instabilities and stretching flows. His research group has developed novel instrumentation and customized rheological analysis techniques that have driven the field of rheology for complex and soft fluids. His instrumentation and testing algorithms, along with freely-distributed code for analyzing large amplitude oscillatory shear flow, and broad-band “chirp” rheometry, are used worldwide in industry and academia . 

McKinley is the author of over 390 technical publications. He has won the Publication Award of the Society of Rheology twice (2007 and 2022), as well as the 2021 Walters Award from J. Non-Newtonian Fluid Mechanics. He was awarded the Bingham Medal of The Society of Rheology in 2013, the Gold Medal from the British Society of Rheology in 2014, and the G.I. Taylor Medal from the Society for Engineering Science in 2022. In 2019, he was elected to the National Academy of Engineering and was also inducted as a fellow of the Royal Society of London. In 2023, he was awarded an honorary doctorate from the Katholieke University of Leuven, and in 2024 became a corresponding member of the Australian Academy of Sciences. In 2025, he was elected to the American Academy of Arts and Sciences and also became a foreign fellow of the Indian National Academy of Engineering.  

Keith A. Nelson, the Haslam and Dewey Professor of Chemistry, earned his BS in chemistry from Stanford University. After completing his doctoral studies in physical chemistry, also at Stanford, he conducted postdoctoral research with John P. McTague at the University of California at Los Angeles. In 1982, Nelson joined the MIT Department of Chemistry as an assistant professor.

His distinguished career has been recognized with numerous honors, including the William F. Meggers Award, the Bomem-Michelson Award, and the Frank Isakson Prize for Optical Effects in Solids. Research in the Nelson Group focuses on the time-resolved optical study and control of  collective transformations in condensed matter, using pulses of light in the THz, optical, and X-ray spectral ranges and laser-generated strain waves to drive the modes of motion through which these changes occur.

Fan Wang is a professor of Brain and Cognitive Sciences, investigator at the McGovern Institute, and co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT. She investigates the neural circuits that govern the dynamic interactions between brain and body, exploring how the brain generates sensory perceptions and controls movement. Wang uses cutting-edge techniques including optogenetics, in vivo electrophysiology, and in vivo imaging to make discoveries with profound clinical implications.

By developing innovative tools to study how brain circuits work, Wang discovered distinct populations of neurons activated by anesthesia that can suppress pain without blocking sensation, and can calm anxiety by regulating automatic body functions like heart rate. She also identified the brain circuits controlling rhythmic movements essential for exploration and communication. Together, these findings reveal how emotion, physiology, movement, and consciousness are deeply interconnected.

Before coming to MIT, Wang obtained her PhD from Columbia University working with Richard Axel, and received her postdoctoral training at the University of California at San Francisco and Stanford University with Marc Tessier-Lavigne. She became a faculty member at Duke University in 2003, where she was later appointed Morris N. Broad Professor of Neurobiology. Wang became an investigator at the McGovern Institute and a faculty member in the Department of Brain and Cognitive Sciences at MIT in 2021. She is a member of the American Academy of Arts and Sciences and a recipient of multiple undergraduate teaching and graduate mentorship awards at MIT.  

Catherine D. Wolfram ’96 is the William Barton Rogers Professor in Energy and professor of applied economics in the MIT Sloan School of Management. Before coming to MIT Sloan, Wolfram previously served as the Cora Jane Flood Professor of Business Administration at the Haas School of Business at the University of California at Berkeley. From March 2021 to October 2022, she served as the deputy assistant secretary for climate and energy economics at the U.S. Treasury, while on leave from UC Berkeley. Before leaving for government service, she was the program director of the National Bureau of Economic Research’s Environment and Energy Economics Program and a research affiliate at the Energy Institute at Haas. Before joining the faculty at UC Berkeley, she was an assistant professor of economics at Harvard University. She received a PhD in economics from MIT in 1996 and an BA from Harvard in 1989.

Wolfram has published extensively on the economics of energy markets. Her work has analyzed rural electrification programs in the developing world, energy efficiency programs in the United States, the effects of environmental regulation on energy markets, and the impact of privatization and market restructuring in the United States and United Kingdom. She is currently working on projects at the intersection of climate, energy, and trade, including work on carbon border adjustment mechanisms and oil market sanctions. Since March 2025, Wolfram has served on the COP30 President’s Council on Economics, Finance, and Climate, and has chaired a working group on climate coalitions.

MIT science writing students collaborate with The Associated Press

Students developed and pitched local climate stories, then worked with visual journalists from the AP over an intensive four-day weekend.

This spring, six reporters from The Associated Press’ climate desk traveled from cities across the United States to work with students from the MIT Graduate Program in Science Writing. Students developed and pitched local climate stories, then, over a four-day intensive weekend, worked with visual journalists from the AP to report and produce their pieces. Articles cover a broad spectrum of environmental topics, ranging from area kelp harvests that are used to produce biofuels to efforts to restore cranberry bogs in environmentally friendly ways, and include visual elements, like photography and videography.

The four collaborative pieces include:

• “How a retired cranberry bog helped change the game for wetland restoration,” by Jamie Jiang and Julia Vaz
• “Planes and ships could run on kelp someday, but there are serious hurdles,” by Zoe Beketova and Ana Georgescu
• “Massachusetts is dumping sewage into waterways. Grassroots organizations are fighting back,” by Ashley D’Souza and Lucie McCormick
• “One of America’s oldest weather observatories shows people the science behind our climate,” by Laura Martin Agudelo and Alex Megerle

“This workshop was an intense few days that offered a unique opportunity for MIT journalists to get feedback while in the field, reporting. The students brought enthusiasm and passion to the reporting, heading out before the sun came up and working long into the nights over the weekend for stories in the Boston area and beyond,” says AP’s Climate Photo Editor Alyssa Goodman, the workshop’s lead organizer. “For the AP team members who participated, it was also a rewarding opportunity, allowing us to share our passion for climate storytelling while getting to know these students, watching them build strong stories and gain experiences that will help them as they continue in journalism.”

The collaboration is unique, even among journalism programs. The Associated Press is one of the most prestigious, longest-running news wire services in existence. Nearly 4 billion people worldwide come in contact with AP journalism every day. The publication has won 59 Pulitzer Prizes, including 36 in photojournalism.

MIT student reporters say that the opportunity to directly work with journalists from the AP’s climate team and have their own stories published has been a highlight of their time in the Graduate Program in Science Writing.

“It was great to be in the field with a reporter and photographer from the AP News team, learning directly from her as the reporting unfolded,” says Zoe Beketova, whose story focused on kelp biofuels. “That kind of expertise is difficult to get in a static classroom setting, and I think my team learned a lot.”

Ana Georgescu says that the experience of working with the AP team was “like stepping into a real newsroom.” Georgescu adds that coordinating with AP editors and reporting teams in real time and under tight deadlines provided valuable on-the-ground experience.

“What made the biggest difference for me was being in the field alongside an experienced photojournalist and seeing how they read a scene in practice,” she says. “We were able to get immediate feedback on how we directed subjects, which scenes we chose, and how we integrated photography into the reporting process. That kind of hands-on, in-the-moment experience was incredibly helpful, and it’s made me really excited to keep exploring climate stories, as well as the visual side of journalism.”

Some democracies are struggling to ensure safe drinking water

Countries with developing economies provide at least some public water, but safety may lag because it’s less visible, researchers say.

About 2 billion people — just under a quarter of the world’s population — lack regular access to clean drinking water. And roughly 800,000 people annually die from illnesses associated with unsanitary water.

Drinking water access is a fundamental problem for human and economic development. The U.N., for instance, highlighted the issue in its Sustainable Development Goals of 2015, an ambitious 17-point agenda that specified safe drinking water as a basic global aim.

Past research shows that democracies, in comparison to other forms of government, tend to be more successful at delivering this kind of public good, which benefits a large portion of the population. This is likely due to accountability measures that include elections, greater transparency, and more freedom in civil society.

But now a study led by an MIT professor shows that across nearly 100 countries with developing economies, that dynamic has become more complex in the 21st century. While democracies are slightly ahead of non-democracies when it comes to providing at least some water, they have been falling behind when it comes to ensuring that there is safe water on tap. 

“Among low- and middle-income countries, which have not done as well economically, we found there wasn’t really a big difference between democracies and non-democracies in the provision of what is called basic drinking water,” says MIT political scientist Evan Lieberman, co-author of a new paper detailing the results. “But for safe drinking water, we found, surprisingly, that democratic countries were becoming less good at extending access.” 

While the study does not pinpoint the precise reasons for this, it suggests a lens for viewing the problem. Democracies tend to be better at delivering visible public goods, the kinds of things citizens can literally see — like infrastructure that delivers water. But the difference between safe and unsafe water is not necessarily visible and obvious, so public officials may not be as responsive.

“This is likely a big part of the equation, that the invisibility of safe water makes it a less compelling public good for politicians,” says Lieberman, the Total Professor of Political Science and Contemporary Africa, and director of MIT’s Center for International Studies.

The paper, “Beyond the tap: The limited value of democracy for delivering universal safe water access in low- and middle-income countries,” is published in the journal World Development. The authors are Lieberman, and Naomi Tilles, a doctoral student in political science at Stanford University.

Seeing is believing

To conduct the study, the scholars analyzed drinking water data recorded by the World Health Organization/UNICEF Joint Monitoring Programme. That provides information for basic availability to water, defined as access to an improved water source with no more than 30 minutes of collection time; and access to safe drinking water, defined as an improved water source that is available on premises, available when needed, and free from potentially disease-producing contaminants, which range from fecal matter to harmful chemicals.

Examining 96 low- and middle-income countries, the researchers looked at a variety of measures pertaining to its democratic or non-democratic features, and ran 39,000 regressions to see how the form of government related to its provision of water. Overall, Lieberman and Tilles found that democratic governance is modestly associated with an increase in the basic availability of water, compared to non-democracies. However, the effect is not particularly robust.

The good news is that between 2000 and 2024, 81 of the 90 countries with data available in both years made gains in safe drinking water access. However, democratic countries have been less successful than their non-democratic counterparts in advancing the goal of achieving universal access. 

“Moreover, the gap between democracies and non-democracies seems to be getting a little bit larger over time,” Lieberman observes. 

Because the study is focused on establishing the overall empirical situation, the scholars do not claim to have determined why this trend has been emerging. Many newer democracies have struggled to establish high-functioning governance in some regions, which may influence their overall results. 

More broadly, Lieberman suggests, visibility matters. Past scholarship has shown that democracies perform relatively well in delivering visible public goods, especially in countries with little information in the public sphere. Delivering water generates attention for politicians in a way that keeping water safe does not. 

“Politicians may figure out they should do things citizens like, to stay in office, such as bringing water to an area,” Lieberman says. “You can have a ribbon-cutting ceremony, and people feel it really happened. But water quality is often invisible.

It’s a more difficult challenge to ensure safe water: You have to do testing, prevent people from polluting, and you may need to treat the water.”

In any case, Lieberman notes, “Given what we find, what is clear is that the incentives are not aligned under the current systems for advancing safe-water access within all democracies. That provides opportunities for human agency to create incentives for citizens, nongovernment agencies, and governments to do what is needed.” 

Development for all

Lieberman comes to the topic of water access as an expert on African politics. His most recent book, “Until We Have Won Our Liberty” (Princeton University Press, 2022), examines the vicissitudes of South African democracy. In the book and in general, he suggests that democracy is the most viable path toward development with “dignity,” meaning economic growth accompanied by liberties and equal treatment under the law. 

“I think democracy provides dignified development, by granting people recognition and participation, and that’s an extremely valuable thing,” Lieberman says.

Still, when it comes to the performance of many countries with regard to safe water, he says, “I think we just need to be clear-eyed about real problems.”

In some countries, he suggests, the time horizon of elected officials may also be relatively short-term, and they may be more oriented toward simpler problems than water safety. At the same time, other members of society need to find ways to make water safety a bigger issue in the eyes of the public. 

“There are important lessons for democracies to learn, and citizens in civil society who are aware of this challenge need to figure out ways to get people to care about it, to recognize the connection between illness and unsafe water, and to use political campaigns to advance their longer-term interests,” Lieberman says.

Overall, he adds, “There is something intrinsically important about democratic government. Then the question becomes how to make it work better to deliver really important outcomes like safe water.”

Technology usually creates jobs for young, skilled workers. Will AI do the same?

A new study of the postwar U.S. shows which kinds of workers historically filled new tech-enabled jobs.

At any given time, technology does two things to employment: It replaces traditional jobs, and it creates new lines of work. Machines replace farmers, but enable, say, aeronautical engineers to exist. So, if tech creates new jobs, who gets them? How well do they pay? How long do new jobs remain new, before they become just another common task any worker can do?

A new study of U.S. employment led by MIT labor economist David Autor sheds light on all these matters. In the postwar U.S., as Autor and his colleagues show in granular detail, new forms of work have tended to benefit college graduates under 30 more than anyone else. 

“We had never before seen exactly who is doing new work,” Autor says. “It’s done more by young and educated people, in urban settings.” 

The study also contains a powerful large-scale insight: A lot of innovation-based new work is driven by demand. Government-backed expansion of research and manufacturing in the 1940s, in response to World War II, accounted for a huge amount of new work, and new forms of expertise. 

“This says that wherever we make new investments, we end up getting new specializations,” Autor says. “If you create a large-scale activity, there’s always going to be an opportunity for new specialized knowledge that’s relevant for it. We thought that was exciting to see.” 

The paper, “What Makes New Work Different from More Work?” is forthcoming in the Annual Review of Economics. The authors are Autor; Caroline Chin, a doctoral student in MIT’s Department of Economics; Anna M. Salomons, a professor at Tilburg University’s Department of Economics and Utrecht University’s School of Economics; and Bryan Seegmiller PhD ’22, an assistant professor at Northwestern University’s Kellogg School of Management.

And yes, learning about new work, and the kinds of workers who obtain it, might be relevant to the spread of artificial intelligence — although, in Autor’s estimation, it is too soon to tell just how AI will affect the workplace.

“People are really worried that AI-based automation is going to erode specific tasks more rapidly,” Autor observes. “Eroding tasks is not the same thing as eroding jobs, since many jobs involve a lot of tasks. But we’re all saying: Where is the new work going to come from? It’s so important, and we know little about it. We don’t know what it will be, what it will look like, and who will be able to do it.”

“If everyone is an expert, then no one is an expert”

The four co-authors also collaborated on a previous major study of new work, published in 2024, which found that about six out of 10 jobs in the U.S. from 1940 to 2018 were in new specialties that had only developed broadly since 1940. The new study extends that line of research by looking more precisely at who fills the new lines of work. 

To do that, the researchers used U.S. Census Bureau data from 1940 through 1950, as well as the Census Bureau’s American Community Survey (ACS) data from 2011 to 2023. In the first case, because Census Bureau records become wholly public after about 70 years, the scholars could examine individual-level data about occupations, salaries, and more, and could track the same workers as they changed jobs between the 1940 and 1950 Census enumerations. 

Through a collaborative research arrangement with the U.S. Census Bureau, the authors also gained secure access to person-level ACS records. These data allowed them to analyze the earnings, education, and other demographic characteristics of workers in new occupational specialties — and to compare them with workers in longstanding ones.

New work, Autor observes, is always tied to new forms of expertise. At first, this expertise is scarce; over time, it may become more common. In any case, expertise is often linked to new forms of technology.

“It requires mastering some capability,” Autor says. “What makes labor valuable is not simply the ability to do stuff, but specialized knowledge. And that often differentiates high-paid work from low-paid work.” Moreover, he adds, “It has to be scarce. If everyone is an expert, then no one is an expert.”

By examining the census data, the scholars found that back in 1950, about 7 percent of employees had jobs in types of work that had emerged since 1930. More recently, about 18 percent of workers in the 2011-2023 period were in lines of work introduced since 1970. (That happens to be roughly the same portion of new jobs per decade, although Autor does not think this is a hard-and-fast trend.) 

In these time periods, new work has emerged more often in urban areas, with people under 30 benefitting more than any other age category. Getting a job in a line of new work seems to have a lasting effect: People employed in new work in 1940 were 2.5 times as likely to be in new work in 1950, compared to the general population. College graduates were 2.9 percentage points more likely than high school graduates to be engaged in new work. 

New work also has a wage premium, that is, better salaries on aggregate than in already-existing forms of work. Yet as the study shows, that wage premium also fades over time, as the particular expertise in many forms of new work becomes much more widely grasped. 

“The scarcity value erodes,” Autor says. “It becomes common knowledge. It itself gets automated. New work gets old.”

After all, Autor points out, driving a car was once a scarce form of expertise. For that matter, so was being able to use word-processing programs such as WordPerfect or Microsoft Word, well into the 1990s. After a while, though, being able to handle word-processing tools became the most elementary part of using a computer.

Back to AI for a minute

Studying who gets new jobs led the scholars to striking conclusions about how new work is created. Examining county-level data from the World War II era, when the federal government was backing new manufacturing in public-private partnerships throughout the U.S., the study shows that counties with new factories had more new work, and that 85 to 90 percent of new work from 1940 to 1950 was technology-driven. 

In this sense there was a great deal of demand-driven innovation at the time. Today, public discourse about innovation often focuses on the supply side, namely, the innovators and entrepreneurs trying to create new products. But the study shows that the demand side can significantly influence innovative activity. 

“Technology is not like, ‘Eureka!’ where it just happens,” Autor says. “Innovation is a purposive activity. And innovation is cumulative. If you get far enough, it will have its own momentum. But if you don’t, it’ll never get there.”

Which brings us back to AI, the topic so many people are focused on in 2026. Will AI create good new jobs, or will it take work away? Well, it likely depends how we implement it, Autor thinks. Consider the massive health care sector, where there could be a lot of types of tech-driven new work, if people are interested in creating jobs.

“There are different ways we could use AI in health care,” Autor says. “One is just to automate people’s jobs away. The other is to allow people with different levels of expertise to do different tasks. I would say the latter is more socially beneficial. But it’s not clear that is where the market will go.” 

On the other hand, maybe with government-driven demand in various forms, AI could get applied in ways that end up boosting health care-sector productivity, creating new jobs as a result. 

“More than half the dollars in health care in the U.S. are public dollars,” Autor observes. “We have a lot of leverage there, we can push things in that direction. There are different ways to use this.” 

This research was supported, in part, by the Hewlett Foundation, the Google Technology and Society Visiting Fellows Program, the NOMIS Foundation, the Schmidt Sciences AI2050 Fellowship, the Smith Richardson Foundation, the James M. and Cathleen D. Stone Foundation, and Instituut Gak.

Four from MIT named 2026 Searle Scholars

Computational neuroscientist Sven Dorkenwald and cell biologist Whitney Henry, along with two MIT alumni, are recognized for their exceptional early-career research contributions.

MIT scientists Sven Dorkenwald and Whitney Henry have been named 2026 Searle Scholars, an award given annually to 15 exceptional early-career researchers in the fields of biomedical sciences and chemistry. Dorkenwald is an assistant professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research. Henry is the Robert A. Swanson (1969) Career Development Professor of Life Sciences and an intramural faculty member at the Koch Institute for Integrative Cancer Research.

In addition, MIT alumni Irene Kaplow ’10 and Jared Mayers PhD ’15 were also honored.

Chosen by a scientific advisory board, Searle Scholars are considered among the most creative young researchers pursuing high-risk/high-reward research. The Searle Scholars Program is funded through the Searle Funds at The Chicago Community Trust and administered by Kinship Foundation. Each scholar will each receive $450,000 in flexible funding to support their work over the next three years.

Sven Dorkenwald

Sven Dorkenwald is a computational neuroscientist investigating the organizational principles of neuronal circuits. The synaptic connectivity of neurons, their connectome, is fundamental to how networks of neurons function. Dorkenwald develops computational and collaborative tools to map, analyze, and interpret synapse-resolution connectomes. His work has led to large connectomic reconstructions of the fruit fly brain and parts of mammalian brains. He uses these connectomes to investigate the architecture of neuronal circuits and how their structure supports complex computations.

“As I establish my new lab, the Searle Scholars Award will help us launch ambitious projects and set our long-term scientific direction,” says Dorkenwald. “I am deeply grateful for the support from the Kinship Foundation and look forward to interacting with this amazing cohort of Searle Scholars.”

Dorkenwald joined the faculty of MIT in 2026 as an assistant professor in the Department of Brain and Cognitive Sciences and an investigator at the McGovern Institute. He earned a BS in physics and an MS in computer engineering from the University of Heidelberg, followed by a PhD in computer science and neuroscience at Princeton University in 2023 under the mentorship of Sebastian Seung and Mala Murthy. Dorkenwald completed his postdoctoral training as a Shanahan Research Fellow at the Allen Institute and the University of Washington, while serving as a visiting faculty researcher at Google Research.

Whitney Henry

Whitney Henry investigates the potential of ferroptosis, an iron-dependent form of cell death, for developing novel therapies that target subpopulations of cancer cells that are highly metastatic, therapy-resistant, and therefore critical instigators of tumor relapse. Her research is focused on uncovering the molecular factors influencing ferroptosis susceptibility, investigating its effects on the tumor microenvironment, and developing innovative methods to manipulate ferroptosis resistance in living organisms, drawing from functional genomics, metabolomics, bioengineering, and a range of in vitro and in vivo models.

“I am incredibly grateful to the Kinship Foundation for supporting our research and giving us the freedom to ask bold, curiosity-driven scientific questions,” says Henry. “This support allows us to pursue ambitious ideas, take creative risks, and embark on new research directions.”

Henry joined the MIT faculty in 2024 as an assistant professor in the Department of Biology and a member of the Koch Institute, and is currently an HHMI Freeman Hrabowski Scholar. She received her bachelor's degree in biology with a minor in chemistry from Grambling State University and her PhD from Harvard University. Following her doctoral studies, she worked in the lab of Robert Weinberg at the Whitehead Institute for Biomedical Research and was supported by fellowships from the Jane Coffin Childs Memorial Fund for Medical Research and the Ludwig Center at MIT.

Alumni also honored

Irene Kaplow ’10, a graduate of the MIT Department of Mathematics, is an assistant professor in the Department of Biology and the Ray and Stephanie Lane Computational Biology Department at Carnegie Mellon University. Her selection as a Searle Scholar is for “deciphering transcriptional regulatory mechanisms underlying mammalian dietary phenotype evolution and their relationships to transcriptional regulatory responses to changes in diet.”

Jared Mayers PhD ’15, who earned his doctorate from the MIT Department of Biology, is an assistant professor at the Fred Hutchinson Cancer Center at the University of Washington. His selection as a Searle Scholar is for “a reverse-translational framework to decipher metabolic vulnerabilities of bacterial pathogens.”

Q&A: The path to a PhD in computational science and engineering at MIT

MIT doctoral candidate Emily Williams reflects on her time at the Center for Computational Science and Engineering as she becomes the program’s first graduate.

In 2023, the Center for Computational Science and Engineering (CCSE), an academic unit in the MIT Schwarzman College of Computing, introduced a new standalone PhD degree program. This interdisciplinary PhD program blends both coursework and a thesis, enabling students to pursue research in cross-cutting methodological aspects of computational science and engineering.

PhD candidate Emily Williams is poised to be the first graduate of the program. With a technical background in aerospace engineering and applied mathematics, her research interests include stochastic and generative modeling for multiscale chaotic systems. She earned a BS in aerospace engineering from the University of Illinois Urbana-Champaign and an MS in aeronautics and astronautics from MIT. She was awarded the Department of Energy Computational Science Graduate Fellowship, which funded her doctoral research. Here, she discusses her experience with the program and its impact on her career trajectory.

Q: What has been a highlight of the CCSE degree program?

A: I found the program curriculum to be extremely thoughtful and intentional. In particular, the program of study was constructed to cover many important areas of computational science and engineering research and education, from engineering and mathematical modeling to scientific and parallel computing. I found a lot of overlap with the DoE CSGF program of study, so I was given a lot of freedom to pursue very interesting technical electives that fit within CSE that I might not have been able to explore if I had been in a discipline-centric program.

Q: Why is this program so impactful, especially in the context of having a stand-alone PhD program?

A: I think a stand-alone PhD program helps to further establish the MIT CCSE as a leader in CSE research and education. The joint programs give graduate researchers more opportunity to learn and apply leading CSE methodologies to their disciplinary areas and primarily stay within their home department. For me, I’ve found that I’ve had more opportunities for collaboration, in potentially applying my methods to a wide range of different exciting applications. I think this theme of collaboration will continue to foster through those advancing through the standalone program in particular.

Q: What advice would you give to students considering this program?

A: I think my advice would be to keep an open mind. My interest in CSE was shaped by common threads in my education and research interests over the years that I didn’t think were connected at all. Through my fellowship and the standalone program, I felt like I was able to create my own path to my degree and take courses that excited me and fit within the CSE themes of our program of study.

Building AI models that understand chemical principles

Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.

Among all of the possible chemical compounds, it’s estimated that between 10²⁰ and 10⁶⁰ may hold potential as small-molecule drugs.

Evaluating each of those compounds experimentally would be far too time-consuming for chemists. So, in recent years, researchers have begun using artificial intelligence to help identify compounds that could make good drug candidates. 

One of those researchers is MIT Associate Professor Connor Coley PhD ’19, the Class of 1957 Career Development Associate Professor with shared appointments in the departments of Chemical Engineering and Electrical Engineering and Computer Science and the MIT Schwarzman College of Computing. His research straddles the line between chemical engineering and computer science, as he develops and deploys computational models to analyze vast numbers of possible chemical compounds, design new compounds, and predict reaction pathways that could generate those compounds. 

“It’s a very general approach that could be applied to any application of organic molecules, but the primary application that we think about is small-molecule drug discovery,” he says.

The intersection of AI and science

Coley’s interest in science runs in the family. In fact, he says, his family includes more scientists than non-scientists, including his father, a radiologist; his mother, who earned a degree in molecular biophysics and biochemistry before going to the MIT Sloan School of Management; and his grandmother, a math professor.

As a high school student in Dublin, Ohio, Coley participated in Science Olympiad competitions and graduated from high school at the age of 16. He then headed to Caltech, where he chose chemical engineering as a major because it offered a way to combine his interests in science and math.

During his undergraduate years, he also pursued an interest in computer science, working in a structural biology lab using the Fortran programming language to help solve the crystal structure of proteins. After graduating from Caltech, he decided to keep going in chemical engineering and came to MIT in 2014 to start a PhD.

Advised by professors Klavs Jensen and William Green, Coley worked on ways to optimize automated chemical reactions. His work focused on combining machine learning and cheminformatics — the application of computation methods to analyze chemical data — to plan reaction pathways that could make new drug molecules. He also worked on designing hardware that could be used to perform those reactions automatically. 

Part of that work was done through a DARPA-funded program called Make-It, which was focused on using machine learning and data science to improve the synthesis of medicines and other useful compounds from simple building blocks.

“That was my real entry point into thinking about cheminformatics, thinking about machine learning, and thinking about how we can use models to understand how different chemicals can be made and what reactions are possible,” Coley says.

Coley began applying for faculty jobs while still a graduate student, and accepted an offer from MIT at age 25. He received a mix of advice for and against taking a job at the same school where he went to graduate school, and eventually decided that a position at MIT was too enticing to turn down.

“MIT is a very special place in terms of the resources and the fluidity across departments. MIT seemed to be doing a really good job supporting the intersection of AI and science, and it was a vibrant ecosystem to stay in,” he says. “The caliber of students, the enthusiasm of the students, and just the incredible strength of collaborations definitely outweighed any potential concerns of staying in the same place.”

Chemistry intuition

Coley deferred the faculty position for one year to do a postdoc at the Broad Institute, where he sought more experience in chemical biology and drug discovery. There, he worked on ways to identify small molecules, from billions of candidates in DNA-encoded libraries, that might have binding interactions with mutated proteins associated with diseases.

After returning to MIT in 2020, he built his lab group with the mission of deploying AI not only to synthesize existing compounds with therapeutic potential, but also to design new molecules with desirable properties and new ways to make them. Over the past few years, his lab has developed a variety of computational approaches to tackle those goals. 

“We try to think about how to best pair a challenge in chemistry with a potential computational solution. And often that pairing motivates the development of new methods,” Coley says. One model his lab has developed, known as ShEPhERD, was trained to evaluate potential new drug molecules based on how they will interact with target proteins, based on the drug molecules’ three-dimensional shapes. This model is now being used by pharmaceutical companies to help them discover new drugs.

“We’re trying to give more of a medicinal chemistry intuition to the generative model, so the model is aware of the right criteria and considerations,” Coley says.

In another project, Coley’s lab developed a generative AI model called FlowER, which can be used to predict the reaction products that will result from combining different chemical inputs. 

In designing that model, the researchers built in an understanding of fundamental physical principles, such as the law of conservation of mass. They also compelled the model to consider the feasibility of the intermediate steps that need to take place on the pathway from reactants to products. These constraints, the researchers found, improved the accuracy of the model’s predictions.

“Thinking about those intermediate steps, the mechanisms involved, and how the reaction evolves is something that chemists do very naturally. It’s how chemistry is taught, but it’s not something that models inherently think about,” Coley says. “We’ve spent a lot of time thinking about how to make sure that our machine-learning models are grounded in an understanding of reaction mechanisms, in the same way an expert chemist would be.”

Students in his lab also work on many different areas related to the optimization of chemical reactions, including computer-aided structure elucidation, laboratory automation, and optimal experimental design.

“Through these many different research threads, we hope to advance the frontier of AI in chemistry,” Coley says.

Justin Solomon appointed associate dean of engineering education

MIT faculty member in electrical engineering and computer science to focus on innovation in engineering education and new pedagogical approaches.

Justin Solomon, associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), has been appointed associate dean of engineering education in the MIT School of Engineering, effective July 1.

In this new role, Solomon will focus on advancing innovation in engineering education across the school. He will help shape new pedagogical approaches in the context of an AI-enabled world and will explore experiential, hands-on, and other modes of learning. Working closely with academic departments, Solomon will serve as a thought partner in integrating AI into curricula and will help facilitate interdisciplinary and shared teaching opportunities across departments and other schools. He will also play a key role in helping the school implement relevant recommendations from the Committee on AI Use in Teaching, Learning, and Research Training. 

Solomon will explore opportunities to build industry collaborations, including new models for internships and industry-engaged learning on campus. Collaborating with department heads and the School of Engineering leadership team, he will also support faculty in designing new courses and evolving existing programs to meet emerging opportunities in engineering.

“Justin’s interdisciplinary approach will be especially valuable as we continue to evolve engineering education to meet new opportunities and challenges. His extensive experience applying AI across a wide range of domains will help each academic department thoughtfully integrate AI and new educational models into their curricula,” says Paula T. Hammond, dean of the School of Engineering and Institute Professor. “I look forward to the vision and perspective he will bring to the school’s leadership team.”

A dedicated educator, Solomon has played a central role in shaping computing education at MIT. He is a key contributor to the Common Ground for Computing, where he co-teaches the core class 6.C01 (Modeling with Machine Learning: From Algorithms to Applications) with Regina Barzilay, the Delta Electronics Professor in the MIT Department of Electrical Engineering and Computer Science and affiliate faculty member at the Institute for Medical Engineering and Science. Within EECS, he teaches 6.7350 (Numerical Algorithms for Computing and Machine Learning) as well as 6.8410 (Shape Analysis). He is also the founder of the Summer Geometry Initiative, a six-week program that introduces students to geometry processing through intensive training, collaboration, and research experiences.

Solomon’s dedication to teaching and helping students has been honored with various awards, including the EECS Outstanding Educator Award and the Burgess (1952) and Elizabeth Jamieson Prize for Excellence in Teaching. He is the author of “Numerical Algorithms,” a textbook that presents a modern approach to numerical analysis for computer science students.

Solomon is a principal investigator at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), where he leads the Geometric Data Processing Group. His research sits at the intersection of geometry and computation, with applications spanning computer graphics, autonomous navigation, political redistricting, physical simulation, 3D modeling, and medical imaging. He is also a core faculty member of the MIT-IBM Watson AI Lab, contributing to research that advances the foundations and applications of artificial intelligence.

His scholarly contributions have been recognized with numerous distinctions, including the 2023 Harold E. Edgerton Faculty Achievement Award for exceptional contributions in teaching, research, and service. In 2025, he was named a Schmidt Polymath, supporting interdisciplinary research across areas such as acoustics and climate that rely on large-scale simulation of physical systems.

Solomon joined the MIT faculty in 2016. He previously held an NSF Mathematical Sciences Postdoctoral Research Fellowship in Princeton University’s Program in Applied and Computational Mathematics. He earned his bachelor’s, master’s, and doctoral degrees from Stanford University. While studying at Stanford, he also worked as a research assistant at Pixar Animation Studios.

A day in the life of MIT MBA student Patrick Yeung

MIT Sloan’s Sustainability Initiative provides opportunities to lead in ways that will help build a more sustainable future.

Senior MBA student Patrick Yeung came to MIT Sloan School of Management wanting to be surrounded by a community of builders. 

“I come from a consulting background, which has its own strengths and gives you a specific toolkit, but I felt like I was not very technical, and so I wanted to be surrounded and inspired by people who had that knowledge and experience,” he says.

“MIT Sloan’s Sustainability Initiative provides a great platform to help a generalist like myself become more specialized in this space, whether it be the Sustainability lunch series that they run every Thursday, the annual conference that gets organized, or the class catalog that aligns with the Sustainability Certificate.”

Yeung eventually hopes to join a climate tech scale-up to help formalize the business and scale, using what he’s learned at MIT Sloan to make a real impact.

“I've come to appreciate the systems thinking approach to sustainability that MIT Sloan has, especially in the context of the tech and lab-scale tech spinout ecosystem that MIT more broadly has. The technology is obviously an important piece of both climate mitigation and adaptation, but we will also need other techno-economic regime changes to be able to truly change our planet for the better — that takes policy and legal changes, that takes leadership and courage, and ultimately it takes a willingness to fail, over and over, in order to iterate.”

The following photo gallery provides a snapshot of what a typical day for Yeung has been like as an MIT student.

The Haystack 37m Telescope: A new era of astrophysical research

The legendary radio astronomy telescope returns to its science and educational mission at MIT Haystack Observatory.

The Haystack 37m Telescope has been a landmark in radio astronomy and radar studies of the solar system since its first light in 1964. Over the following four decades, it supported NASA's Apollo landings on the moon, made planetary radar maps of the surface of Venus, contributed to experimental tests of Einstein's general relativity, supported the development of VLBI, and conducted foundational studies of quasars and star-forming regions. 

Recently, the Haystack 37m Telescope — a 37-meter radio and millimeter-wavelength antenna at MIT Haystack Observatory in Westford, Massachusetts — made its return to front-line astronomical research following an extended period of system upgrades. These observations reconnect this instrument with its long tradition of scientific discovery and open a new chapter.

On Dec. 8, 2025, Haystack scientists observed the supermassive black hole system at the center of the galaxy Messier 87 (M87) using a technique called very long baseline interferometry (VLBI) that links telescopes across continents to achieve extraordinary resolution. These observations mark the return of one of America's most storied radio telescopes to its historical scientific and educational mission.

The observations targeted the powerful jet of energy and matter launched from M87’s central black hole, M87*. This jet, driven by a black hole six-and-a-half billion times the mass of our sun, extends thousands of light years into intergalactic space and is one of the most energetic phenomena in the known universe. 

Previous international campaigns, namely those led by the Event Horizon Telescope, have imaged the black hole's immediate “shadow.” The Haystack 37m Telescope observations, performed in collaboration with the telescopes of the Very Long Baseline Array (VLBA) and the Greenland Telescope (GLT), help to probe the larger-scale structure of the jet, investigating how energy is transported far beyond the black hole's vicinity. Understanding this process is central to explaining how supermassive black holes shape the galaxies that surround them.

“The Haystack 37m Telescope’s exceptional sensitivity enables the intercontinental telescope array to detect faint emission from around the distant M87* black hole,” says Paul Tiede, principal investigator of the M87 study. “In tandem with the GLT and the VLBA, Haystack is helping create the first multifrequency movies of M87*’s faint jet, greatly improving our understanding of black hole physics.”

The upgraded Haystack 37m Telescope opens multiple new lines of research. At MIT, Saverio Cambioni and Richard Teague of the Department of Earth, Atmospheric and Planetary Sciences (EAPS) plan to use the instrument within MIT’s Planetary Defense Project to measure asteroid sizes and shapes, characterizing objects that could pose a hazard to Earth and deepening our understanding of the solar system’s formation. Associate Professor Brett McGuire of the Department of Chemistry plans to search for complex organic molecules in space, work that speaks to the question of how the chemical precursors to life arise.

“We are thrilled to provide the research community with a powerful telescope at a time where few such instruments are available,” says Jens Kauffmann, principal investigator of the Haystack 37m Telescope Astronomy Program, who uses the telescope to study the formation of stars and their planets. “Even more exciting are the prospects this generates for the next generation of astronomers. Hands-on training opportunities on world-class research telescopes have become exceptionally rare worldwide, and now we can offer this singular advanced workforce development program right here in Massachusetts.”

Student involvement with the Haystack 37m Telescope has already resumed: Undergraduate interns at Haystack Observatory played an active role in developing the telescope’s control systems and data analysis algorithms. This work exemplifies Haystack’s role as a hands-on research and training environment where students contribute directly and gain practical experience with a frontline research instrument.

The return to research-focused observations is the result of more than 10 years of careful, sustained work. From 2010 to 2014, the Haystack 37m Telescope underwent a major upgrade and refurbishment that enhanced its ability to observe at millimeter wavelengths. This work was primarily done to improve the antenna’s capability as a space radar. The dish now primarily serves U.S. government agencies in that capability, and astronomy was temporarily a secondary activity. 

But work to restore the telescope's science capability never stopped. Initial support from the National Science Foundation (NSF) in 2015 modernized systems for data analysis and radio signal processing. The first successful engineering-oriented VLBI experiments with the new dish were conducted at the same time. Additional NSF funding in 2019, provided in the context of the Next Generation Event Horizon Telescope (ngEHT) program, enabled a more general and sustained effort to upgrade receiver equipment and computing systems. Support from private donors to Haystack also aided in this longer-term effort.

Several recent developments, particularly in 2025, proved significant. With support from MIT's Jarve Seed Fund for Science Innovation, scientists and engineers removed lingering technical limitations with astronomy systems and expanded the telescope's scientific reach. Other funding for projects led by the Smithsonian Astrophysical Observatory enabled the M87 campaign and commissioning of the next-generation digital back end, a highly advanced signal-processing system developed for the ngEHT. Together, these advances made the December 2025 observations possible. MIT Haystack Observatory is now pursuing support from both private and federal sources for further improvements under the Haystack 37m Telescope Astronomy Program.

“The upgraded Haystack 37m Telescope empowers MIT students and researchers to pursue fundamental questions relating to our origins and our solar system,” says Richard Teague, professor at MIT EAPS. “With privileged access to such a powerful facility, we can undertake ambitious observational programs previously impossible to schedule. This is the beginning of what we expect will be an exciting era of new discoveries with the Haystack 37m Telescope.”

Single-molecule tracker illuminates workings of cancer-related proteins

Researchers can now use custom-built microscopy and nanotechnology to tag and follow the activity of individual proteins in real-time.

Using a powerful single-molecule imaging method they developed, a research team from the Broad Institute of MIT and Harvard has unveiled a dynamic view of how some cancer-related proteins interact in living cells. 

The technique relies on highly stable nanoparticle probes that brightly illuminate individual molecules for long periods of time. The researchers used their method to observe, for the first time, individual receptors as they move around the cell membrane, attaching to and then letting go of other receptors to alter signaling within the cell.

Described in the journal Cell, the work demonstrates the method’s potential for investigating other receptors and molecules, and for improved drug screening to better understand the effects of therapeutics on living cells.

“With our photostable probes, we can map out the entire lifespan of these molecules in their native environment and see things that have never been observable before,” says study leader Sam Peng, a Broad Institute core institute member and assistant professor of chemistry at MIT.

Molecular movies

Peng’s method solves a problem with existing contrast agents used in single-molecule tracking, such as dyes. Under the laser light that’s used to excite these dyes, they burn out after a few seconds in a phenomenon known as photobleaching, which means that scientists could only use them to take a few snapshots of cell receptors, and not follow them over the entirety of the signaling process.

For a longer and richer view, Peng’s lab developed long-lasting probes, known as upconverting nanoparticles, which emit signals that remain stable under laser excitation. The nanoparticles contain rare-earth ions that continue to luminescence for minutes, hours, and potentially years. In addition, by altering the type and doses of the ions, scientists can engineer probes emitting in many different colors, enabling tracking of many targets in a single experiment.

In the current study, the researchers aimed to uncover new biology by focusing on the EGFR family of cell receptors, which have been linked to several kinds of cancer. They collaborated with EGFR experts Matthew Meyerson and Heidi Greulich of the Broad’s Cancer Program. They knew that EGFR receptors need to pair up, or “dimerize,” in order to initiate signaling within the cell, but they wanted to learn more about the dynamics of these pairings — what the receptors partner with, how long they stay together, and how they find new partners.

For a better and more sustained look at the receptors, the research team customized their upconverting nanoparticles to tag EGFR and related receptors HER2 and HER3, which are linked to cancer, and used them to track the molecules in living human cells.

A new view of protein pairings

In this study, Peng and his team observed that, when activated with a stimulating molecule, EGFR receptors can pair up and stay dimerized for several minutes, something not observable using traditional dyes. Excessive and prolonged dimerization can lead to too much cell growth and cancer.

A microscopy video shows upconverting nanoparticles tagged to EGFR receptors (labeled pink and green), which track individual receptors as they dimerize. Image courtesy of the researchers.

When the EGFR molecules carried cancer-related mutations, the dimers became more stable, with the more stabilizing mutations linked to more potent cancers in people. In addition, the mutated receptors could form stable dimers even without an external stimulus prompting them to dimerize. The finding helps explain how EGFR mutations can lead to uncontrolled cell growth and cancer, and could inform efforts to target this process therapeutically.

The team discovered several other new and surprising details about how HER2 and HER3 form stable pairings with themselves, which helps illuminate the role of these molecules in related cancers.

When the research team tagged all three receptor types in one experiment, they observed a vibrant scene with receptors navigating the cell surface, finding partners, unpairing, and then finding new partners, over and over again.

Beyond shedding light on EGFR biology, the scientists hope that collaborators in other fields will apply their method to ask new scientific questions about other proteins of interest. “We think this technique could be transformative for studying molecular biology, because it enables dynamic biological processes to be observed with high spatiotemporal resolution over unprecedented timescales,” says Peng.

They are also planning to explore the method’s use in studying the mechanism of drug action, to reveal how potential therapeutics alter individual molecules over time. In addition, they will continue to improve their methods, such as making the probes smaller, brighter, and able to emit more colors.

New research enables a robot to chart a better course

By rapidly generating a smooth path plan that cuts travel time and avoids obstacles, the open-source “MIGHTY” system could streamline disaster recovery and parcel delivery.

In the aftermath of a devastating earthquake, unpiloted aerial vehicles (UAVs) could fly through a collapsed building to map the scene, giving rescuers information they need to quickly reach survivors. 

But this remains an extremely challenging problem for an autonomous robot, which would need to swiftly adjust its trajectory to avoid sudden obstacles while staying on course.

Researchers from MIT and the University of Pennsylvania developed a new trajectory-planning system that tackles both challenges at once. Their technique enables a UAV to react to obstacles in milliseconds while staying on a smooth flight path that minimizes travel time. 

Their system uses a new mathematical formulation that ensures the robot travels safely to its destination along a feasible path, and that is less computationally intensive than other techniques. In this way, it generates smoother trajectories faster than state-of-the-art methods.

The trajectory planner is also efficient enough for real-time flight using only the robot’s onboard computer and sensors. 

Named MIGHTY, the open-source system does not require proprietary software packages that can cost hundreds of thousands of dollars. It could be more readily deployed in a wider variety of real-world settings.

In addition to search-and-rescue, MIGHTY could be utilized in applications like last-mile delivery in urban spaces, where UAVs need to avoid buildings, wires, and people, or in industrial inspection of complex structures, such as wind turbines.

“MIGHTY achieves comparable or better performance using only open-source tools, which means any researcher, student, or company — anywhere in the world — can use it freely. By removing this cost barrier, MIGHTY helps democratize high-performance trajectory planning and opens the door for a much broader community to build on this work,” says Kota Kondo, an aeronautics and astronautics graduate student and lead author of a paper on this trajectory planner.

Kondo is joined on the paper by Yuwei Wu, a graduate student at the University of Pennsylvania; Vijay Kumar, a professor at UPenn; and senior author Jonathan P. How, a Ford professor of aeronautics and astronautics and a principal investigator in the Laboratory for Information and Decision Systems (LIDS) and the Aerospace Controls Laboratory (ACL) at MIT. The research appears in IEEE Robotics and Automation Letters.

Overcoming trade-offs           

When Kondo was a child, the Fukushima Daiichi nuclear accident occurred following the Great East Japan Earthquake. With school cancelled, Kondo was stuck at home and watched the news every day as workers explored and secured the reactor site. Some workers still had to enter hazardous areas to contain the damage and assess the situation, exposing them to high doses of radioactive material.

“I became passionate about creating autonomous robots that can go into these dynamic and dangerous situations, then come back and report to humans who stay out of harm’s way,” Kondo says.

This task requires a strong trajectory planner, which is software that decides the path a robot should follow to safely get from point A to point B. 

But many existing systems force tradeoffs that limit performance. 

While some commercial systems can rapidly generate smooth trajectories, they can cost hundreds of thousands of dollars. Open-source alternatives often underperform compared to commercial solvers or are difficult to use.      

With MIGHTY, Kondo and his colleagues developed an open-source system that produces high-quality, smooth trajectories while reacting to obstacles in real-time, and which runs fast enough for flight using only onboard components.

To do this, they overcame a key challenge that limits many open-source systems. 

These methods usually estimate how long it will take the robot to get from point A to point B as a first step. From that fixed estimation of travel time, the planner finds the best path to reach the destination.

While using a fixed travel time allows the planner to rapidly generate a trajectory, it has drawbacks. For one, if the UAV must go far out of its way to avoid obstacles, it could be forced to crank up the speed to meet the fixed travel-time budget. This makes it harder to avoid sudden hazards.

A MIGHTY method

Instead, MIGHTY uses a mathematical technique, called a Hermite spline, that optimizes the travel time and flight path together, in a single step, to form a smooth trajectory that can be precisely controlled.

“Optimizing the spatial and temporal components together gets us better results, but now the optimization becomes so much bigger that it is harder to solve in a feasible amount of time,” Kondo says.

The researchers used a clever technique to reduce this computational overhead. 

Instead of generating a trajectory from scratch each time, MIGHTY makes an initial guess of a trajectory. Then it refines the trajectory through an iterative optimization, using a map of the scene generated by the UAV’s lidar sensors.

“We can make a decent guess of what the trajectory should be, which is a lot faster than generating the entire thing from nothing,” Kondo says.

This enables MIGHTY to react in real-time to unknown obstacles while keeping the trajectory smooth and minimizing travel time. The system utilizes the UAV’s onboard components, which is important for applications where a robot might travel far from a base station.

In simulated experiments, MIGHTY needed only about 90 percent of the computation time required by state-of-the-art methods, while safely reaching its destination about 15 percent faster than these approaches. 

When they tested the system on real robots, it reached a speed of 6.7 meters per second while avoiding every obstacle that appeared in its path.

“With MIGHTY, everything is integrated in one piece. It doesn’t need to talk to any other piece of software to get a solution. This helps us be even faster than some of the commercial solvers,” Kondo says.

In the future, the researchers want to enhance MIGHTY so it can be used to control multiple robots at once and conduct more flight experiments in challenging environments. They hope to continue improving the open-source system based on user feedback.

“MIGHTY makes an important contribution to agile robot navigation by revisiting the trajectory representation itself. Hermite splines have already been successfully used in visual simultaneous localization and mapping, and it is nice to see their advantages now being exploited for trajectory planning in mobile robots. By enabling joint optimization of path geometry, timing, velocity, and acceleration while retaining local control of the trajectory, MIGHTY gives robots more freedom to compute fast, dynamically feasible motions in cluttered environments,” says Davide Scaramuzza, professor and director of the Robotics and Perception Group at the University of Zurich, who was not involved with this research.

This research was funded, in part, by the United States Army Research Laboratory and the Defense Science and Technology Agency in Singapore.

Startup making reusable emergency housing wins MIT $100K competition

Uplift Microhome’s modular housing units can provide their own power and water, for faster deployments.

A startup making emergency housing cheaper and faster to deploy won this year’s MIT $100K Entrepreneurship Competition on May 12.

Uplift Microhome is building reusable, modular housing units to provide housing on demand to people affected by natural disasters and other emergencies. Each of the company’s homes has its own batteries and water reservoir, allowing them to quickly be transported and placed off-grid.

“Every year, millions of Americans are displaced by natural disasters,” said co-founder Charlie Nitschelm, who is in MIT’s Leaders for Global Operations program, earning a master’s in engineering and an MBA. “If they're lucky, they can stay with friends or family. If they’re not so lucky, they could end up in a homeless shelter. But disasters aren’t just two-week problems. It takes months, sometimes years, to get back to what life was like before. Bottom line: We lack dignified and affordable housing after disasters.”

Uplift Microhome was one of seven teams chosen to pitch at the final event, which took place inside a packed Kresge Auditorium. Each team got five minutes to pitch their startups before a few minutes of questioning from judges.

This year’s competition started in April with more than 80 applications. The program’s judges selected 16 teams to compete in the semifinal before whittling that number down to the finalist teams for Tuesday’s event.

“This competition isn’t just about one big night,” $100K managing director and MIT Sloan School of Management student Celine Christory said. “It’s a year-long journey for our organizers and students. It kicks off with the ‘Pitch’ event in December, moves to ‘Accelerate’ in March, and culminates in the ‘Launch’ event.”

In the pitch that won the $100,000 Danny Lewin Grand Prize, Nitschelm said it takes an average of four months for the U.S. Federal Emergency Management Agency (FEMA) to deploy single-use housing after a disaster. That’s because these homes require power and utilities in addition to extensive foundation preparation.

“As a result, less than 1 percent of survivors actually receive a physical home,” Nitschelm said. “The rest get a check and are told to go figure it out. This isn’t just our opinion. The Department of Homeland Security audited FEMA and recommended providing a cost-effective housing alternative that allows disaster survivors to stay close to their home.”

Uplift’s homes can be transported on the back of a tractor trailer and deployed using a standard forklift. In addition to its battery and water reservoir, the homes feature self-leveling bases that allow them to be deployed on uneven terrain.

“That dramatically simplifies delivery, installation, and deactivation to the point where you can economically recover, refurbish, and redeploy the unit,” says co-founder Trevor O’Leary, a student at Harvard Business School.

The company has already built a home and believes it can manufacture each unit at a cost similar to the cheapest tractor trailer while delivering housing in hours. The company expects the marginal cost of reusing each unit to be an order of magnitude less expensive than current solutions. Down the line, it plans to deploy homes to combat housing insecurity, for seasonal workers and during construction projects. It plans to manufacture its homes in the United States.

The second-place $50,000 David T. Morgenthaler Founder’s Prize was awarded to the startup Mohan, which is using generative artificial intelligence to map the Earth’s subsurface in three dimensions. The company is deploying its technology to help mining companies decide where to drill, starting by targeting copper deposits.

“Everyone is talking about AI and chips, but no one is talking about what they sit on: copper,” said co-founder Hongze Bo, a PhD student in MIT’s Department of Earth, Atmospheric and Planetary Sciences. “Every cable, GPU, and data center depends on copper. By 2030, we’re going to be 4 million tons of copper short. But we don't know where the next deposit is. Today we just drill and hope.”

The core of Mohan’s technology is a diffusion AI model that iteratively removes noise from subsurface data to create underground scans. The company also develops its own subsurface data.

“We built a full, 3D subsurface model using generative AI,” explained Bo. “It’s the same technology behind [image generation tools] Sora and Midjourney.”

The third place $5,000 prize went to Iceberg Systems, which is using autonomous AI agents to predict how risk cascades across the economy. The company invented a new class of AI systems at MIT that coordinates millions of AIs to simulate how risks emerge through interaction. It has been working with the Department of Energy.

“Iceberg simulates behaviors across millions of market participants, from brokers to consumers to institutions, to simulate and predict how shocks cascade through their interactions and create systemic risk in the economy,” says co-founder and MIT PhD student Ayush Chopra.

The $5,000 Audience Choice Prize went to Pixology, an agentic AI platform that creates on-brand, sponsor-ready sports content to help monetize live moments.

The other finalists that presented at this year’s event were:

• NeuralPhysics, which is building foundation physics models and agents for hardware design simulation and manufacturing;
• DesignFlowAI, a design intelligence app embedded in computer-aided design software to give engineers insights in real time; and
• Auto Lab, an autonomous AI platform that helps teams build better models faster. 

The $100K Entrepreneurship Competition is one of MIT’s annual flagship entrepreneurial events. It began more than 30 years ago when a group of students, along with the late Ed Roberts, who was the founder and chair of the Martin Trust Center for MIT Entrepreneurship, decided to start a startup pitch competition.

The prize started at $10,000 then grew to $50,000 before reaching today’s $100,000 grand prize. Past participants include HubSpot, Akamai, and Lightmatter.

In addition to the prizes, teams received mentorship from venture capitalists, serial entrepreneurs, corporate executives, and attorneys; funding for prototypes; business plan feedback; and more.

Two from MIT named 2026 Knight-Hennessy Scholars

The prestigious fellowship funds graduate studies at Stanford University.

MIT master’s student Sunshine Jiang ’25 and Rupert Li ’24 are recipients of this year’s Knight-Hennessy Scholarship. Now in its ninth year, the highly competitive scholarship provides up to three years of financial support for graduate studies at Stanford University. 

Sunshine Jiang  ’25

Sunshine Jiang, from Hangzhou, China, graduated from MIT in 2025 with a bachelor’s degree as a double major in physics and electrical engineering and computer science, along with minors in mathematics and economics. She will receive her master of engineering degree this month and will start her PhD in computer science at Stanford School of Engineering this fall. 

Jiang researches embodied artificial intelligence and robotics, developing data-efficient, adaptive systems for general-purpose robots that broaden accessibility. She has presented her research at major conferences, including the Conference on Robot Learning, the International Conference on Robotics and Automation, and the International Conference on Learning Representations. 

Jiang led the development of AI-powered systems that provide access to traditional Chinese art in rural classrooms, founded cross-country programs that expand girls’ access to STEM education, and created a Covid-19 documentary amplifying community voices, which was featured on China Daily.

Rupert Li ’24

Rupert Li, from Portland, Oregon, is currently pursuing a PhD in mathematics at Stanford School of Humanities and Sciences. He graduated from MIT in 2024 with a bachelor’s degree, double majoring in mathematics and computer science, economics, and data science. Along with his bachelor’s degree, he also received a master’s degree in data science. Li then traveled to the United Kingdom as a Marshall Scholar, where he earned a master’s degree in mathematics from the University of Cambridge.

Li’s research interests lie in probability, discrete geometry, and combinatorics. He enjoys serving as a mentor for MIT PRIMES-USA, a high school math research program, and previously served as an advisor for the Duluth REU, an undergraduate math research program. In addition to the Knight-Hennessy Scholarship and the Marshall Scholarship, he has been awarded the Hertz Fellowship, P.D. Soros Fellowship, and the Goldwater Scholarship, and he received honorable mention for the Frank and Brennie Morgan Prize.

3Q: Why science is curiosity on a mission

VP for Communications Alfred Ironside describes how a new initiative from MIT seeks to remind Americans of the value and power of curiosity-driven research.

This week, MIT launches a new initiative — titled Science Is Curiosity on a Mission — to make the case for the long-horizon, curiosity-driven science that has powered generations of American innovation. Through stories of scientists pursuing open-ended questions, the project highlights how fundamental discovery research sparks advances in medicine, technology, national security, and economic growth.

MIT News spoke with Alfred Ironside, the Institute’s vice president for communications, about what inspired the effort, what’s at stake for the U.S. research enterprise, and why curiosity remains one of America’s greatest strengths.

Q: What is “Science Is Curiosity on a Mission,” and why launch it now?

A: Science has been under threat for some time now, and public investment in discovery science has been flagging. We want to remind people in Washington and across the country what curiosity-driven science is all about, and why it matters so much in our individual lives and in the life of the country. 

Science begins with curiosity — someone asking a question and refusing to let it go. History’s most important discoveries did not begin with a commercial objective or a guaranteed outcome. They began because someone wanted to understand how the world works. Think Ben Franklin and his kite: This drive to discover goes back to the beginnings of the United States. 

That’s the story we want to tell, but in today’s terms. We’re spotlighting researchers whose years-long pursuit of core questions has seeded breakthroughs that have changed lives for the better.

We’re launching this storytelling initiative now because public investment is declining, and in all the debates about funding what’s gotten lost is an appreciation for the incredible gifts of curiosity-driven discovery science. 

Over generations, the United States became the world’s scientific leader by investing in research of this kind, especially at universities, where long-term scientific undertakings have time and space to thrive. In turn, those investments have created an extraordinary pipeline of innovation, the envy of the world.

When public investment in basic science falters, the long-term losses start right away — and cascade. Labs close. Young scientists leave the field. Entire avenues of discovery go unexplored. Those losses are not always immediately visible, but eventually we feel them through what’s missing: treatments that never arrive, industries that never emerge, talent that migrates elsewhere.

Other countries understand this. They’re watching us stumble — and they’re growing their research investments aggressively. America’s scientific leadership has been built over decades — and maintaining it requires similar commitment.

It’s important to note that while this initiative to tell the story of discovery science was sparked at MIT, it is not about MIT. We want to spotlight university-based scientists across the country whose work is critical in advancing discovery, educating talent, and fueling innovation that benefits all of us.

Q: Why emphasize the idea of “curiosity”?

A: We start with curiosity for two reasons. First, it’s a human experience we’ve all had, so everyone can relate to it. Everyone knows the feeling of just wanting to know why something happens or how something works. Second, it’s the essential fuel that drives discovery science. 

There’s sometimes a tendency to talk about science in terms of outputs: breakthroughs, startups, commercial applications. Those things matter enormously, but they usually come much later. The beginning is more human. It’s someone wondering why something behaves the way it does, or whether a seemingly impossible problem might have an answer.

Some of the most transformative breakthroughs arose from questions that once appeared disconnected from practical use. MRI technology grew from research on atomic nuclei. The foundations of immunotherapy came from scientists trying to understand how the immune system works. GPS depends on what was once viewed as purely theoretical physics.

Curiosity fuels scientific discovery by pushing people to keep pursuing deep questions because they simply need to know: How does the brain work? How does cancer start? What is the universe made of?

That’s why the second half of the phrase matters: “on a mission.” University researchers are not indulging in idle speculation. They are pursuing knowledge to expand our understanding — and that new knowledge can be the key to startling new solutions.

Universities are uniquely important environments for this work. They bring together people from different disciplines and backgrounds who challenge assumptions and generate new questions. That concentration of talent and openness is extraordinarily productive.

After World War II, the American research university system became one of the most successful engines of discovery in human history. Public investment in university research has helped produce new medicines, computing technologies, communications networks, energy systems, and entire industries that shape modern life.

This effort aims to reconnect all of us with that story.

Q: What’s at stake if the U.S. fails to sustain support for basic research?

A: What’s at stake is not just scientific leadership, but the future pace of American innovation and opportunity.

The innovation pipeline operates across long time horizons. The discoveries powering today’s companies and medical treatments often crystallized 10, 20, or 30 years ago. The breakthroughs that will define the 2040s and 2050s are being explored in laboratories right now.

Basic research is the foundation of that pipeline, and private-sector innovation depends on it. Private investment plays a critical role, but it naturally gravitates toward projects with clearer commercial returns. Public funding supports the earliest, highest-risk stages of inquiry, where outcomes are uncertain but the potential benefit to society is enormous.

If that pipeline dries up, the consequences are stark. Fewer discoveries lead to fewer technologies, startups, and industries. We also risk losing scientific talent to countries that are watching our shifting national priorities — and making larger and more sustained investments in advancing science.

At the same time, there is enormous reason for optimism. The American scientific enterprise remains one of the great achievements of the modern era. It has delivered extraordinary gains in health, prosperity, and quality of life. Millions of people are alive today because of advances rooted in publicly supported research.

This system was built through sustained national commitment across generations. The question now is whether the country will continue investing in curiosity, discovery, and the people pursuing the new knowledge that will allow us to solve the intractable problems of tomorrow.

When curiosity is given room to run, the results can be life-changing for us all.

Elazer Edelman receives the 2026-2027 Killian Award

The professor of medical engineering and science is honored for medical research that has led to better treatments for cardiovascular disease.

Elazer R. Edelman ’78, SM ’79, PhD ’84, an engineer and cardiologist who helped develop cardiovascular stents that have been used by more than 100 million people, has been named the recipient of the 2026-2027 James R. Killian Jr. Faculty Achievement Award.

The award committee recognized Edelman, the Edward J. Poitras Professor in Medical Engineering at MIT’s Institute for Medical Engineering and Science, for his work at the interface of engineering, science, and medicine. In addition to his work on stents, he has made significant contributions to tissue engineering and to deciphering the fundamental biological processes underling cardiovascular disease.

A member of the MIT faculty for more than 30 years, Edelman is renowned as a teacher and mentor. He is also a professor of medicine at Harvard Medical School and a critical care cardiologist at Brigham and Women’s Hospital, and he served as director of MIT’s Institute for Medical Engineering and Science from 2018 to 2024.

“He is a clinician of the highest order who has touched the lives of many, a teacher of greatest passion who has mentored hundreds and taught thousands, and an engineer whose work has reached around the globe,” states the award citation, which was presented at today’s faculty meeting by Xuanhe Zhao, chair of the Killian Award Selection Committee and a professor of mechanical engineering at MIT.

The Killian Award was established in 1971 to recognize outstanding professional contributions by MIT faculty members. It is the highest honor that the faculty can give to one of its members.

“It’s deeply meaningful that your colleagues think enough of you to want to recognize your life’s work. This is an incredibly awe-inspiring group, and for them to feel that way is a truly special honor,” Edelman told MIT News after learning that he had been selected for the award.

Edelman, who grew up in Brookline, Massachusetts, got his first MIT experience as a high school student, taking classes as part of the Institute’s High School Studies Program. That experience led him to apply to MIT, where he earned two bachelor’s degrees, in applied biology and electrical engineering and computer science, followed by a master’s in bioelectrical engineering and a PhD in medical engineering and medical physics. He also earned an MD from Harvard Medical School through the Harvard-MIT Program in Health Sciences and Technology.

As a graduate student, Edelman was one of the first students to join the lab of Robert Langer, the David H. Koch Institute Professor at MIT. Working with Langer, he developed mathematical approaches to guide the design of controlled drug-delivery systems.

“Bob opened my eyes to what it really means to use MIT science to make the world a better place,” Edelman says.

Early in his career, Edelman brought a scientist’s eye to one of medicine’s most urgent clinical challenges: how to address diseased blood vessels without provoking further injury. His studies of the cellular and molecular mechanisms of atherosclerosis and vascular healing — work that continues to this day — coupled with fundamental insights from engineering and physics, helped enable the optimization of bare-metal stents and the development of drug-eluting stents. 

Roughly 90 percent of the more than 100 million stents implanted worldwide now release drugs through principles his work helped define and advance, saving countless lives and improving quality of life for patients around the globe.

Edelman’s work reflects a continuing cycle of discovery: Basic insights in biology shaped transformative medical technologies, and the challenges posed by those technologies, in turn, continue to push biology, science, technology, and engineering together toward new discoveries and clinical advances.

“His landmark work on the cellular mechanisms underlying atherosclerosis and on the biology of cell-material interfaces established the scientific foundations that transformed bare-metal cardiovascular stents from a promising mechanical concept into a biologically informed and clinically transformative therapy with enduring legacy — paving the way for a cascade of innovations that changed the landscape of medicine,” the award committee wrote.

More recently, Edelman’s lab has designed novel heart valves and other innovative approaches to mechanical organ support.

During his tenure as the director of IMES, he led an MIT-wide effort to provide personal protective equipment to health care workers and emergency responders in the early stages of the Covid-19 pandemic. 

“One of the things I’m most proud of is working with many people at MIT in the Covid response. At the height of Covid, we were supplying 23 percent of all PPE throughout New England,” he says. “Every single person who could possibly contribute contributed.”

As director of MIT’s Center for Clinical Translational Research and faculty lead for the Hood Pediatric Innovation Hub, he is now working to help clinical research thrive at MIT and to address the inequities in technology access for society’s most vulnerable population — children.

Throughout his career, Edelman has devoted himself to mentoring students and trainees.

“I’m really proud of what our students have accomplished, not only scientifically, but on a personal level, and not only with me, but everything they’ve done afterwards. The greatness of a place like MIT is that you enable people to grow beyond their potential. That’s really the extraordinary thing about our community,” he says.

In recognition of his scientific achievements, Edelman has been elected a fellow of the American College of Cardiology, the American Heart Association, the Association of University Cardiologists, the American Society of Clinical Investigation, American Institute of Medical and Biological Engineering, the American Academy of Arts and Sciences, National Academy of Inventors, the Institute of Medicine/National Academy of Medicine, and the National Academy of Engineering.

“The Selection Committee is delighted to have this opportunity to honor Professor Elazer Edelman for his exceptional contributions to medical engineering and science, to MIT, and to the world,” the award citation concludes.

Researchers “reprogram” materials by quickly rearranging their atoms

A new method for precisely moving columns of individual atoms within a material could give rise to exotic quantum properties.

It’s been 37 years since scientists first demonstrated the ability to move single atoms, suggesting the possibility of designing materials atom by atom to customize their properties. Today there are several techniques that allow researchers to move individual atoms in order to give materials exotic quantum properties and improve our understanding of quantum behavior.

But existing techniques can only move atoms across the surface of materials in two dimensions. Most also require painstakingly slow processes and high-vacuum, ultracold lab conditions.

Now a team of researchers at MIT, the Department of Energy’s Oak Ridge National Laboratory, and other institutions has created a way to precisely move tens of thousands of individual atoms within a material in minutes at room temperature. The approach uses a set of algorithms to carefully position an electron beam at specific locations of a material, then scan the beam to drive atomic motions.

“The results demonstrate the ability to deterministically move atoms repeatedly within a material’s 3D atomic lattice,” says MIT Research Scientist Julian Klein, who conceived of and directed the project. “We can reprogram materials to create defects at will, realizing entirely artificial states of matter not found in nature with a wide range of potential applications, including sensing, optical, and magnetic technologies. There are so many opportunities enabled by these techniques.”

“It’s like a photocopier that can create columns of identical atomic defects,” says Frances Ross, MIT’s TDK Professor in Materials Science and Engineering. “It’s especially useful because you can move a few atoms to form defects, and do it again and again to build atomic arrangements in three dimensions that have tunable functions in a system that is more robust because the defects exist beneath the surface.”

In a Nature paper appearing today, the researchers described their approach and how they used it to create more than 40,000 quantum defects in a crystalline semiconductor material.

The researchers say the approach offers a new way to study quantum behavior in materials. It could also one day lead to improvements in systems that leverage quantum defects, like quantum computers, dense magnetic memory, atomic-scale logic devices, and more.

Joining Klein and Ross on the paper are Kevin Roccapriore and Andrew Lupini, researchers at Oak Ridge National Laboratory; Mads Weile, a former MIT visiting student; Sergii Grytsiuk, a former Radbound University researcher; Malte Rösner, a professor at Bielefeld University in Germany; Zdenek Sofer, a professor at the University of Chemistry and Technology Prague in the Czeck Republic; Dimitar Pashov, a research associate at King’s College London; and Mark van Schilfgaarde and Swagata Acharya, researchers at the National Laboratory of the Rockies.

Designing matter

In a now-famous 1989 demonstration, IBM researchers used a scanning tunneling microscope to arrange 35 atoms on the surface of a chilled crystal to spell out “IBM.” It was the first time atoms had been precisely positioned, and an important milestone. The approach enabled scientists to engineer specific defects, such as atom-sized vacancies and surface atoms in crystalline materials, leading to major advances in quantum science. But placing those 35 atoms had taken researchers many hours, if not days.

In parallel with those developments, researchers also developed two additional approaches for manipulating atoms in a vacuum, using optical tweezers to trap neutral atoms and oscillating electric fields to trap ions.

While those approaches have enabled remarkable progress, they remain limited to either surfaces or highly controlled experimental systems. Another factor limiting the design of materials for applications such as quantum computers is the inability of atomic manipulation techniques to move atoms in three dimensions: The patterns are created on the surface of a material, where they are exposed to the environment and cannot survive outside tightly controlled laboratory settings.

Engineering usable materials with custom quantum properties would require researchers to rearrange many more atoms, preferably on the interior of materials. The MIT researchers demonstrated that capability in their Nature study.

“We were trying to improve the number of atoms we could move in a reasonable length of time,” Ross explains. “You want to place the atoms close to each other so they can interact, and you want to have a lot of them arranged as you’d like — thousands or millions of atoms in specific locations you’ve chosen. That’s been challenging with existing techniques.”

The researchers used high-performance microscopes at the Department of Energy’s Oak Ridge National Laboratory for their work. Their new technique uses a sophisticated set of algorithms to direct an electron beam at a target atom with a precision of a few picometers (one trillionth of a meter). The beam does a tight loop to help zero in on its target, then sends a beam of electrons through the material in a carefully designed oscillating path, spending about a second at each location. 

“We developed algorithms that allow us to quickly obtain information on where the beam is in the material,” Klein explains. “The trick is to use very few electrons in the process of getting that information, so the whole process is fast and does not unintentionally damage your crystal. It took many years to develop these algorithms and determine the minimum required information needed to infer where the atoms are located with the highest precision.”

The motion of the beam as it delivers electrons, an oscillating path devised by the researchers, pushes entire columns of atoms to new locations the way you might swipe a screen on your phone.

In their experiments, the researchers used this approach to direct the movement of columns of chromium atoms in a stable semiconductor material, chromium sulfide bromide, using a crystal about 13 nanometers thick. The beam created atom-sized vacancies in the material, each vacancy paired with the displaced atom, that they calculated would give the crystal exotic quantum properties.

To show how well their approach scaled, the researchers created over 40,000 defects in about 40 minutes, creating vacancies and interstitials across different distances and in different patterns, calculating that different atomic arrangements should give rise to different quantum mechanical properties.

“Each of these defects has certain ways to interact with its neighbors,” Ross says. “If you place them in a pattern, you could essentially simulate the interactions between the electrons within a molecule, so the whole electronic structure of that molecule can, in a sense, be mapped onto a pattern that you can write into a solid material.”

Probing quantum systems

The success of the approach was likely aided by the way chromium binds within the semiconductor, which has a unique electronic structure. The researchers are further investigating other crystals in which this might work, though they suspect it will be applicable to a diverse range of materials. 

In the materials where it works, the approach has several advantages over existing techniques.

“Moving atoms within solids enables the creation of quantum properties in materials that are stable in the air outside of vacuum conditions,” Klein explains. “And this approach is also scalable to many atomic manipulations, so moving thousands or millions of atoms to create artificial structures would represent completely new physics. We’d like to study those systems.”

The researchers say their technique lays the foundation for a new class of programable matter, which could aid the development of a range of stable quantum devices.

“This is a way of accessing physical phenomena that involve a lot of atoms placed in a certain specified arrangement, and can’t be done by self-assembly,” Ross says. “You can create individually tuned atomic arrangements, and you can have so many of them, each arranged exactly how you like over areas that are tens and hundreds of nanometers. That leads to collective physics we are excited to explore.”

The work was supported, in part, by the Department of Energy and the National Science Foundation.

A new approach to cancer vaccination yields more powerful T cells

Using immune-remodeling mRNA molecules, researchers generated T cells that can slow tumor growth and, in some cases, eradicate tumors.

MIT engineers have developed a new way to amplify the T-cell response to mRNA vaccines — an advance that could lead to much more powerful cancer vaccines and stronger protection against infectious diseases.

Most vaccines generate both antibodies and T cells that can target the vaccine antigen by activating antigen-presenting cells, such as dendritic cells. In this study, the researchers boosted the T-cell response with a new type of vaccine adjuvant (a material that can help stimulate the immune system). The new adjuvant consists of mRNA molecules encoding genes that turn on immune signaling pathways and promote a supercharged T-cell response. 

In studies in mice, this mRNA-encoded adjuvant enabled the immune system to completely eradicate most tumors, either on its own or delivered along with a tumor antigen. The adjuvant also boosted the T-cell response to vaccines against influenza and Covid-19.

“When these adjuvant mRNAs are included in the vaccines, the number of antigen-targeted T cells is substantially increased. These T cells play an important role in the immune response, assisting in the clearance of virally infected cells or, in the case of cancer, killing cancerous cells,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science.

Anderson and Christopher Garris, an assistant professor at Harvard Medical School and Massachusetts General Hospital, are the senior authors of the study, which appears today in Nature Biotechnology. The paper’s lead authors are Akash Gupta, a former Koch Institute research scientist who is now an assistant professor at the University of Houston; Kaelan Reed, an MIT graduate student; and Riddha Das, a research fellow at Harvard Medical School and MGH. Robert Langer, the David H. Koch Institute Professor at MIT, and Ralph Weissleder, a professor of radiology and systems biology at MGH and Harvard Medical School, are also authors.

More powerful vaccines

Vaccines that stimulate the body’s immune system to attack tumors have shown promise in clinical trials, and a handful have been FDA-approved for certain cancers. In some patients, these vaccines stimulate a strong response, but in others, a weak response fails to kill the cancerous cells.

The MIT-MGH team wanted to find a way to make those immune responses more powerful. One way to do that is to deliver immune-stimulating molecules called cytokines along with a vaccine. However, cytokines can overstimulate the immune system, leading to potentially severe side effects.

As an alternative approach, the researchers decided to deliver mRNA strands encoding two genes, IRF8 and NIK, which are involved in antigen presentation and can switch immune cells into a more active state.

NIK is an enzyme that activates a signaling pathway involved in immunity and inflammation, while IRF8 is a transcription factor that helps program dendritic cells, particularly a subset called cDC1, which are especially effective at activating T cells. These antigen-presenting cells can digest foreign antigens and present them to T cells, stimulating the T cells to mount an immune response against the antigen.

“We see that the dendritic cells start shifting toward a more cDC1 phenotype, which is the most important dendritic cell phenotype and can generate a stronger T-cell response,” Gupta says. 

The researchers packaged the mRNA in lipid nanoparticles similar to those used to deliver mRNA Covid vaccines, but with a different chemical composition that promotes their delivery to the spleen after being injected intravenously. 

Inside the spleen, the particles encounter antigen-presenting cells, including dendritic cells. Within 24 hours, these cells begin expressing IRF8 and NIK, and both of these pathways help drive dendritic cells to mature and become activated so that they can prime an anti-tumor response. 

Over a few days to a week, the T-cell population expands. These T cells, along with other immune cells such as natural killer (NK) cells, can then recognize and attack tumors.

“Most cancer immunotherapies rely on external signals to activate immune cells. We take a different approach — reprogramming immune cells from within by targeting their internal signaling machinery, enabling a more potent and durable anti-tumor response,” Das says. 

Stronger T cells

The researchers tested the immune-remodeling mRNAs in several mouse models of cancer, including an aggressive bladder cancer, colon carcinoma, melanoma, and metastatic lung cancer. In nearly all of these mice, the injected mRNA stimulated a strong T-cell response that significantly slowed tumor growth and in many cases completely eradicated the tumors. This happened even when the mice were not given a vaccine against a specific cancer antigen. When they were, the response was even stronger.

“We showed that you can get an anti-cancer response with these adjuvants without including the antigen, just by activating the immune system. However, cancer-specific antigens with the adjuvants in a vaccine further improved the responses,” Anderson says.

The mRNA adjuvant also enhanced the immune response to immunotherapy drugs called checkpoint blockade inhibitors. These drugs, which work by lifting a brake that tumor cells put on T cells, are FDA-approved to treat several kinds of cancer. These drugs don’t work for all patients, but combining them with the mRNA vaccine adjuvant could offer a way to make them more effective, the researchers say.

“The microenvironment of solid tumors is often hostile to T cells and represents a major barrier to effective immunotherapy. We find that immune remodeling with these adjuvants creates a T cell–permissive environment and promotes tumor rejection,” Garris says.

The researchers also explored whether their new adjuvant could boost the immune response to vaccination against viral infection. When they delivered the mRNA particles along with Covid or flu vaccines, they found that the vaccine generated a 10-to-15-fold stronger T cell response in the mice.

The researchers now plan to test this approach in additional animal models, in hopes of developing it for use in both cancer and infectious diseases. 

“While there are differences between the mouse systems that we’ve worked in and humans, we are optimistic that these adjuvants will work in humans and could improve a range of different vaccines,” Anderson says.

The research was funded by Sanofi, the National Institutes of Health, the Marble Center for Cancer Nanomedicine, and the Koch Institute Support (core) Grant from the National Cancer Institute.

A new way to spot signs of dark matter

Gravitational waves emitted by colliding black holes may bear imprints of dark matter, which physicists could detect with a new model.

Dark matter is thought to make up most of the matter in the universe, but the only way it interacts with its surroundings is through gravity. If two colliding black holes spiral through a dense region of dark matter and merge, gravitational waves rippling across space and time could carry an imprint of that dark matter.

Now, physicists may be able to spot such imprints of dark matter in gravitational waves that are detected on Earth. 

Researchers at MIT and in Europe have developed a method that makes predictions for what a gravitational wave should look like if it were produced by black holes that moved through dark matter, rather than empty space. They applied the technique to publicly available gravitational-wave data previously recorded by LIGO-Virgo-KAGRA (LVK), the global network of observatories that detect gravitational waves from black hole mergers and other far-off astrophysical sources.

The researchers looked through the gravitational-wave signals recorded over the LVK’s first three observing runs. From 28 of the clearest signals, the team found that 27 originated from black holes that merged in a vacuum, as physicists expected. But the pattern of one signal, GW190728, showed possible signs of a dark matter imprint. 

The scientists emphasize that they have not detected dark matter. Rather, the new method offers a new way to screen gravitational-wave data for hints of dark matter, which physicists can then follow up and confirm with other techniques. 

“We know that dark matter is around us. It just has to be dense enough for us to see its effects,” says Josu Aurrekoetxea, a postdoc in the MIT Department of Physics. “Black holes provide a mechanism to enhance this density, which we can now search for by analyzing the gravitational waves emitted when they merge.”

Aurrekoetxea and his colleagues report their results in a study appearing today in Physical Review Letters. The study’s co-authors are LVK member Soumen Roy of Université Catholique de Louvain (UCLouvain) in Belgium, Rodrigo Vicente of the University of Amsterdam, Katy Clough of Queen Mary University of London, and Pedro Ferreira of Oxford University. 

A dark pull

Dark matter is an invisible, hypothetical form of matter that, unlike normal everyday matter, has no interactions with the electromagnetic force. Dark matter can pass through light, magnetic fields, and any other form of energy along the electromagnetic spectrum without leaving a trace. The only evidence that dark matter exists is through its apparent interaction with one other force: gravity. 

By observing how gravity bends around distant galaxies, astronomers have surmised that there must be an extra force, outside of the galaxies’ own gravitational pull, to explain the bending fields, or “lensing.” This extra force, physicists suspect, is dark matter, which could account for over 85 percent of the matter in the universe. But exactly what dark matter is is a matter of huge debate, with theories for dark matter particles that range widely in particle size and properties. 

One class of proposed dark matter consists of “light scalar” particles, whose masses are many orders of magnitude lighter than an electron. Theorists predict that such dark matter should behave not just as particles, but also as coordinated waves when moving near black holes.

When waves of dark matter come in contact with a rapidly spinning black hole, physicists predict that the black hole's rotational energy can be transferred to the dark matter, amplifying it. This phenomenon, known as superradiance, would whip up the waves to extremely high densities of dark matter, akin to churning cream into butter.

At high enough densities, light scalar dark matter, which is invisible by all other accounts, should leave an imprint on the gravitational waves that reverberate from the colliding black holes. 

But exactly what would that imprint look like? And could such an imprint be detectable in gravitational waves that arrive on Earth, from black holes that merged many millions of light years away? 

For answers to those questions, Aurrekoetxea and his colleagues developed a model to predict the gravitational waveform, or the pattern of gravitational waves that two black holes would produce, if they collided in an environment of dark matter, versus in a vacuum (empty space, with no dark matter). 

An imprint’s prediction

For their new study, the team performed detailed numerical simulations to predict the gravitational wave that would be produced given various properties of two colliding black holes — a system known as a “black hole binary.” They considered black hole binaries across a range of scenarios and properties, for example, varying the size and mass of each black hole, the environment of dark matter that the black holes might pass through, and the density of the dark matter that the black holes would spin up. 

They designed the model to predict what a gravitational wave from a black hole binary would look like if it carried an imprint of dark matter, and furthermore, what that wave would look like if it traveled a given distance across space and time, to eventually arrive at a detector on Earth.

With their model, they looked to see whether any gravitational-wave signals that have been detected on Earth match their predicted patterns of dark matter imprints. To do so, they applied the model to publicly-available data recorded by LVK over the observatories’ first three observing runs. The observatories have picked up hundreds of gravitational-wave signals during this period. For their purposes, the researchers focused on the clearest signals, comprising gravitational waves from 28 separate events. 

For each event, the team compared the pattern of the actual gravitational wave against their model of what the signal would look like if it were generated by the same event in an environment of dark matter. They also compared the gravitational wave to the more expected scenario in which the signal was produced in a vacuum. 

Of the 28 clearest signals that they analyzed, 27 were solidly within the predictions for having been produced in a vacuum. However, the pattern of one event, GW190728, showed a “preference,” or an agreement with the team’s dark matter model. In other words, the signal may carry an imprint of dark matter. 

GW190728 is a gravitational wave that is named after the date that it was detected — on July 28, 2019. Scientists previously determined that the gravitational wave originated from a black hole binary with a total mass of about 20 times the mass of the sun. With their model, the team showed that such a system could have merged through a dense cloud of dark matter and produced a similar gravitational wave to GW190728. 

“The statistical significance of this is not high enough to claim a detection of dark matter, and further checks should be performed by independent groups,” Aurrekoetxea says. “What we think is important to highlight is that without waveform models like ours, we could be detecting black hole mergers in dark matter environments, but systematically classifying them as having occurred in vacuum.”

“We now have the potential to discover dark matter around black holes as the LVK detectors keep collecting data in the coming years,” says co-author Soumen Roy, who led the data analysis part of the work. “It is an exciting time to search for new physics using gravitational waves.”

“Using black holes to look for dark matter would be fantastic,” adds co-author Rodrigo Vicente, who developed the analytical model of the signal. “We would be able to probe dark matter at scales much smaller than ever before.”

This work was supported, in part, by the U.S. National Science Foundation and MIT’s Center for Theoretical Physics — a Leinweber Institute.

Powerful shrinking technique could enable devices that compute with light

MIT researchers created tiny 3D photonic devices with features small enough to channel visible light.

Using a new technique that can create vacancies at any site across a material and then shrink it to about 1/2,000 of its original volume, MIT researchers have designed nanotechnology devices that could be used for optical computing and other applications involving the manipulation of visible light.

The new fabrication technique, known as “implosion carving,” allows researchers to imprint features throughout a hydrogel using photopatterning. If patterned with a resolution of about 800 nanometers, these features can then be shrunk to less than 100 nanometers. 

Because that resolution is smaller than the wavelength of light, the devices can bend light in specific ways that allow them to perform optical computations.

“In order to enable nanophotonic applications in visible light, we need to make nanostructures with feature sizes with a resolution less than 100 nanometers. Only in that way can we precisely create the structure that can manipulate visible light,” says Quansan Yang, a former MIT postdoc, now an assistant professor at the University of Washington, and one of the lead authors of the new study.

In their paper, the researchers demonstrated a photonic device that can perform a simple digit-classification task, but future versions could be used for high-speed imaging and information processing, they say.

Gaojie Yang, a former MIT postdoc, is the co-lead author of the paper, which appears today in Nature Photonics. The paper’s senior authors are Peter So, director of the MIT Laser Biomedical Research Center (LBCR) and an MIT professor of biological engineering and mechanical engineering, and Edward Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT and a professor of biological engineering, media arts and sciences, and brain and cognitive sciences. Boyden is also a Howard Hughes Medical Institute investigator and a member of MIT’s McGovern Institute for Brain Research, the Yang Tan Collective, and Koch Institute for Integrative Cancer Research.

Nanoscale feature sizes

Photonic devices, which transmit and manipulate light, hold potential for use as optical computer chips that could offer an energy-efficient alternative to semiconductor chips. However, existing techniques for creating 3D photonic devices haven’t yet achieved the 100-nanometer resolution that is needed to channel visible light, which has wavelengths between 380 and 750 nanometers.

Using an additive manufacturing technique called two-photon lithography, researchers can use light to create 3D nanoscale features, but with a resolution larger than 100 nanometers. Another technique, known as electron-beam lithography, can be used to etch smaller-resolution features onto a silicon chip, but it doesn’t generate 3D structures. 

To make 3D devices with the necessary feature size, the researchers extended the concept of “implosion fabrication,” which Boyden’s lab developed in 2018, to create a new variant called “implosion carving.” In implosion carving, a laser creates vacancies — tiny voids where the hydrogel material has been removed — at precisely targeted locations. These vacancies exhibit different optical properties than the surrounding hydrogel. The hydrogel is then shrunk to bring the patterned features down to the nanoscale.

The carving process begins with immersing the hydrogel in a photosensitizing dye. Then, the researchers use a laser to excite the photosensitizer at specific places in the gel, which in turn generates reactive oxygen species that cut the bonds holding the hydrogel together. This creates a vacancy in that spot.

Once the desired vacancy pattern has been carved into the hydrogel, the researchers shrink it using a two-step process. First, they soak it in a solution containing ions, which causes it to shrink about tenfold in each dimension. To shrink it a little more, and to remove the watery solution, the hydrogel then undergoes a process called supercritical drying, which can remove liquid from a gel without damaging it.

At the end of the process, the hydrogel has been shrunk more than tenfold in each dimension, leading to a 2,000-fold reduction in volume. 

Computing with light

To demonstrate the versatility of this technique, the researchers used it to create several 3D shapes, including a helix and a structure inspired by a butterfly wing. Some of these structures are too thin, and have too high an aspect ratio, to be stably created using conventional two-photon lithography.

The researchers also created a device that could perform a simple calculation known as digit classification, a task that is traditionally used to test the performance of neural networks. During this task, the device was presented with a digit, such as 1 or 5, and had to light up a specific location to indicate which number was detected.

To achieve this, the researchers patterned vacancies throughout the device so that it would act like a neural network. The pattern of vacancies would diffract input light as it passed through many layers of patterned hydrogel, so that the output light was determined by the shape of the digit that was entered into the system.

“This is a purely optical system that effectively performs optical computing,” So says. 

“One of the very attractive features of this technology is that you can manipulate the property of the material at every tiny location,” says Dushan Wadduwage, an assistant professor at Old Dominion University and former MIT postdoc, who is also an author of the paper. “You have millions of different locations that you need to decide the property of, and that turns into a really interesting design problem where we can use deep-learning algorithms to find designs over these millions of parameters and come up with parts that go into optical systems in new ways.”

The researchers now plan to use the same principles to build optical devices that could classify cells based on their state as they flow through a microfluidic device. This could help identify rare cells such as circulating tumor cells in a blood sample, they say. 

This approach could also enable the creation of high-throughput imaging techniques for applications such as analyzing tissue samples from biopsies or surgical specimens. And, if adapted to work with other materials such as hydrophobic polymers, it could also be used to create channels within 3D nanofluidic devices. 

Other authors of the paper include Gaojie Yang, Takahiro Nambara, Hiroyuki Kusaka, Yuichiro Kunai, Alex Matlock, Corban Swain, Brett Pryor, Yannick Salamin, Daniel Oran, Hasindu Kariyawasam, Ramith Hettiarachchi, and Marin Soljacic. 

The research was funded, in part, by the MIT-Fujikura Partnership Fund, the U.S. Army Research Office through the Institute for Soldier Nanotechnologies at MIT, Lisa Yang and Y. Eva Tan, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the U.S. National Institutes of Health.

Improving the reliability of circuits for quantum computers

A new technique helps scientists measure a phenomenon that can cause quantum circuits to perform differently than expected, increasing the error in computations.

Quantum computers could someday solve pressing problems that are too convoluted for classical computers, such as modeling complex molecular interactions to streamline drug discovery and materials development. 

But to build a superconducting quantum computer that is large and resilient enough for real-world applications, scientists must precisely engineer thousands of quantum circuits so they perform operations with the lowest possible error rate.

To help scientists design more predictable circuits, researchers from MIT and Lincoln Laboratory developed a technique to measure a property that can unexpectedly cause a superconducting quantum circuit to deviate from its expected behavior. Their analysis revealed the source of these distortions, known as second-order harmonic corrections, leading to underperforming circuit architectures.

The MIT researchers fabricated a device to detect second-order harmonic corrections, identify their origin, and precisely measure their strength. This technique could help scientists deliberately design quantum circuits that can counteract the effects of these deviations.

This is especially important in larger and more complicated quantum circuits, where the negative impact of second-order harmonic corrections can be amplified. 

“As we make our quantum computers bigger and we want to have more precise control over the parameters of these devices, identifying and measuring these effects is going to be important for us to have a precise understanding of how these systems are constructed. It is always important to keep diving down into the circuit to see if there is an effect you didn’t expect, which impacts how your device is performing,” says Max Hays, a research scientist in the Engineering Quantum Systems (EQuS) group of the Research Laboratory of Electronics (RLE) and co-lead author of a paper on this research.

Hays is joined on the paper by co-lead author Junghyun Kim, an electrical engineering and computer science (EECS) graduate student in the EQuS group; senior author William D. Oliver, the Henry Ellis Warren (1894) Professor of EECS and professor of physics, leader of the EQuS group, director of the Center for Quantum Engineering, and associate director of RLE; as well as others at MIT and Lincoln Laboratory. The research appears today in Nature Physics.

A pair-wise problem

In a quantum computer that utilizes superconducting circuits, which is one of many potential computing platforms, Josephson junctions are critical elements that enable the transfer and manipulation of information. These devices utilize two superconducting wires that are brought very close together, with a nanometer-scale barrier between them. Like a traditional circuit, the electric charge in Josephson junctions is carried by electrons. 

But in a superconducting circuit, charge-carrying electrons pair up, forming what are called Cooper pairs. These Cooper pairs can “quantum tunnel” through the barrier between the two wires, transporting current from one wire to the other.

Cooper pairs can usually only tunnel one pair at a time, which is a key property that makes quantum computation possible. 

“If you try to force more Cooper pairs through, it just doesn’t work. This non-linear effect is extremely important for all our circuits. If we didn’t have that effect, then we wouldn’t be able to control or manipulate any quantum information that we store in these circuits,” Hays explains.

But sometimes, Cooper pairs can unexpectedly squeeze through the barrier two at a time, an effect that is known as a second-order harmonic correction. This effect limits the performance of a quantum circuit that has been configured to only allow single-pair tunneling.

“If two Cooper pairs tunnel at the same time, then the assumption we used to build our circuit doesn’t apply anymore. We need to fix the circuit so it can handle that,” Kim says.

But before they can fix the circuit, scientists need to know the source and strength of these distortions.

To obtain this information, the MIT researchers fabricated a quantum circuit so it would be very sensitive to these effects. Essentially, the device is designed to suppress the quantum tunneling process of single Cooper pairs, while allowing the two-pair tunneling process to continue. 

In this way, they can detect the presence of second-order harmonic corrections and precisely measure their strength. 

Straight to the source

They can also use this circuit to pinpoint the source of these harmonics, which helps researchers identify the best way to correct for them. 

There are two potential sources of second-order harmonics — one source is intrinsic to the dynamics of the Josephson junction and the other is caused by the wires connecting the junction to other circuit elements. 

While prior research had indicated the second-order harmonics could be due to the dynamics of the junction, the MIT researchers found that additional inductance — the tendency to oppose changes in the flow of electric current —from wires in the circuit was the actual source in their devices. 

“This is important because, if we know where the second-order harmonic correction is coming from, we can predict how strong it is likely to be, and use that information to engineer more predictable circuits that will hopefully perform better,” Hays says.

In the future, the researchers want to design experiments that more accurately predict how a device will perform when second-order harmonic corrections occur. They also want to study other sources of second-order harmonic corrections and whether those sources could have negative impacts on a circuit under different fabrication conditions.

This work is funded, in part, by the U.S. Department of Energy, the U.S. Co-design Center for Quantum Advantage, the U.S. Air Force, the Korea Foundation for Advanced Studies, and the Intelligence Community Postdoctoral Research Fellowship Program at MIT. 

For most US drivers, EVs offer emissions benefits and cost savings

When it comes to emissions, individual driving patterns matter as much as how “green” the regional electricity mix is, MIT researchers report.

Despite regional variability in climate, electricity sources, congestion, and the wide variation in individual driving patterns, electric vehicles generate less greenhouse gas emissions and do not cost more than comparable gas-powered vehicles for drivers and vehicle fleet owners in most parts of the United States, according to a new study by MIT researchers.

The team’s approach captures many key factors that contribute to regional and individual differences in the life-cycle emissions and ownership cost of electric vehicles, including meteorological data, the distance and duration of trips, and fuel prices.

To paint a fuller picture of emissions and costs than was previously available, the researchers sourced data from thousands of U.S. zip codes and drilled down to the level of individual drivers within those locations. Their study considers time-averaged fuel prices so as not to be overly influenced by fluctuations in prices at any one point in time. They finalized their analysis at the end of 2024 and early 2025.

Their results indicate that a person’s driving behaviors can matter as much as regional factors like the local electricity mix when it comes to the emissions savings of an electric vehicle, compared to a similar gas-powered vehicle. In most locations, a battery-electric vehicle reduces emissions between 40 and 60 percent, with larger impacts in urban areas. 

They also found that colder climates do not reduce overall emission benefits as much as some media reports assume.

The researchers utilized this detailed analysis to update a public tool they previously developed, carboncounter.com, which enables individuals to compare the life-cycle emissions and total ownership costs of nearly any car on the market. A new version of carboncounter.com is also being released today.

“There are a lot of statements being thrown around, like that electric vehicles don’t reduce emissions very much in cool climates, and we wanted to analyze these factors systematically and evaluate these statements against one another simultaneously. Rather than simply asking, ‘Are EVs better?’, this paper helps answer ‘better for whom, and under what conditions?’” says Marco Miotti PhD ’20, a senior researcher at ETH Zurich who completed this research while a graduate student in the Institute for Data, Systems, and Society (IDSS) at MIT. 

He is joined on the paper by senior author Jessika Trancik, a professor in IDSS. The research appears today in Environmental Research Letters.

A holistic approach

Many prior studies that compare emissions and costs of electric vehicles (EVs) to combustion-engine vehicles cover a few factors, like the amount of renewable energy in the grid and how gas prices impact affordability, Miotti says.

“To our knowledge, there have been few efforts so far that bring all these factors together. But if someone wants to buy a car and have a better understanding of the factors that affect emissions and costs, this holistic approach is important,” he adds.

The researchers focused on two types of EVs: battery-electric vehicles, which only operate on electricity, and plug-in hybrid electric vehicles, which also have a combustion engine that works in tandem with the battery to optimize fuel savings.

The team expanded and improved a set of previously developed vehicle cost and emissions models to incorporate a wider variety of factors and data types.

For instance, they refined an existing model that estimates energy use and gas mileage so it could capture more nuances of local climate variability. 

“But the real effort was not just in extending these different models, but in bringing together all these different data and making them work with the models in a consistent manner,” Miotti says.

The team sourced data on a wide variety of factors for each U.S. zip code, such as typical drive cycles, the amount of traffic, local gas and electricity prices, makeup of the regional electricity mix, meteorological profiles, and more. They used statistical approaches to amalgamate different types of data. 

For example, the team used a probabilistic matching technique to combine data on how often people drive, which was drawn from nationwide travel surveys, with more detailed GPS data that includes factors like drivers’ acceleration patterns and the distance they usually drive on each day of the week.

The researchers designed their analysis to focus on the spatial picture of emissions and costs, based on U.S. zip codes, while simultaneously considering the impact of the size and features of each specific vehicle model.

“At the end of the day, it’s the vehicle and fleet owners who make decisions about vehicle purchases. So, we wanted to make sure to consider their wide-ranging individual perspectives rather than simply performing a region-by-region comparison,” says Trancik.

Lower emissions, comparable costs

In the end, their modeling framework revealed that all factors they analyzed matter about equally in determining emissions-reduction potential of EVs compared to internal combustion vehicles. 

EVs reduce emissions the most in areas with a cleaner electricity mix, denser traffic, higher annual travel distances, and a mild climate, in decreasing order of importance. In each area, emission reductions increase for drivers who drive more often, drive larger vehicles, and are more frequently stuck in traffic. 

In a colder area like North Dakota, fuel economy of battery-electric vehicles might be reduced by as much as 50 percent on a particularly frigid night, but the effect on annual emission benefits is minimal. 

“We even did a sensitivity study to see if the range is reduced in very cold climates, and we found that, even in the most unfavorable conditions, EVs still reduce emissions by a substantial amount,” Miotti says.

On the cost side, the models show that, in most places across the U.S., EVs are competitive with comparable combustion-engine vehicles in terms of lifetime ownership cost, even without clean vehicle tax credits. And in areas where electricity is relatively affordable, battery-electric vehicles tend to cost less than their plug-in hybrid or combustion-engine counterparts.

In the future, the researchers want to expand this analysis to include a temporal dimension, so the framework also considers how changes in vehicle, fuel, and electricity prices affect emissions and costs over time. 

“While we found that the electricity mix is a big driver of the spatial variation in emissions savings of EVs, the electricity grid is decarbonizing everywhere. As that happens, emissions savings across space will become more homogenous for EVs, but the differences across one driver to another will remain,” Miotti says.

They could also use the framework to explore regions outside the United States or incorporate data on hybrid-electric vehicles that cannot be plugged in.

This work was funded, in part, by the MIT Martin Family Society of Fellows for Sustainability.

Mapping the ocean with autonomous sensors

Founded by Ravi Pappu SM ’95, PhD ’01, Apeiron Labs is deploying low-cost ocean sensors to improve storm forecasts, detect endangered species, and more.

In late October 2025, Tropical Storm Melissa moved through the Caribbean Sea with moderate winds that didn’t get much attention. But on Oct. 25, aided by a patch of warm ocean, the storm rapidly intensified. By the time it made landfall in Jamaica, it was one of the strongest Atlantic hurricanes on record, uprooting trees, tearing the roofs from buildings, and causing catastrophic flooding and power outages.

Ravi Pappu SM ’95, PhD ’01 blames the surprise on our inability to gather high-quality ocean data.

“The storm intensified because of a small pool of hot water in the Caribbean Ocean that fed it energy,” Pappu explains. “These pools are everywhere. They can be hundreds of kilometers wide and are literally invisible to us. If we knew about that pool, we could say very precisely how the hurricane would intensify and better deal with it.”

Pappu thinks he has a way to solve that problem. He is the founder of Apeiron Labs, a company deploying low-cost autonomous ocean sensors to capture more data, in more places, and at a lower cost than is possible today. The company’s devices roam the ocean up to a quarter mile below the surface and continuously gather data on temperature, acoustics, salinity, and more, providing a real-time look at one of the planet’s last known mysteries. He says the sensors can do for the ocean what small, modular CubeSat satellites did for Earth observation from space.

When the devices are ready to be recharged, trackers make it easy to scoop them from the ocean surface. Pappu envisions the recovery process being done by autonomous boats in the future.

“Humanity needs ocean measurements, and we need them at a scale that has never been attempted before,” Pappu says. “It’s a massively hard problem. In the last century, oceanographers resigned themselves to calling it the century of undersampling. If we are successful, we will have a much more fine-grained understanding of our oceans and how they impact humans. That’s what drives us.”

Homework

Pappu came to MIT after completing a 10-year homework assignment. It started when he was a child in India in the 1980s, when he saw a hologram on the cover of National Geographic for the first time.

“I was so taken by it that I decided I needed to learn how to make those three-dimensional images,” Pappu recalls. “I learned what I could by reading books and papers. I didn’t know who invented the hologram until I read a book about MIT’s Media Lab. The book named the person who invented the rainbow hologram, so I wrote him a letter. I didn’t know his address, so I just wrote on the envelope, ‘Steve Benton, holography researcher, MIT, USA.’”

To Pappu’s surprise, the letter reached Benton, and the former Media Lab professor even wrote back with some further topics he needed to learn about.

Pappu never forgot that. He earned a bachelor’s degree in electrical engineering in India, then earned his master’s degree at Villanova University, taking all the optics classes he could.

“Eventually, about 10 years after I saw my first hologram, I wrote to Steve and I said, ‘I did all these things you asked me, now I want to study with you,’” Pappu says. “That’s how I got into MIT.”

Pappu studied under Benton for the next three years. He also studied under Professor Neil Gershenfeld as part of his PhD. Following graduation, Pappu and four classmates started ThingMagic, a consulting company that eventually sold RFID readers. ThingMagic was acquired 2010. Pappu returned to MIT for two years as a visiting scientist around the time of the acquisition.

Following that experience, Pappu worked at In-Q-Tel, an organization that invested in ThingMagic and other companies with potential to advance national security. It was there that Pappu realized how badly the world needed large-scale, inexpensive ocean sensing.

“All of the ocean sensing up to that point, and even today, was about making a really expensive thing that cost $20 million, goes to the bottom of the ocean, and stays there for five years,” Pappu says. “We needed things that are cheap and scalable to deploy wherever you need them for as long as you want.”

Pappu officially founded Apeiron Labs in 2022.

“What we’re focused on is figuring out how the ocean works,” Pappu says. “How warm is it? What is the pH? How salty is it? These things vary from place to place every 10 kilometers or so. It varies over time, and it varies by season. If we knew the details of the ocean with the same fidelity we have for the atmosphere, we would be able to tell exactly when and where hurricanes hit. It would mean less uncertainty.”

Apeiron’s ocean-sensing devices are each 3 feet long and about 20 pounds. They’re designed to be dropped off a boat or plane with biodegradable parachutes and stay in the ocean for six months. Each device continuously sends data to the cloud, is controllable through a cloud-based ocean operating system, and is accessible on a mobile phone.

“We lower the carbon footprint and cost of gathering ocean data because everything else needs a diesel ship — and a fully crewed ship costs $100,000 a day,” Rappu says. “By the time you collect the first data in the old model, you’ve already committed to a lot of money in addition to millions of dollars for the sensors. “

The company’s devices currently have two types of sensors: one for measuring salinity, temperature, and depth, and the other that uses a hydrophone to passively listen for things like submarines and whales.

That could be used to detect the low-frequency calls and clicks of endangered whales and other fish species. Currently, fishermen must look for whales manually with spotters on ships or planes. The data could also be used to improve weather forecasts, monitor noise from offshore energy projects, and track currents.

“Currents are determined by temperature and salinity, so if there’s an oil spill, our data could help determine where that spill is going,” Pappu says. “Or if you’re a fisherman, knowing where the water changes from warm to cold, which is where the fish hang out, is very useful.”

An ocean of possibilities

Apeiron Labs has worked with government defense agencies including the U.S. Navy over the last two years. The company has also tested its devices off the coast of California and in the Boston Harbor.

“The most important thing is, when we show people our approach and what we’ve demonstrated so far, they are no longer asking, ‘Can it be done?’ they’re asking, ‘What can we do with it?’” Pappu says. “Our customers have spent decades working in the ocean and they understand how novel these capabilities are.”

Of all the possibilities, improved storm forecasting could be the one Pappu is most excited about.

“Our mission is to lower the barriers to ocean data,” Pappu says. “The ocean is a huge determinant of weather, climate, and short-term forecasting. Despite our best efforts to predict the intensity of storms, sudden changes are still the norm, and much of that comes down to a lack of understanding of our oceans. If we were monitoring these things over long periods of time and finer spatial scales, we could see these storms coming much earlier with more certainty.”

MIT student Jack Carson named 2026 Udall Scholar

The Udall Foundation identifies and rewards future leaders in tribal public policy, Indigenous health policy, and the environment.

Jack Carson, a second-year undergraduate at MIT majoring in electrical engineering and computer science, has been named a 2026 Udall Scholar, one of up to 65 undergraduates nationally to receive the prestigious $7,500 award. 

The Udall Scholarship honors students who have demonstrated a commitment to the environment, Indigenous health care, or tribal public policy. Carson is only the third MIT student to win this award, and the first to win for tribal policy.

Carson, a member of the Cherokee Nation and resident of Oklahoma, exemplifies the multidisciplinary approach to problem-solving that the Udall Scholarship seeks to honor. His work spans artificial intelligence, biomedical research, Indigenous community development, and ethics.

"Jack is the type of leader the Udall Foundation exists to support," says Kim Benard, associate dean for distinguished fellowships. "He's not only conducting cutting-edge research, but he's actively creating opportunities for Indigenous students to enter tech fields."

At MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), Carson works in the Barzilay Lab, developing multiomics models for personalized therapeutic target identification. His work on deep learning and statistical physics has resulted in a sole-author paper published at the International Conference on Machine Learning (ICML).

Carson founded Code.Tulsa, a summer technology program designed to introduce Indigenous high school students to computer science and tech careers. The initiative addresses a significant gap: Indigenous communities remain highly underrepresented in technology fields, despite the potential for tech to advance tribal sovereignty and economic development.

This year, Carson won the Elie Wiesel Prize in Ethics Essay Contest. He is an accomplished musician who has performed at Carnegie Hall and with the National Opera, a motorcycle racer, and a self-described philosopher deeply committed to questions of justice and responsibility.

Photonics advance could enable compact, high-performance lidar sensors

With a novel design, MIT researchers overcame a stubborn problem that has limited the effectiveness of chip-based systems for lidar.

Lidar systems use pulses of infrared light to measure distance and map a 3D scene with high resolution, allowing autonomous vehicles to rapidly react to obstacles that appear in their path. But traditional lidar sensors are expensive, bulky systems with many moving parts that degrade over time, limiting how the sensors can be deployed.

A new study from MIT researchers could help to enable next-generation lidar sensors that are compact, durable, and have no moving parts. The key advance is a novel design for a silicon-photonics chip, which is a semiconductor device that manipulates light rather than electricity. 

Typically, such silicon-photonics chip-based systems have a restricted field of view, so a silicon-photonics-based lidar would not be able to scan angles in the periphery. Existing workarounds to this problem increase noise and hamper precision.

To avoid these drawbacks, the MIT researchers designed and demonstrated an array of integrated antennas that minimizes unwanted crosstalk between the antennas. Their innovation allows a lidar chip to scan a wider field of view while maintaining low-noise operation compared to other silicon-photonics-based approaches.

This novel demonstration could fuel the development of advanced lidar sensors for demanding applications like autonomous vehicle navigation, aerial surveying, and construction site monitoring.

“The functionality we demonstrated in this work solves a fundamental problem for integrated optical-phased-array technology, enabling future lidar sensors that can achieve significantly higher performance than we could demonstrate previously,” says Jelena Notaros, the Robert J. Shillman Career Development Associate Professor of Electrical Engineering and Computer Science (EECS) at MIT, a member of the Research Laboratory of Electronics, and senior author of a paper on this innovation.

She is joined on the paper by lead author and EECS graduate student Henry Crawford-Eng as well as EECS graduate students Andres Garcia Coleto, Benjamin M. Mazur, Daniel M. DeSantis, and Tal Sneh. The research appears today in Nature Communications.

Adjusting an antenna array

Many traditional lidar systems map a scene using a bulky box that spins to send pulses of light in multiple directions. The light bounces off nearby objects and returns to the sensor, providing data that are used to reconstruct the environment. 

Instead, silicon-photonics-based lidar sensors systematically scan an emitted light beam in multiple directions non-mechanically using a system called an integrated optical phased array (OPA).

Key to an OPA is an array of integrated antennas that have tiny perturbations placed periodically along their length. These corrugations allow the antenna to scatter light from an input source up and out of the photonic chip.

By adjusting the phase of light routed to each antenna, the researchers can change the angle at which the light is emitted out of the array. In this way, they can steer the beam with no moving parts.

But if engineers place the antennas too close together, the antennas will couple with each other and the light they emit will get jumbled. To avoid this, scientists typically space the antennas farther apart, but this also has downsides.

If the antennas are spaced too far apart, the array will emit multiple copies of the light beam at different angles. The researchers can only steer the primary beam so far in either direction until it is undiscernible from its neighboring copies.

“This limits our field of view, so the autonomous vehicle now only knows what is in front of it for a certain angular range,” Garcia Coleto explains.

These beam copies, known as grating lobes, can cause false positives by confusing the sensor. They also waste power.

The MIT researchers solved this problem by designing a set of reduced-crosstalk antennas that can be placed close together without causing a significant coupling effect.

In a standard OPA, all the antennas have the same design, meaning the same arrangement of corrugations. These identical antennas couple very strongly when placed close together.

To address this fundamental roadblock, the MIT researchers designed a set of three antennas with different geometries, varying the width of each antenna and the size and arrangement of corrugations. With varied geometries, each antenna has a different propagation coefficient, which determines how light travels down the antenna.

“Because the antennas have very different propagation coefficients, when we put them close together, essentially each antenna doesn’t ‘see’ the antenna next to it. Therefore, it won’t couple with its neighbor,” Garcia Coleto says. 

A photonic balancing act

But even though the antennas have different propagation coefficients, the researchers still need them to emit light in the same way. 

They achieved this by carefully designing the antennas to meet three parameters. 

First, each antenna must emit the same amount of light. Second, each antenna must emit a beam at the same angle for the same wavelength of light. Third, the emission angle must change uniformly across the array as the researchers steer it.

“We have this challenge where we require the antennas to have different geometries to reduce the crosstalk, but we need to simultaneously design the antennas to have the same emission characteristics. While it is possible to engineer this, it is extremely difficult because, typically, when antennas are designed with different geometries, they tend to behave differently,” Crawford-Eng says.

The researchers first developed the fundamental electromagnetic theory behind how radiative modes couple. They used that theory as a guide to design and simulate their antennas.

Building on those analyses, they fabricated the OPA with reduced-crosstalk antennas spaced significantly closer than they would be in a traditional OPA, then experimentally tested the system.

While a typical OPA would have coupling of about 100 percent in this experiment, their OPA reduced coupling to about 1 percent while generating a single, precise beam. Using this design, they demonstrated accurate beam steering across a wide field of view without any grating lobes. 

In the future, the researchers plan to further improve their technique to enable an even wider field of view. In addition, they are exploring a new potential solution to wide field-of-view functionality that they discovered while developing the underlying theory.

“This work addresses a longstanding challenge in integrated optical phased arrays: simultaneously achieving both a wide field of view, which requires dense antenna spacing, and high beam quality, which requires low crosstalk between neighboring antennas. The authors solve this problem with an elegant antenna design. Their innovation is an important step forward for chip-scale, solid-state beam-steering technology,” says Joyce Poon, professor of electrical and computer engineering at the University of Toronto and director of the Max Planck Institute of Microstructure Physics, who was not involved with this work.

This research was supported, in part, by the Semiconductor Research Corporation, the National Science Foundation, an MIT MathWorks Fellowship, the U.S. Department of War, and the MIT Rolf G. Locher Endowed Fellowship.

The work was conducted, in part, using MIT.nano facilities.

Study: Firms often use automation to control certain workers’ wages

MIT economists found US companies tend to target employees earning a “wage premium,” which increases inequality but not necessarily productivity.

When we hear about automation and artificial intelligence replacing jobs, it may seem like a tsunami of technology is going to wipe out workers broadly, in the name of greater efficiency. But a study co-authored by an MIT economist shows markedly different dynamics in the U.S. since 1980. 

Rather than implement automation in pursuit of maximal productivity, firms have often used automation to replace employees who specifically receive a “wage premium,” earning higher salaries than other comparable workers. In practice, that means automation has frequently reduced the earnings of non-college-educated workers who had obtained better salaries than most employees with similar qualifications. 

This finding has at least two big implications. For one thing, automation has affected the growth in U.S. income inequality even more than many observers realize. At the same time, automation has yielded a mediocre productivity boost, plausibly due to the focus of firms on controlling wages rather than finding more tech-driven ways to enhance efficiency and long-term growth.

“There has been an inefficient targeting of automation,” says MIT’s Daron Acemoglu, co-author of a published paper detailing the study’s results. “The higher the wage of the worker in a particular industry or occupation or task, the more attractive automation becomes to firms.” In theory, he notes, firms could automate efficiently. But they have not, by emphasizing it as a tool for shedding salaries, which helps their own internal short-term numbers without building an optimal path for growth.

The study estimates that automation is responsible for 52 percent of the growth in income inequality from 1980 to 2016, and that about 10 percentage points derive specifically from firms replacing workers who had been earning a wage premium. This inefficient targeting of certain employees has offset 60-90 percent of the productivity gains from automation during the time period.

“It’s one of the possible reasons productivity improvements have been relatively muted in the U.S., despite the fact that we’ve had an amazing number of new patents, and an amazing number of new technologies,” Acemoglu says. “Then you look at the productivity statistics, and they are fairly pitiful.”

The paper, “Automation and Rent Dissipation: Implications for Wages, Inequality, and Productivity,” appears in the May print issue of the Quarterly Journal of Economics. The authors are Acemoglu, who is an Institute Professor at MIT; and Pascual Restrepo, an associate professor of economics at Yale University.

Inequality implications

Dating back to the 2010s, Acemoglu and Restrepo have combined to conduct many studies about automation and its effects on employment, wages, productivity, and firm growth. In general, their findings have suggested that the effects of automation on the workforce after 1980 are more significant than many other scholars have believed. 

To conduct the current study, the researchers used data from many sources, including U.S. Census Bureau statistics, data from the bureau’s American Community Survey, industry numbers, and more. Acemoglu and Restrepo analyzed 500 detailed demographic groups, sorted by five levels of education, as well as gender, age, and ethnic background. The study links this information to an analysis of changes in 49 U.S. industries, for a granular look at the way automation affected the workforce. 

Ultimately, the analysis allowed the scholars to estimate not just the overall amount of jobs erased due to automation, but how much of that consisted of firms very specifically trying to remove the wage premium accruing to some of their workers. 

Among other findings, the study shows that within groups of workers affected by automation, the biggest effects occur for workers in the 70th-95th percentile of the salary range, indicating that higher-earning employees bear much of the brunt of this process. 

And as the analysis indicates, about one-fifth of the overall growth in income inequality is attributable to this sole factor.

“I think that is a big number,” says Acemoglu, who shared the 2024 Nobel Prize in economic sciences with his longtime collaborators Simon Johnson of MIT and James Robinson of the University of Chicago.

He adds: “Automation, of course, is an engine of economic growth and we’re going to use it, but it does create very large inequalities between capital and labor, and between different labor groups, and hence it may have been a much bigger contributor to the increase in inequality in the United States over the last several decades.” 

The productivity puzzle

The study also illuminates a basic choice for firm managers, but one that gets overlooked. Imagine a type of automation — call-center technology, for instance — that might actually be inefficient for a business. Even so, firm managers have incentive to adopt it, reduce wages, and oversee a less productive business with increased net profits.

Writ large, some version of this seems to have been happening to the U.S. economy since 1980: Greater profitability is not the same as increased productivity.

“Those two things are different,” says Acemoglu. “You can reduce costs while reducing productivity.” 

Indeed, the current study by Acemoglu and Restrepo calls to mind an observation by the late MIT economist Robert M. Solow, who in 1987 wrote, “You can see the computer age everywhere but in the productivity statistics.” 

In that vein, Acemoglu observes, “If managers can reduce productivity by 1 percent but increase profits, many of them might be happy with that. It depends on their priorities and values. So the other important implication of our paper is that good automation at the margins is being bundled with not-so-good automation.” 

To be clear, the study does not necessarily imply that less automation is always better. Certain types of automation can boost productivity and feed a virtuous cycle in which a firm makes more money and hires more workers. 

But currently, Acemoglu believes, the complexities of automation are not yet recognized clearly enough. Perhaps seeing the broad historical pattern of U.S. automation, since 1980, will help people better grasp the tradeoffs involved — and not just economists, but firm managers, workers, and technologists. 

“The important thing is whether it becomes incorporated into people’s thinking and where we land in terms of the overall holistic assessment of automation, in terms of inequality, productivity and labor market effects,” Acemoglu says. “So we hope this study moves the dial there.”

Or, as he concludes, “We could be missing out on potentially even better productivity gains by calibrating the type and extent of automation more carefully, and in a more productivity-enhancing way. It’s all a choice, 100 percent.”

Method for stress-testing cloud computing algorithms helps avoid network failures

The “MetaEase” technique provides a heads-up to potential scenarios that could cause long wait-times or outages.

Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a cloud service outage that leaves millions of users unable to access applications. 

The technique uncovers hidden blind spots that might cause a shortcut algorithm to fail unexpectedly when it is deployed. 

This new approach can identify worse-case scenarios that an engineer might miss if they use a traditional method that compares an algorithm against a set of human-designed past test cases. It is also less labor-intensive than other verification tools that require engineers to rewrite an algorithm in a complex mathematical code each time they want to test it.

Instead of needing a mathematical reformulation, the new method reads the algorithm’s source code directly and automatically searches for worse-case scenarios that lead to the highest level of underperformance.

By helping engineers quickly and easily stress-test a networking algorithm before deployment, the method could catch failure modes that might otherwise only appear in a real outage. The technique could also be used to analyze the risks of deploying AI-generated code.

“We need to have good tools to measure the worse-case scenario performance of our algorithms so we know what could happen before we put them into production. This is an easy-to-use tool that can be plugged into current systems so we can find the best algorithm to use and ensure the worse-case scenarios are identified in advance,” says Pantea Karimi, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this new technique. 

She is joined on the paper by senior authors Mohammad Alizadeh, an associate professor of EECS and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Behnaz Arzani, a principal researcher at Microsoft Research; along with Ryan Beckett, Siva Kesava Reddy Karkarla, and Pooria Namyar, researchers at Microsoft Research; and Santiago Segarra, a professor at Rice University. The research will be presented at the USENIX Symposium on Networked Systems Design and Implementation. 

Assessing algorithms

In large systems like cloud servers, the tried-and-true algorithms that route data from one place to another or are often too computationally intensive to run in a feasible amount of time. 

So, engineers and researchers develop suboptimal algorithms called heuristics that can run much faster. However, there could be unexpected but plausible circumstances that will cause a heuristic to underperform or fail when deployed.

A heuristic can route millions of data requests across a cloud network in seconds, but under the wrong conditions — like an unusual traffic pattern or a sudden spike in demand — the shortcut can break down in ways the designer never anticipated.

When these problems occur, a company may have no choice but to drop some requests that can’t be processed. 

The firm could also deliberately allocate more resources in advance to head-off a potential disaster, leading to higher overall costs and wasted electricity from underutilization.

“This is really bad for a company because, either way, they are going to lose a lot of money. If this particular scenario hasn’t happened before and was never tested, how would a developer know in advance before it happens?” Karimi says.

Stress-testing heuristics typically involves running a new algorithm in simulation using a set of human-designed test cases and manually comparing the performance with a previous algorithm. But this is time-consuming and can leave blind spots if an engineer doesn’t know to test for certain situations.

Alternatively, engineers could use a verification tool to evaluate the performance of their heuristic more systematically. However, these tools require the engineer to encode the algorithm into a complex, mathematical formula that can take days to flesh out. The process, which doesn’t work for every type of heuristic, must be repeated each time the engineer changes the code.

Instead, the researchers developed a more user-friendly and efficient verification tool, called MetaEase, that analyzes the heuristic’s existing implementation code directly to identify the biggest risks of deploying it.

“This would reduce the friction of using these heuristic analysis tools,” Karimi says.

She began this work during an internship at Microsoft Research, where the team previously developed MetaOpt, a heuristic analyzer that requires engineers to rewrite their algorithms as formal optimization models. MetaEase grew out of the desire to remove that barrier.

Maximizing the gap

MetaEase is driven by two key innovations. First, it uses a technique called symbolic execution to map out the different decision points in the heuristic's code. These are places where the algorithm might behave differently depending on the input.

This technique produces a set of representative starting points, each corresponding to a distinct behavior the heuristic could exhibit.

Second, from these starting points, MetaEase utilizes a guided search to systematically move toward inputs that make the heuristic perform as poorly as possible, compared to the optimal algorithm.

In machine learning, for instance, an input could be a set of user queries to an AI chatbot at a given time.

“In this way, we have exploited every possible heuristic behavior and used special techniques to move in the direction where we think the performance gap is going to increase,” Karimi explains.

In the end, MetaEase identifies the input that maximizes the performance gap between the heuristic and an optimal benchmark.

With this information, a heuristic developer could inspect the input to understand what went wrong and incorporate safeguards that will prevent the problem from happening during deployment.

In simulated experiments, MetaEase often identified inputs with larger performance gaps than traditional methods — pinpointing more catastrophic worse-case scenarios. And it did so much more efficiently. 

It was also able to analyze a recent networking heuristic that no state-of-the-art method could handle.

In the future, the researchers want to enhance MetaEase so it can process additional types of types of data, like categorical inputs. They also want to improve the scalability of their method and adapt MetaEase to evaluate more complex heuristics.

“Reasoning about the worst-case performance of deployed heuristics is a hard and longstanding problem. MetaEase makes tangible progress by analyzing heuristics directly from source code, eliminating the need for formal models that have historically limited who can use such analysis tools. I was pleasantly surprised that it handles non-convex and randomized heuristics by combining symbolic execution with gradient-based search in a practical and effective way,” says Ratul Mahajan of the University of Washington Paul G. Allen School of Computer Science and Engineering, who was not involved with this research.

This research was funded, in part, by a Microsoft Research internship and the U.S. National Science Foundation (NSF).

Astronomers pin down the origins of a planetary odd couple

New measurements of a hot Jupiter and its mini-Neptune companion suggest both planets formed surprisingly far away from their host star.

Across the Milky Way galaxy, a planetary odd couple is circling a star some 190 light years from Earth. A normally “lonely” hot Jupiter is sharing space with a mini-Neptune, in a rare and unlikely pairing that’s had astronomers puzzled since the system’s discovery in 2020.

Now MIT scientists have caught a glimpse into the atmosphere of the mini-Neptune, which is circling inside the orbit of its Jupiter-sized companion, and discovered clues to explain the origins of this unusual planetary system.

In a study appearing today in Astrophysical Journal Letters, the scientists report on new measurements of the mini-Neptune’s atmosphere, made using NASA’s James Webb Space Telescope (JWST). It is the first time astronomers have measured the composition of a mini-Neptune that resides inside the orbit of a hot Jupiter.

Their measurements reveal that the smaller planet has a “heavy” atmosphere that is rich with water vapor, carbon dioxide, sulfur dioxide, and hints of methane. Such a heavy atmosphere would not have been acquired by the planet if it had formed in its current location, very close to its star.

Instead, the scientists say their findings point to an alternate origin story: Both the mini-Neptune and the hot Jupiter may have formed much farther away, in the colder region of the protoplanetary disk. There, the planets could slowly build up atmospheres of ice and other volatiles. Over time, the planets were likely drawn in toward the star in a gradual process that kept them close, with their atmospheres intact.

The team’s results are the first to show that mini-Neptunes can form beyond a star’s “frost line.” This boundary refers to the minimum distance from a star where the temperature is low enough that water instantly condenses into ice.

“This is the first time we’ve observed the atmosphere of a planet that is inside the orbit of a hot Jupiter,” says Saugata Barat, a postdoc in MIT’s Kavli Institute for Astrophysics and Space Research and the lead author of the study. “This measurement tells us this mini-Neptune indeed formed beyond the frost line, giving confirmation that this formation channel does exist.”

The team consists of astronomers around the world, including Andrew Vanderburg, a visiting assistant professor at MIT, and co-authors from multiple other institutions including the Harvard and Smithsonian Center for Astrophysics, the University of South Queensland, the University of Texas at Austin, and Lund University.

A “one-of-a-kind” system

As their name implies, mini-Neptunes are planets that are less massive than Neptune. They are considered to be gas dwarfs, which are made mostly of gas, with an inner, rocky core. Mini-Neptunes are the most commonly found planet in the Milky Way, though, interestingly, no such world exists in our own solar system. Astronomers have observed many planets circling a wide variety of stars in a range of planetary systems. Mini-Neptunes, then, are generally considered to be garden-variety planets.

But in 2020, Chelsea X. Huang, then a Torres Postdoctoral fellow at MIT (now on the faculty at University of South Queensland), discovered a mini-Neptune in a rare and puzzling circumstance: The planet appeared to be circling its star with an unlikely companion — a hot Jupiter.

The astronomers made their discovery using NASA’s Transiting Exoplanet Survey Satellite (TESS). They analyzed TESS’ measurements of TOI-1130, a star located 190 light years from Earth, and detected signs of a mini-Neptune and a hot Jupiter, orbiting the star every four and eight days respectively.

“This was a one-of-a-kind system,” says Huang. “Hot Jupiters are ‘lonely,’ meaning they don’t have companion planets inside their orbits. They are so massive, and their gravity is so strong, that whatever is inside their orbit just gets scattered away. But somehow, with this hot Jupiter, an inner companion has survived. And that raises questions about how such a system could form.”

A spot-on snapshot

The 2020 discovery of TOI-1130 and its odd planetary pair inspired Huang, Vanderburg, and their colleagues to take a closer look at the planets, and specifically, their atmospheres, with JWST. In its new study, the team reports its analysis of TOI-1130b — the inner-orbiting mini-Neptune.

Catching the planet at just the right time was their first challenge. Most planets circle their star with a regular, predictable period, like the tick of a clock. But the mini-Neptune and the hot Jupiter were found to be in “mean motion resonance,” meaning that each can affect the other’s motion, pulling and tugging, and slightly varying the time each takes to orbit their star. This made it tricky to predict when JWST could get a clear view.

The team, led by Judith Korth of Lund University, assembled as many past observations of the system as they could, and developed a model to predict when each planet would pass by the star at an angle that JWST could observe.

“It was a challenging prediction, and we had to be spot-on,” Barat says.

In the end, the team was able to catch a direct and detailed snapshot of both planets.

“The beauty of JWST is that it does not observe just in one color, but at different colors, or wavelengths,” Barat explains. “And the specific wavelengths that a planet absorbs can tell you a lot about the composition of its atmosphere.”

From JWST’s measurements, the team found that the planet absorbed wavelengths specifically for water, carbon dioxide, sulfur dioxide, and to a lesser degree, methane. These molecules are heavier than hydrogen and helium, which constitute lighter atmospheres. Astronomers had assumed that, if mini-Neptunes formed very close to their star, they should have light atmospheres.

But the team’s new results counter that assumption and offer a new way that mini-Neptunes could form. Since heavier molecules were found in the atmosphere of TOI-1130b, which resides very close to its star, the scientists say the only possible explanation for its composition is that the planet formed much farther out than its current location.

The planet likely accumulated its heavy atmosphere of water and other volatiles such as carbon dioxide and sulfur dioxide in the icy region beyond the star’s frost line. In this much colder environment, water condenses onto bits of dust to form icy pebbles, which an infant planet can draw into its atmosphere. The water evaporates as it slowly migrates in closer to its star.

Barat says the team’s detection of heavy molecules in the atmosphere of TOI-1130b confirms that the planet — and likely its hot Jupiter companion — formed in the outskirts of the system. Through gradual migration, the two planets would be able to stay close together and keep their atmospheres intact.

“This system represents one of the rarest architectures that astronomers have ever found,” Barat says. “The observations of TOI-1130b provide the first hint that such mini-Neptunes that form beyond the water/ice line are indeed present in nature.”

This work was supported, in part, by NASA.

The tech revolution that wasn’t

Associate Professor Dwai Banerjee’s new book examines the visionaries who wanted to turn India into a world power at making computers.

In 1960, engineers at India’s Tata Institute of Fundamental Research (TIFR) built what they called an “Automatic Calculator,” the country’s first working computer. It had the same type of ferrite-core memory as IBM’s world-leading machines, and at a glance, appeared to herald a new age of tech advances in India.

Constructed with a fraction of the resources Western computer engineers had, the TIFRAC, as they called it, was a remarkable feat.

“The people working on it had never really seen an actual functioning computer,” says Dwai Banerjee, an associate professor of science, technology, and society, and the author of a new book about computing in India. “You had this ambitious group of engineers building a state-of-the-art machine with very, very, limited resources. The fact they could build this is staggering.”

However, the TIFRAC was never even replicated, let alone produced at scale. The visionaries behind it wanted to turn India into an independent computing nation: a place that would produce its own equipment and become an industry power. Instead, the TIFRAC became a technological cul-de-sac, and India’s tech industry took on a very different shape. Instead of exporting equipment, it exports talent, sending skilled engineers and executives around the globe.

Now Banerjee explores those issues in the book, “Computing in the Age of Decolonization: India’s Lost Technological Revolution,” published by Princeton University Press. In it, he examines the country’s pursuit of technological self-sufficiency, and the global forces that prevailed against this vision. As a result, the country is “the world’s leading provider of inexpensive outsourcing and offshoring services, yet enjoys minimal benefits from more profitable advances in research, manufacturing, and development,” Banerjee writes.

“This book is about understanding how the current landscape of technological power came to be and the unequal way in which power is distributed across the world when it comes to anything to do with computing,” Banerjee says. “Basically, the historical conditions of the mid-20th century period are essential to understanding why the world of computing looks the way it does today.”

Computing and the geopolitics of knowledge

When India became a sovereign nation in 1947, many of its leaders believed “rapid technology-driven industrialization was the only way out of centuries of colonial underdevelopment,” as Banerjee writes. Some leapt into action, such as the remarkable nuclear physicist Homi J. Bhabha, who helped establish the TIFR.

Initially, Indian leaders hoped to gain cooperation for the U.S. and international organizations in making technological advances, but quickly ran into Cold War politics. Computing was heavily bound up with defense matters; India was not always fully aligned with U.S. political interests, so the flow of knowledge from the U.S. to India was distinctly limited.

“This is very much an external constraint story,” Banerjee says. “You need blueprints and not just working papers, and that’s what was guarded by the U.S. for a very long time.”

Still, the TIFR research team toiled away as its computing projects until the TIFRAC was up and running — making national headlines.

“The achievement it represents is mind-boggling,” Banerjee emphasizes. “A computer in the U.S. would have cost more to run than this entire institute in India.”

As Banerjee details in the book, the TIFRAC machine was built to grow. Its engineers matched the speed of IBM machines and planned to import larger ferrite-core memory stacks as their workload expanded. But when IBM released the FORTRAN programming language in 1957, it required four times the memory the TIFRAC machine was equipped with. India’s 1958 foreign exchange crisis then shaped the machine’s fate: The World Bank convened a U.S.-led creditor consortium that conditioned rescue loans on the opening of Indian markets to Western capital. Importing larger memory stacks became unaffordable, rendering the TIFRAC obsolete almost as soon as it was completed.

“It’s a geopolitics-of-knowledge question, not that they made a mistake,” Banerjee says of the Indian engineers. “They didn’t know IBM was about to reshape software.”

Exit IBM, enter services

Though IBM’s jump forward after the release of Fortran left the TIFRAC project stalled out, Indian advocates for computer manufacturing did not give up their dream. For one thing, they looked around for partnerships and other ways of moving their domestic tech industry forward. And then in 1978, India, uniquely, banned IBM from the country, on account of its business practices.

That might have set the stage for India’s computer manufacturing industry to flourish. But at the same moment, countervailing forces took hold, including a widespread turn toward the private sector as an increasing source of activity, rather than public-private enterprises.

“For a moment you have this imagination come to a sort of fruition,” Banerjee observes. “But by the late 1970s and 1980s, there is a new group of people arguing for quick profits through software services, saying that this route feels less painful than setting up manufacturing, R&D, and firms for a decade or more.”

This turn toward private-sector services rather than government-involved manufacturing ultimately became a decisive factor in shaping India’s tech-sector trajectory. Rather than seeking to make machines domestically, the country became part of the global tech-services sector, while many of its engineers migrated to Silicon Valley and other tech hotspots. Global tech firms used their reach to advance the idea that many countries would develop independent industries. This is not the outcome India’s leaders and technologists once envisioned.

“It still surprises me because of the one thing India did that no other country in the world managed to do, and that’s kick out IBM,” Banerjee says. “The fact that this vision fades is part of changing government ambition.”

Beyond the mavericks

In writing the book, Banerjee has multiple goals. One is simply shedding more light on the rich details of India’s initial computing efforts. Another is contesting the idea that India somehow naturally found a role providing services and exporting talent; that is not what many people once hoped.

Still another motif in Banerjee’s work is that the history of computing too often centers on innovators who are cast as mavericks, shrugging off conventions to upend business and society — whereas the large-scale forces of global capital and geopolitics matter greatly in technological development.

“This book suggests we often overplay those stories of individual genius, because you can be a genius with all the right ideas, but if you don’t have all the institutions supporting you, it means nothing,” Banerjee says.

Other scholars have praised “Computing in the Age of Decolonization.” Matthew L. Jones, a professor of history at Princeton University, has stated that Banerjee’s book is a “scrupulous accounting of ultimately failed Indian efforts to secure technological sovereignty in the wake of independence,” which “joins the best recent accounts of computing worldwide and transforms how we think through diverse national trajectories through the Cold War and beyond.”

For his part, Banerjee hopes a wide variety of readers will be interested in the book — and recognize that the specific case of India and computing can tell us a lot about the challenges of new types of economic growth in many places.

“India stands in for a lot of countries in the mid-20th century that had recently gained formal political independence and were thinking of ways to catch up with the rest of the advanced industrialized world,” Banerjee says. “But the power structures tied to technological and scientific advancement did not disappear. They were replaced by newer structures, including foreign policy with very specific ideas about what different countries should be doing with regard to technology. That’s where the story starts.”

Biologist Joey Davis explores how cells build complex structures

His studies have shed light on the assembly instructions that govern ribosomes, the critical protein-building machines of the cell.

Ribosomes, the cellular machines that assemble proteins, are made from dozens of proteins and RNA molecules. Putting all of those pieces together is a complex puzzle — one that MIT Associate Professor Joey Davis PhD ’10 revels in trying to solve.

Understanding how these structures form and later break down could help researchers learn more about how disruptions of these fundamental processes can lead to disease. But, as Davis points out, it’s also an interesting biological question.

“Our long-term goal is to really understand how the natural world assembles these huge complexes rapidly and efficiently. It’s a fundamentally interesting question to think about how these things get put together,” he says.

His work has helped reveal that unlike building a house, which happens in a prescribed sequence of steps — pouring the foundation, building the frame, putting on the roof, then doing electrical and plumbing work — ribosomes can be assembled in a more flexible way. Cells can even skip an assembly step and then come back to it later.

“In these natural systems, it seems like the assembly pathways are much more dynamic and flexible,” he says. “It appears that evolution has selected pathways that aren’t strictly ordered in the way we would think about an assembly line, where you always put in one component, then the next, and then the next. We’re excited to understand the selective advantages of such approaches.”

A love of discovery

Davis’ interest in how things are put together developed early in life, inspired by his father, a carpenter who framed houses. During the mid-1980s, the family moved from Colorado to Southern California, where his father worked in construction during a housing boom there.

“I was always interested in building things, which I think probably came from being around my dad and other builders,” Davis says.

As an undergraduate at the University of California at Berkeley, where he majored in computer science and biological engineering, Davis’ interests turned toward smaller scales, in the realm of cells and molecules. During his junior year, he started working in the lab of chemistry professor Michael Marletta, who studies molecular-level biological interactions.

In the lab, Davis investigated how enzymes that contain heme are able to preferentially bind to either oxygen or nitric oxide, two gases that are very similar in structure. That work kindled a love of studying the natural world and pursuing discoveries in fundamental science.

“Being in the Marletta lab and seeing students and postdocs that were really passionate about these problems had a big impact on me,” Davis says. “The goal was to understand the fundamentals of how molecular discrimination works, and the idea of discovery for the sake of discovery was thrilling.”

After graduating from Berkeley, Davis spent another year working in Marletta’s lab, and then a year working odd jobs, before heading to MIT to pursue a PhD in biology. There, he worked with Professor Bob Sauer, now emeritus, who studied the relationship between protein structure and function, with a particular focus on the molecular machines that degrade or remodel proteins.

Davis’ thesis research centered on enzymes called AAA proteases, which remove damaged proteins from cellular membranes and send them to cell organelles that break them down. In addition to studying the structure and function of the proteases, Davis worked on ways to engineer them to tag specific proteins for destruction.

That work led him into synthetic biology, which he used to develop genetic parts that drive production of proteins of interest. Some of those parts ended up being used by the biotech startup Ginkgo Bioworks, where Davis took a job as a senior scientist after graduating.

Working at Ginkgo Bioworks allowed Davis to stay in Boston while his partner finished her PhD. The couple then moved back to California, where Davis worked as a postdoc at Scripps Research, which was home to one of the first direct electron detection cameras for cryo-electron microscopy (cryo-EM). These detectors allow researchers to generate structures with near atomic resolution. At Scripps, Davis began using them to study ribosomes as they were being assembled.

Peering into the ribosome

After joining the MIT faculty in 2017, Davis continued his work on ribosomes and assembled a lab group that includes students from a variety of backgrounds who work together to develop new ways to explore biological phenomena.

“I have a mix of method developers and biologists in the group, and the work from each of them informs each other,” Davis says. “My lab goes back and forth between building sets of tools to answer biological questions, and then as we’re answering those questions, it motivates the next generation of tool development.”

During ribosome assembly, RNA molecules fold themselves into the correct shapes, creating docking sites for proteins to attach. Then, more RNA molecules come in and fold themselves into the structure.

“It’s a beautifully coupled process by which the cell folds hundreds of RNA helices and binds on the order of 50 proteins, and it does it in two minutes from start to finish. E. coli does this 100,000 times per hour, and it’s amazing how rapid and efficient the process is,” Davis says.

Cryo-EM allows scientists to capture this process in minute detail. It can be used to take hundreds of thousands of two-dimensional images of ribosome samples frozen in a thin layer of ice, from different angles. Computer algorithms then piece together these images into a three-dimensional representation of the ribosome.

To gain insight into how ribosomes are assembled, researchers can stall the process at different points and then analyze the resulting structures. In 2021, Davis’s lab developed a new method called CryoDRGN, which uses neural networks to analyze cryo-EM data and generate the full ensemble of structures that were present in the sample.

This work has shown that when certain steps of ribosome assembly are blocked, many different structures result, suggesting that the assembly can occur in a variety of ways.

In future work, Davis aims to dramatically increase the throughput of cryo-EM to generate datasets of protein structures that could help improve the AI-based models that are now used to predict protein structures.

“There are still huge swaths of sequence space that these models are very poor at predicting, but if we could collect data on those sequences en masse, that could potentially serve as key training data for a next-generation protein structure prediction method that could fill out that space,” he says.