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

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

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

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

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

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

Overcoming the limits

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

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

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

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

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

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

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

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

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

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

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

Leveraging magnetism

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

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

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

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

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

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

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

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

The crack of a bat accompanied by a roar from the crowd can capture a baseball fan’s attention, even if they miss seeing the home run. Humans may be visual creatures, but we also perceive the world around us by listening to it. 

To improve artificial perception, MIT Professor Paris Smaragdis SM ’97, PhD ’01 seeks to make machines that can hear and understand sound even better than humans.

A machine with super-human hearing could rapidly pinpoint the location of a traffic accident by listening for squealing tires and crunching metal, or identify when an industrial drill might break while it is boring through dense bedrock to dig a geothermal well.

“I like to say that I do the same thing the computer vision folks do, but instead I do it for hearing,” says Smaragdis, a professor with joint appointments in the Music and Theatre Arts program of the School of Humanities, Arts, and Social Sciences, and the Department of Electrical Engineering and Computer Science in the School of Engineering and the MIT Schwarzman College of Computing. 

His research group explores areas like machine learning for sound source separation, smart devices that can augment the audio surroundings of humans, and better tools to help people understand, manipulate, analyze, and create music.

“Having had a musical background, I’ve been interested in examining these ideas. What does it take to make machines understand sound? There is a huge domain of applications for machines that can listen,” says Smaragdis, who joined MIT in 2025.

A musical prelude

Smaragdis, who grew up in Greece, began playing classical guitar at a young age. He enjoyed playing traditional pieces but reached a turning point in his musical journey when his father brought home a small synthesizer.

“That little synthesizer had a function that allowed you to make your own sounds, and I became completely captivated by the possibilities,” he says.

Synthesizers were taking a more prominent place in pop music during the 1980s, adding to his fascination with the technology.

As he advanced through school, Smaragdis wanted to study music made with synthesizers. But this was not an educational path offered by the more traditional European conservatories at the time.

Instead, he enrolled at Berklee College of Music in Boston, into a program where he could explore the use of computers and synthesizers to shape and manipulate sound.

“With computers and synthesizers, I could make new sounds that have never been heard before,” he says.

At the same time, Smaragdis became immersed in jazz fusion. He declared bass as his major at Berklee since it would allow him more opportunities to play with jazz ensembles.

“I found the bass to be sonically more interesting than the guitar. It was a more unexplored domain, and I’ve always gravitated toward unexplored domains,” he says.

That interest in the unexplored carried over into his coursework. He and mentor Richard Boulanger, a professor of electronic production and design, created new tools to help people use computers to write, produce, and enhance music. 

Through his studies at Berklee, Smaragdis embarked on a collaborative project with Professor Barry Vercoe (who passed away in 2025) at the MIT Media Lab to create software synthesizers for music creation. Building on that project, Smaragdis pursued graduate studies in Vercoe’s group, where he completed his master’s degree and PhD, followed by a postdoc.

“In the Media Lab, I got exposed more to the computer part of computer music. That’s where my attention shifted a bit. Now I really wanted to make computers that could understand sound,” he says.

Tuning in to unexplored domains

At that time, many students in the Media Lab were using signal processing techniques to help machines handle sound. Smaragdis chose a less explored approach — machine learning — to separate himself from the pack.

He found that training machine-learning models to understand sound offered advantages that couldn’t be attained with traditional signal processing techniques.

“Over time, it became really clear to me that we need to teach computers how to listen. We can’t just tell them how to listen. If anything, we don’t even know how we humans listen,” he says. “We don’t have a vocabulary to explain what it means to listen, or how to tell the difference between a cat’s meow and the sound of a violin.”

After finishing his postdoc, Smaragdis began a career at Mitsubishi Electric Research Labs, where he worked on artificial intelligence systems that could scan video soundtracks and understand what is happening on screen. 

“What if you record an entire soccer game, but you only want to watch the highlights? In computer vision, it is very difficult to identify what a highlight is. But on the other hand, if you only listen to the sounds, then when the crowd goes crazy you would know that something interesting is happening,” he says.

That system was eventually incorporated into electronic devices, including a personal video recording system Mitsubishi was developing at the time, and into traffic monitoring systems and cell phones.

Smaragdis later joined Adobe, where he created the audio research team that built user-friendly tools to help artists, musicians, and producers manipulate sound without needing a lot of expertise.

“As we did that work, I kept coming up with deeper technical problems that needed to be resolved. I jumped into academia to address that itch,” he says.

Smaragdis joined the faculty at the University of Illinois at Urbana-Champaign, where he and his group incorporated the latest machine-learning techniques into audio-processing systems.

One of the technologies they developed utilized neural networks for separating individual sounds from audio mixtures. That project caught the attention of the team working on the 2021 documentary mini-series “The Beatles: Get Back.”

The production team enlisted Smaragdis to help clean up some archival Beatles recordings.

“That was a very different way of audio processing than what I was doing in academia. Now, I had to do something that sounded good but didn’t necessarily have to look good on paper. We didn’t have a formula we could optimize,” he says.

Every recording involved different challenges. For instance, in one clip John Lennon was playing music while Paul McCartney was horsing around, reading headlines from newspapers and making fun of George Harrison.

“We were trying to come up with a technological solution that could help us do everything, as opposed to addressing each problem on its own,” he says.

His contributions helped the team win an Emmy Award for sound editing for a nonfiction or reality program, in 2022.

A concerted effort

After 15 years at the University of Illinois, Smaragdis decided to join the faculty at MIT to tackle the thorny, interdisciplinary problems that were emerging in the field. 

His group now focuses on two main areas. For one, they develop systems that make computers more useful tools for musicians. 

One project in this area is enabling machines to understand how to listen to music, so they can provide constructive feedback to musicians.

“We want to enhance the toolbox a musician has. We don’t want to use computers to replace musicians,” he says.

On the other side, his group focuses on the fundamental tools scientists and artists alike can use to process, analyze, and manipulate audio.

For instance, his team has recently been exploring algorithms that allow sophisticated signal processing where traditional frames of reference, such as sampling rates, frame sizes, or context-windows, are not fixed — or even defined. 

That implies different computational structures that are yet unexplored, despite their potential for more efficient processing, Smaragdis says.

“That requires rethinking a lot of the basics, but once you have that ability, you can start getting much more flexible and more powerful systems,” he adds.

They also explore ways to incorporate the latest techniques, like large language models, into speech recognition and audio enhancement.

“AI is an immensely powerful tool, but I don’t think we have found the ideal way to use it for sound and music yet,” he says.

He also enjoys mentoring students and helping them materialize their visions for research projects.

Since few of his students have experience using computation in sound, he emphasizes hands-on lessons so they see and hear how to transform equations into something tangible.

Smaragdis still feels a thrill from making music, whether with a computer or a more traditional instrument. Off campus, he tries to play jazz bass whenever he can find the time, and enjoys exploring the rich musical community of Boston with his wife and 15-year-old son.

Outside the musical realm, he plays and coaches underwater hockey — a sport where players wear diving masks and use sticks to push a heavy puck across the bottom of a pool toward their opponent’s goal. He coached the underwater hockey team at the University of Illinois, and is hoping to revive the MIT underwater hockey club soon and start hosting tournaments on campus.

While underwater hockey may be a lesser-known sport, it fits with Smaragdis’ lifelong interest in pursuing the underexplored.

“I’ve always like doing things that were different from what everyone else was doing. If you can create a new sound that no one has heard before, what does that mean about your ability to create new things? I still find these questions completely fascinating,” he says.

Like many leaders today, Prabha Jha has been feeling the significant impact artificial intelligence is having on business operations. While the rapid evolution of the technology can bring fear, uncertainty, and confusion, Jha chose a different response: excitement. She began asking herself, “How do I become part of this once-in-a-lifetime thing?” 

Jha holds a bachelor’s degree in information technology from the University of Calcutta and earned her MBA while working at Verizon, where she continues to build her career. As she looked for an educational opportunity to engage more deeply with AI, MIT quickly emerged as a natural choice. 

Growing up, Jha viewed MIT as “the mecca for anybody who is in engineering and technology,” so she naturally turned to the Institute when seeking an opportunity to learn about AI. Unlike other programs that took place fully online, MIT xPRO’s AI for Senior Executives stood out to Jha primarily because it offered an in-person component that allowed her to meet and connect with peers. 

Jha decided to take the leap. She acknowledges that the program was a significant investment of both time and money, but ultimately views it as one of “the best decisions [she] made” — one she “would do all over again if [she] had to.” The experience gave Jha the opportunity she was looking for to invest in herself and strengthen her skills in AI. It also provided her with invaluable professional relationships and the confidence to develop multiple AI solutions for Verizon. Putting those news skills and relationships to work, she co-wrote, with some of her peers, “The AI Anthology,” a collection of AI insights designed to support other leaders navigating similar challenges with AI. 

An unexpected learning obstacle

Jha’s learning journey wasn’t without its curveballs, though. Just two months before she was set to complete the program, she spent two weeks in the hospital with a severe infection and was unable to graduate with her original cohort. With the help of MIT staff, she joined the next cohort, giving her an unexpected opportunity to spend another five days on campus with 100 brand-new peers. 

“You just never know what curveball life can throw and what it might be there for,” Jha says.

What initially felt like a setback turned into an unexpected benefit. Jha valued the opportunity to meet new people and spend more time on campus. She also appreciated that just six months later, the program’s content had already been refreshed. Those additional “five days of immersion” became a vital part of Jha’s learning journey, giving her and her peers more time to collaborate face-to-face and learn from one another. 

“I think it was eye-opening to be able to meet so many people with diverse backgrounds and geography, and then we connected at the human level,” she says. 

Jha particularly valued that sense of connection in the context of learning about AI, a field that, she acknowledges, comes with fears, vulnerabilities, and difficult questions. Learning alongside peers with different professional and cultural backgrounds gave her new perspectives and added another dimension to the experience. Jha estimates that “30 percent of what I was learning was from the program, material, and professor [while] 70 percent was my peers and the interactions.”

Peer discussions spark an idea

The idea that would change the trajectory of Jha’s time in the program came during a “salon gathering” at the home of Manolis Kellis, a professor in MIT’s Department of Electrical Engineering and Computer Science. As students shared personal stories about their experiences with AI, one story in particular stayed with Jha: that of one of her peers, whose motivation to explore AI solutions stemmed from her work to find a cure for her mother’s Alzheimer's disease and dementia. 

At that moment, Jha realized that AI is personal. She still “gets goosebumps thinking of that moment where AI really became human and a connecting point.”

She saw the value in capturing these diverse perspectives and experiences with AI that go beyond operational efficiency and revenue growth, and wanted to continue the conversation beyond the program. Jha expressed to her peers an interest in capturing these stories and connections in a book. One year later, Jha and 20 other leaders released “The AI Anthology,” a collection of essays examining the influence AI has had across industries and across society. 

One of the biggest takeaways from the AI for Senior Executives program — and one that Jha hopes readers will take from her book — is the importance of thinking differently. 

Jha believes leaders may be missing a fundamental shift: “We are still kind of stuck in this traditional measurement of success,” she says. “We cherish revenue; we like cost-cutting and time-saving, and converting them to dollars.” 

While Jha acknowledges this mindset makes sense in corporate America, she believes leaders must move beyond it in order to find more empowerment through AI and its capabilities. She notes that future generations are already asking different questions, including: “What can I get in the quality of my life?” and “How can I use my time in a way that is fulfilling for me early on?” 

The future of embracing AI for business and a better world 

Jha recognizes that AI adoption is not optional for businesses, and that everyone must learn about and embrace it. At the same time, she is a steadfast believer in AI’s ability to create a better world. Instead of viewing AI as a foregone burden, she sees it as a “transformation unlike any other” that is providing us with the opportunity to overcome insecurity, adapt and grow, and invest in ourselves. 

In her work at Verizon, Jha takes seriously the company’s role as “a brand name for reliable, quality service” providing “critical infrastructure” to groups, such as first responders or children, who depend on their services. This responsibility comes with a privileged obligation to participate in and protect society, and Jha finds it empowering that AI can help enable this. In her own experience, she’s appreciated the ability to accelerate progress and impact, when she may have previously needed to rely on a larger team. 

So, what’s next for Jha? Currently, she is working on a new initiative focused on supporting small and medium-sized businesses that are navigating AI implementation. Her goal is to help them understand what tools they need, how AI fits into their specific operational model, and how they can measure success, so they can focus on their strengths as a business and how they can drive value. 

Angeline Peng doesn’t come from a strong faith tradition, but she is a big believer in the power of discussion. In her role with the Addir Fellows Interfaith Dialogue Program at MIT, she convenes and leads regular, small-group interfaith conversations to help other students — and herself — grapple with big questions.

The Addir Fellows Program was started in 2005 through a grant from the U.S. Department of Homeland Security. It is now supported by MIT’s Office of Religious, Spiritual, and Ethical Life. The program has maintained a steady focus on “sharing spiritual values and experiences, not just opinions,” says MIT Chaplain Thea Keith-Lucas.

A fourth-year math major, Peng sees deep connections between what she’s learning in class and the Addir Program. Here, she describes her work with the program, the link between faith and logic, and how she believes discussing big questions changes people.

Q: What is the Addir Fellows program?

A: It’s an interfaith dialogue club. “Addir” comes from the Sumerian word for “bridge,” and that's what we're here to do — build bridges between people from different walks of life. 

We meet every week in small groups of five to eight people. The groups start off with what we call our “spiritual autobiographies.” As much as we can, everyone gives a description of where they're coming from. After that, every week we pick a topic and discuss it. 

We try to balance faith traditions in the small groups. The biggest limiting factor is scheduling. That turns out to be really complicated. 

Q: What’s your own spiritual autobiography?

A: My family is atheist. I was born in Singapore, which is very multicultural, and we moved to Lehi, Utah, when I was 10. Utah is very homogeneous; most people in my neighborhood were part of the Church of Jesus Christ of Latter-Day Saints. Sometimes in high school I would ask friends about their beliefs, but college was the first time I could really explore. 

At some point I realized it's important to know myself better, to understand and have my own principles. Exploring different religions is an attempt — and I am still building this — to understand what I think is important, what I value, what I think is right, and what I think is wrong. 

Getting insight from different faith traditions is really helpful. I believe different religions, or different approaches to religion, are all interpretations of universal truth — and so exploring from all kinds of perspectives will give me a better understanding of what that could mean. 

I'll say, I'm not too sure about it yet. I don't know if there's some kind of universal good, or bad, or whatever. But I do think there are some kernels in everything. 

Q: Who participates? Does the program bring together a range of faith traditions?

A: When I signed up for my first Addir event, I met grad students and undergrads from just about everywhere. It was very refreshing, like — “Wow! I didn't know there were all these people here!” At MIT, you can end up in a kind of bubble. You know people from your dorm or your major. This program’s different.

The people come from a wide spectrum of traditions and backgrounds. Also, we have quite a lot who are somewhat agnostic or less extreme in their beliefs. 

A big part of why people sign up for Addir is they want to listen to other people and learn. Sometimes, this means they don't talk as much. I do my best to instigate — play devil’s advocate and push at people's ideas. I believe that’s part of my job.

Q: Do you think participants feel pressure to speak “for” their faiths?

A: I wouldn't say anyone is trying to represent their faith, because there are so many facets of just one faith anyway. When there are questions, everybody gives an answer like, “This is what I think.” Sometimes people will bring up a text and say, “It says this, and this is how I interpret it, or this is how certain people in my life interpret it.” That can be really helpful.

Also, I wouldn't say we’re focused on just religion. A lot of people are just trying to find their way in life, whether it’s through spiritual or secular questions. In my small groups, we've talked quite a bit about what we can do to just be a better person; exploring different aspects of that, and dealing with more everyday stuff like regrets, guilt, pleasure, pain, punishment. Obviously, religion can help you with answers. 

I like to think: How can we answer those questions as a group, in that room, in that moment? The answers might be different for everyone, but if we can hear what other people think, maybe we can get insight and be persuaded into believing something new. 

Q: How does the mathematician in you come out during these conversations? 

A: I think part of why I do math is spiritual, so they're connected in that sense. It all relates to how I want to live my life. Some people describe doing math like making art — they're in pursuit of beauty and some deeper truth. I think math is really pretty, and there's a lot of beauty in the truth. 

One of the great tools of mathematics is that it teaches you how to abstract and understand which details are just details, and what are the core ideas. Doing a lot of math helps me stay objective, abstracting away things that are less important. 

Q: Can it be difficult to reconcile issues of faith and logic? 

A: You have to always believe in something. It's like picking your axioms. You start with faith in something, and from there you can extrapolate away what you think.  

It can be very difficult. Gödel's incompleteness theorem says you can't prove everything with any set of axioms. You can choose whatever set of axioms you like, and it either is incomplete or inconsistent; incomplete, as in you can't prove every statement is either true or false, and inconsistent in that you will at some point prove that something is both true and false. So you can't have both. But we want both! 

Mathematicians live with the incomplete, and this is probably true for any belief system. Some people are deeply unhappy not knowing the answer, and some people are more OK with it. I tend to be very OK with it. 

Q: Do you think this program changes people?

A: Definitely. Over time, people's opinions really do change. We all have the more “press-ready” opinions we give to others. Even in Addir, it's got to be half or two-thirds of the year before I feel comfortable talking about everything I really believe. This program is genius because you actually become friends by the end. 

To actually care about another person — as a person, outside of what they believe — is really a function of time. You need to be together and have this dialogue for a while. When there’s conflict, finding solutions is very situation-dependent, and maybe not possible. But eventually, you get to know each other. You can talk about controversial issues or opinions that maybe you were scared of sharing before. It's so nice to have this space as your opinion is changing. 

Because of Addir, maybe one person learns a little bit, and they go back to their own group of people and share that perspective. And when they share it, someone else learns. I'm a big proponent of let's try to change things locally — very locally; person by person — and maybe we can spread that positivity. 

At any given moment, a U.S. Air Force pilot may be maneuvering an aircraft mid-mission, a U.S. Navy officer resurfacing a submarine after weeks undersea, or a U.S. Army technician offloading drone data in a combat zone. Each operation depends on satellite communications (satcom) and, specifically, on cryptographic keys that allow terminals to communicate securely while keeping adversaries locked out.

At the scale of modern operations, managing these keys is a technical challenge. Every terminal needs to have the right keys at the right time, quickly and securely, and if any keys are compromised, they need to be refreshed without leaving out devices that may be offline, disconnected, or under attack.

MIT Lincoln Laboratory researchers have now solved this challenge with the Protected Anti-Jam Tactical Satcom (PATS) Key Management System (KMS) Prototype. This new architecture enables keys to refresh rapidly across terminals dispersed worldwide, even in contested or bandwidth-constrained environments.

"We're enabling the nation to achieve highly assured, highly available communications. Even when adversaries know where forces are operating and are trying to stop them from communicating, they're unable to do so, because we've built in smarts across this entire system to keep talking,” says Joseph Sobchuk, a principal investigator of the PATS KMS Prototype program and researcher in the Secure Resilient Systems and Technology Group.

This architecture is being adopted as the cryptographic backbone of the U.S. Space Force's next-generation satcom system, PATS. The KMS Prototype serves as the gold-standard reference implementation for the industry-built operational KMS, which will be integrated across the PATS ecosystem, encompassing satellites, user terminals on military platforms, and ground-based communication hubs.

Developed under sponsorship of the Space Force’s Space Systems Command (SSC), the KMS Prototype reflects Lincoln Laboratory's end-to-end approach to technology development, from shaping the core key-management concepts to putting them into practice in a prototype to transitioning a technical baseline to government and industry. For this transitioned innovation, the SSC and Lincoln Laboratory team received a 2025 R&D 100 Award, recognizing the KMS Prototype among the year’s most impactful new technologies.

Managing key challenges

Cryptographic keys are foundational to secure communications. These keys, strings of random characters used by cryptographic algorithms, help protect communications by encrypting data and supporting protected transmission patterns, such as frequency hopping. Without key protection, the communications sent and received by terminals are more susceptible to eavesdropping and interference.

Historically, operators manually uploaded keys to terminals before missions. More recently, some systems have supported over-the-air key updates, but bandwidth constraints, security concerns, and operational complexity have limited real-time, wide-scale refresh.  

"Key management is the linchpin that turns advanced, anti-jam hardware and waveforms into a usable mission capability," says Roger Khazan, leader of the Secure Resilient Systems and Technology Group. "Without a scalable way to deliver the right keys to the right systems at the right time, protected satcom cannot operate reliably across a dynamic force."

One primary threat to satcom is signal jamming, where adversaries flood specific frequencies with noise. To resist jamming, PATS uses frequency hopping, in which signals jump rapidly between frequencies in a pattern that looks random to anyone without the key. This hopping only works when every legitimate terminal holds current keys and stays in sync. Keeping all those terminals correctly keyed is the KMS's job. "Designing a system to handle that coordination efficiently, without breaking the conversation, is incredibly difficult," Sobchuk says.

Maintaining synchronization becomes even more critical when devices are compromised. Terminals share keying material so they can communicate as a group and follow protected hopping patterns. If an adversary captures a device, such as a downed drone, and extracts its keys, the exposure can extend beyond that one device. Depending on what keying material is exposed, an adversary may gain access to protected communications or help a jammer follow the hopping pattern. Restoring security means refreshing keys for legitimate terminals — including those that may be offline or operating in contested conditions — while locking the captured device out.

But here's the catch: To send new keys, you need to establish a secure link to terminals, and to establish a secure link, terminals need valid keys. This situation creates a long-standing "chicken-or-egg" problem for key management.

Solving the chicken-or-egg problem

Lincoln Laboratory's solution is a hybrid key distribution method using a "pull-and-push" approach. Each month, each terminal "pulls" a package of keys tailored to that terminal over the satcom link. Then, daily, the satellite "pushes" a smaller key to every terminal. The monthly keys encrypt the daily keys, creating layered security. The daily key determines the unpredictable frequency-hopping patterns. Even if an adversary captures today's key, tomorrow's will be different, and encrypted to exclude them.

"This way of sending keys hadn't existed before," Sobchuk says, adding that Lincoln Laboratory researchers have been pioneering this key-management technology for more than a decade. "The combination of pull and push, monthly and daily, is the magic behind all of it."

This hybrid approach also solves the issue of leaving out devices that were disconnected during a key refresh. For instance, if a submarine submerges for six months, it can request keys for the entire period in advance. Even if keys are refreshed while it's offline, the submarine can immediately reconnect when it resurfaces because the monthly keys provide access to the daily key.

"Submarine crews want to log on to the satellite and talk right away, not wait to get back to shore for new keys. They want to turn on their system and have it work," Sobchuk says.

Monthly and daily key broadcasts must reach thousands of devices spanning the globe. To enable this large-scale sharing, the team adapted theoretical algorithms from academia to create the first operational-scale implementation of broadcast encryption for such a protected satcom application. Broadcast encryption is a method for securely sending information to many users at once. These algorithms encrypt each daily key using just a small subset of keys instead of separately encrypting the daily key for every terminal. This implementation preserves communication bandwidth that would otherwise be consumed just by sending keys.

"The point isn't just stronger cryptography. It's making secure communications usable at operational scale, in contested conditions, without imposing a crippling burden on the warfighters and operators who depend on them," says Sean O'Melia, an assistant leader in the Secure Resilient Systems and Technology Group.

Transitioning to operations

Lincoln Laboratory has transitioned the KMS Prototype to multiple government and industry partners developing PATS components across service branches. To facilitate this coordination, the team has supported dozens of integration events and produced in-depth technical documentation. The prototype is allowing developers to test and validate their components while defense contractors build the operational version of KMS.

The laboratory's work is also enabling contractors to achieve National Security Agency (NSA) certification of end cryptographic units (ECUs), the hardware devices within a terminal that transmit, receive, or store keys. Last year, the first PATS ECU — the space-hub ECU that goes on the satellite — earned NSA certification. Achieving this certification is an arduous process requiring proof that the design, implementation, and supporting processes are all secure.

After years of work, the team is grateful to have helped lay a foundation for the future of secure satcom, both through the KMS Prototype and the larger PATS technical vision, Khazan says. The effort brought together expertise from across the laboratory’s Cyber Security and Information Sciences Division and Communication Systems Division.

"PATS KMS is the kind of problem Lincoln Laboratory was built to solve: high-risk research, rigorous engineering, and transition into a national-security capability. Working with Space Systems Command and the PATS community, our team helped turn advanced key-management ideas into a technical baseline that industry can build on and the government can use. The result is a more-resilient satcom architecture that can scale across a complex operational ecosystem," he says.

MIT researchers developed a new type of origami-based construction method that could be used to build complex structures that are cheaper and easier to assemble, and use less material than those built with some conventional techniques.

This scalable system simplifies the process of designing lightweight, rigid structural shells from modular components that can be fabricated from flat sheets of material and then folded into shape. 

The units are connected to build a larger lattice structure using simple tools and a foolproof assembly process. They form a strong, load-bearing structural shell that doesn’t need interior support columns.

This method could be particularly well-suited for disaster relief shelters that can be rapidly fabricated and shipped efficiently as flat panels, then set up quickly by workers at the site of an earthquake or flood. It could also be used to develop strong, lightweight components for airplanes or modular robots, or architectural elements like sound-dampening panels and building facades.

The researchers’ technique can generate structures that are many times stiffer than those made using some other forms of structural origami, while requiring only about two-thirds as much material. This could make it a more sustainable form of construction.

In addition to developing small prototypes, the researchers demonstrated the scalability of this approach by fabricating a room-sized folded aluminum sculpture that was recently hung at the Boston Public Library as an exhibition inaugurated for the annual Fab Lab Conference and Symposium.

“This work shows that the power of digital manufacturing can go beyond personal fabrication projects and start touching the real world, enhancing the way we design houses and large structures. We are demonstrating structural origami on building scales,” says Alfonso Parra Rubio, a graduate student in the Center for Bits and Atoms (CBA) at MIT and lead author of a paper on this method.

He is joined on the paper by Riccardo Foschi, a researcher at the University of Bologna in Italy; Rupert Maleczek, a senior scientist at the University of Innsbruck in Austria; Tomohiro Tachi, a professor at the University of Tokyo; and senior author Neil Gershenfeld, an MIT professor and the director of the CBA. The research appears in the International Journal of Solids and Structures.

Lightweight, rigid components

The researchers drew inspiration from the folded tessellations developed by the artist and scientist Ron Resch in the 1960s. Resch employed repeating patterns of polygonal unit cells to create complex 3D structures (like a honeycomb). 

But rather than creating a shape from one folded piece of material, like Resch’s tessellations, the researchers fabricate unit cells that are folded individually and connected to form the 3D structure.

By designing individual building blocks, they can simplify the fabrication process and create more complex shapes.

While working in the Tachi lab, Parra Rubio developed a method for combining two tripod-shaped unit cells from a Resch tessellation into a building block that has zero degrees of freedom, which means it is completely rigid and locked in place. 

These rigid building blocks can be connected into a network of interwoven beams that form a 3D structure with extremely high stiffness and stability, but very light weight.

“This helps us build strong structures while minimizing the amount of material we are using,” Parra Rubio explains.

But it would be enormously challenging to manually design polygonal building blocks that will form a structure that meets a user’s constraints.

To simplify the process, Parra Rubio joined forces with CBA graduate student Erik Strand to develop an automated solver that designs a series of manufacturable unit cells that will form the user’s desired structure. These design files can be fed to a CNC milling machine that automatically cuts the building blocks from flat sheets of material, like aluminum. 

“On the computational part, we break this big problem down into many small subproblems. Now, we solve each cell independently to make sure that it is foldable, and then we globally assemble them after that,” Strand says.

Simplified assembly

Builders fold the individual units into shape and assemble them into a finished structure using only hand tools, like screwdrivers. 

The assembly process does not require any large-scale welding equipment, which could make it simpler, faster, and cheaper than some other forms of construction. In addition, the unit cells are designed so they adjust naturally into their correct shape as the structure is assembled. 

“The way the unit cells are designed, the structure can only exist in one configuration. The connection is the same everywhere, even though each unit cell is different,” Parra Rubio says.

Simulations indicated that this method yields structures about 3.5 times stiffer than those made with some other origami-based techniques, while using less material. In addition, the resulting structures could be strong enough for some architectural applications, Parra Rubio adds. 

To demonstrate the versatility of this approach, the researchers assembled a 23-foot sculpture from pieces of folded aluminum that was hung from the ceiling of the atrium in the Boston Public Library. A team with no professional construction experience built the entire structure in a matter of days, Parra Rubio says.

“It was really fun to work on something at such a quick pace where the theory was really meeting a practical use for it. We had to think a lot about how we could tweak the design to achieve each objective,” Strand says.

In the future, the researchers want to test this approach in larger, architectural structures. They also want to explore the use of unit cells with more complex geometries, which could offer greater strength or stiffness, and develop a user-friendly design interface. 

“This work shows that folding metal is a method that is ready to be used for building structures. We can do it big enough and strong enough, now that we can bring it out of the lab and to the construction site,” Gershenfeld says.

“Within the architecture, engineering, and construction industry, complex structures are often delivered through a fragmented sequence of handoffs between design, engineering, fabrication, and construction teams, with each transition creating opportunities for miscoordination, rework, and loss of design intent. By embedding geometric, structural performance, and assembly intelligence directly into each module, Rubio’s approach maintains a seamless digital thread from design through erection, enabling unprecedented customization while ensuring precise execution,” says James Coleman, SM ’14, MArch ’14, cofounder of SumPoint, a project installation specialty firm. 

Coleman works on design for fabrication and erection of complex architectural projects, and was not involved with this research.

This research was funded, in part, by the Center for Bits and Atoms Research Consortia, the University of Bologna in Italy, and the Austrian Research Agency.

J-PAL North America, a research and policy center in the MIT Department of Economics, is launching a free Homelessness Evaluation Resource Hub. 

The hub — a public repository of evergreen multimedia content developed with a grant from Google.org — aims to equip decision-makers with foundational tools on how to leverage evidence to reduce homelessness and improve housing stability.

Homelessness represents both a cause and a consequence of poverty and inequality. Rigorous evidence is critical in identifying effective solutions to eliminating homelessness, but rising constraints on time, funds, and other resources can create difficult barriers to developing and accessing high-quality evidence.

J-PAL North America aims to increase access to evidence-informed paths to housing stability by providing essential tools for researchers, policymakers, and practitioners to evaluate the impact of their programs, expand the body of literature on what works to reduce homelessness, and leverage existing evidence to inform programs and decision-making. 

To launch the hub, J-PAL North America is hosting a virtual event on Oct. 27.

David Phillips, director of research at the Wilson Sheehan Lab for Economic Opportunities (LEO) and research professor of economics at the University of Notre Dame, served as the scientific advisor on the hub. 

“I’m thrilled to have been able to contribute to J-PAL North America’s Homelessness Evaluation Resource Hub,” Phillips says. “In my 15 years working with nonprofit and government leaders on program evaluations, I've seen how much value comes from practitioners and academics entering each others’ world, learning to speak each others’ languages, and, most of all, learning from each other. This resource hub builds shared language for research design so teams can move forward with clarity and confidence — creating more time to focus on the shared goals of continuous learning and improving outcomes for communities.”

The hub includes resources focused on two primary activities: using evidence, and generating evidence. The Using Evidence section provides newly developed two-page policy briefs that synthesize experimental and quasi-experimental research results on five established homelessness and housing interventions — “Housing First,” emergency financial assistance, case management, legal assistance in housing court, and housing vouchers — with more on the way. 

The section also features J-PAL North America’s 2019 Evidence Review, “Reducing and Preventing Homelessness: Lessons from Randomized Evaluations,” which synthesizes results from 40 rigorous evaluations of 18 distinct programs related to homelessness prevention and reduction in North America. 

The Generating Evidence section houses seven modules on foundational concepts of rigorous impact evaluations such as ethics, data and measurement, and opportunities for randomization, and how to apply them to evaluations in the homelessness sector. These resources build upon J-PAL’s experience training over 30,000 learners over two decades to become better users and producers of evidence. 

“We are proud to be launching the Homelessness Evaluation Resource Hub,” says Laina Sonterblum, a J-PAL North America policy and communications manager who oversees the organization’s housing and homelessness portfolio. “These resources are informed by over a decade of experience working with partners and researchers to understand the current literature and build the base of rigorous research on the best ways to address homelessness. We’re hoping the hub can provide a free, accessible entry point for anyone curious about how evidence can be a tool for learning and maximizing the effectiveness of programs and policies.”

The resources in the hub are also informed by nearly 20 informational interviews with prominent researchers, intermediaries, government leaders, and service providers in the region and build off a decade of experience working with partners and researchers to build the base of rigorous evidence on the best ways to address homelessness. J-PAL North America developed these resources in close collaboration with partners at LEO at Notre Dame and is especially grateful to David Phillips, who provided meticulous guidance and subject matter expertise. 

Explore the Resource Hub. 

Hashim Sarkis will step down as dean of the MIT School of Architecture and Planning (SA+P) at the end of June 2027. During his 12 years as dean, Sarkis elevated the school’s role and impact by creating new academic centers, adding more support for students, and, quite visibly, moving into a new home in MIT’s renovated Met Warehouse building. 

To an unusual degree, these achievements are interconnected: The Met Warehouse, dedicated this month, features innovative and expanded spaces for education, research, and public engagement. The building enables SA+P to add programs, host interdisciplinary work, and stage events of Institute-wide interest. 

Sarkis, the Elizabeth and James Killian (1926) Professor at MIT, and a professor of architecture and urban planning, also led the Institute’s “One Community = One Campus” planning project from 2016 to 2018, which conceptualized MIT as a contiguous urban space. The report helped MIT add sustainable infrastructure as well as new buildings, from dormitories to the theater arts and music buildings — and now the Met Warehouse. 

For Sarkis, providing more support for SA+P students is as important as any other accomplishment. The school will provide full tuition support in multiyear graduate programs, starting with new students in the fall of 2027. 

“I do believe education is a right for every student,” Sarkis says, when asked to cite the most meaningful changes he has helped enact. 

In a letter to the MIT community, Provost Anantha Chandrakasan wrote that Sarkis had crafted “a remarkable tenure as dean,” one that has “advanced a distinctive role for SA+P within MIT: connecting technology to society through design, planning, making, and creative practice.”

Sarkis, a lauded architect who has published widely and runs an international design practice, became dean in January 2015. He will take a sabbatical in the 2027-28 academic year, then return as a professor and head of the MIT-LUMA Lab. 

In his letter to the community, Chandrakasan also announced the formation of a search committee to identify the next dean of SA+P. The 17-person committee is being chaired by Justin Steil, professor of law and urban planning in DUSP.

The “transformative power of design”

MIT’s School of Architecture and Planning is a broad-ranging place, encompassing the Department of Architecture; the Department of Urban Studies and Planning; the MIT Media Lab, which is home to the graduate program in Media Arts and Sciences; the Center for Real Estate; the program in Art, Culture, and Technology; the Leventhal Center for Advanced Urbanism; and the Morningside Academy for Design. One of the hallmarks of Sarkis’ tenure has been the growth of existing interdisciplinary programs at SA+P and the development of new ones. In 2016, a gift from the Leventhal family expanded the Center for Advanced Urbanism, established in 2013, and renamed it in honor of Norman B. Leventhal ’38. The center enables research and hands-on projects addressing complex design and planning challenges in cities globally. 

During Sarkis’ tenure, MIT also introduced an undergraduate minor in design in 2016 and relaunched its bachelor of science in art and design in 2018, expanding opportunities for students across the Institute. The school also established DesignX, an accelerator supporting entrepreneurship in design and the built environment.

In 2020, MIT launched the Mobility Initiative, bringing together researchers from across the Institute to examine the future of transportation and mobility. Led by Professor Jinhua Zhao, now head of the Department of Urban Studies and Planning, the initiative connects research in transportation, technology, urban planning, and policy.

In 2022, with support from the Morningside Foundation, the Institute founded the Morningside Academy for Design (MAD), an interdisciplinary design center allowing for campus-wide collaboration. And in 2024, with support from the LUMA Foundation, SA+P launched the MIT-LUMA Lab, which works across a wide range of fields, including design, science, technology, and art, to explore solutions for climate-based and other environmental challenges.

In a different vein, SA+P also collaborated with the MIT Schwarzman College of Computing this year to establish the MIT and HPI AI and Creativity Hub (MHACH), which aims to further work in design and computing at a time of rapid expansion for AI applications. 

Three of these centers — LCAU, MAD, and MIT-LUMA Lab — are located in the transformed Met Warehouse building, a leading example of adaptive reuse in architecture and engineering. The huge brick edifice, which initially had tiny window slits bringing in minimal light, was used for about a century as a storage facility, until 2015, when MIT began exploring other possibilities for the building.

By 2018, the concept of moving SA+P into the Met Warehouse had gained traction, with Sarkis publicly telling MIT News, “It’s about really creating a design hub for MIT on the campus. ... Moving does not address just the school’s aspirations, but MIT’s aspirations.” 

After working with the Cambridge Historical Commission, the project architects, Diller Scofidio + Renfro, replaced large segments of brick wall with glass sheets, added skylights, and reconfigured the interior, which now has multiheight design studios, modular classrooms and common spaces, an auditorium, public galleries, a large entrance lobby with a café, and building-long corridors on all floors. For almost a decade, Sarkis served as the key driver of the project — and was an advocate for adaptive reuse, rather than creating a new building requiring a greater carbon footprint. 

“I think it sends a very good message that this vanguard school of architecture, at the Massachusetts Institute of Technology, is moving into a historic building and adapting it for the future,” Sarkis told MIT News this summer. 

At the building’s formal dedication ceremony on Oct. 1, MIT President Sally Kornbluth called the Met Warehouse “a testament to the transformative power of design, which has been central to MIT from the very beginning.” She also heralded it as a model for education, noting that future learning in many fields may call for “exactly like the kind of hands-on, in-person, collaborative problem-solving the new Met was made for. … It’s also primed to help the rest of MIT meet the moment.”

The many sources of design and democracy

Sarkis grew up in Beirut, Lebanon, with a childhood interest in architecture. His views about the civic applications of design have long had many sources. He received his BA in architecture from the Rhode Island School of Design in 1987, then earned an MA in 1989 and PhD in 1995, in architecture, from Harvard University. At Harvard, his PhD work included political philosophy, as he studied with legal theorist Roberto Mangabeira Unger and philosophers Hilary Putnam and John Rawls, among others. 

Sarkis was a professor at Harvard’s Graduate School of Design from 1998 until he joined MIT in 2015. He has published widely, including the 2003 book “Circa 1958: Lebanon in the Pictures and Plans of Constantinos Doxiadis.” He edited the 2002 volume “CASE: Le Corbusier’s Venice Hospital and the Mat Building Revival,” and co-edited, with Eric Mumford, the 2008 volume “Josep Lluís Sert: The Architect of Urban Design, 1953-1969.” He is also co-author, with Roi Salguiero Barrio and Gabriel Kozlowski, of the 2020 book, “The World as an Architectural Project.” 

In 1998, Sarkis also established his practice, HashimSarkis Studios, which has offices in Lebanon and Massachusetts. Among his best-known works are the Byblos Town Hall in Lebanon, completed in 2016, which features three volumes rising above a glass-enclosed ground floor, to represent and help constitute the transparency needed for democratic government. His first major project, Housing for the Fishermen of Tyre, also in Lebanon, was cited as one of the most significant buildings of the century in the “Phaidon Atlas of 21st-Century World Architecture.”

During his upcoming sabbatical, Sarkis will work on a variety of projects in locations including Venice, Egypt, and Armenia. 

In addition to his many duties as dean, Sarkis served as the curator of the Venice Biennale’s 2021 International Architecture Exposition. The exhibition’s theme was a question Sarkis has long contemplated: “How Will We Live Together?” Featuring work conceptualized at many scales, the exhibition displayed projects by 112 designers from 46 countries and was critically acclaimed; The New York Times called it “a case study for how to begin to tackle such questions.”

A dose of optimism

Sarkis’ seriousness of purpose as SA+P dean has long meshed with what he has called a “quirky” sense of humor, in the MIT vein. In 2016 he served as a judge for the “Crossing the Charles” competition, in which dozens of inventive MIT-designed watercraft floated across the Charles River to mark the 100th anniversary of MIT’s move from Boston to Cambridge. A parade also unfolded on the bridge carrying Massachusetts Avenue across the river. 

In an echo of those events, last month SA+P organized its own procession into the Met Warehouse, complete with costumes gesturing at the Bucentaur, the boat that in 1916 carried MIT’s charter across the river. The procession was conceptualized and directed by MIT Professor Azra Akšamija, and developed in collaboration with many students, faculty, and staff. 

Meanwhile, when it comes to the experience of having other architects redesign the Met Warehouse, Sarkis quips, “I learned to be a client.” 

More seriously, talking about high points of his tenure as dean, Sarkis quickly calls the organized visioning process for the Met Warehouse “inspiring,” adding, “We needed a common framework, and faculty were able to project forward and identify it.” The building, Sarkis emphasizes, helps reinforce what he believes is central and distinctive about design work at the Institute: “the MIT model of conducting research and education at the same time.” 

In the face of current challenges confronting education, Sarkis steadfastly stuck with the Met Warehouse project, helping complete it while continuing to build up the School of Architecure and Planning and solidifying MIT’s place at the leading edge of design. That may be a larger sign that such progress remains possible. 

“Optimism is integral to our fields,” Sarkis says. 

Each year, Climate Week NYC brings together more than 100,000 people in more than 1,000 events across the city to discuss climate challenges, explore solutions, and spur action. Participants come from industry, academia, philanthropy, nonprofits, government, and finance and venture capital. And this year, the mix included a strong, cross-campus presence from MIT.

The MIT community could be seen multiple days during Climate Week, with appearances by Evelyn Wang, vice president for energy and climate, at the official opening ceremony discussing artificial intelligence and the climate equation; an event co-hosted by MIT and the Bezos Earth Fund on climate innovation; and 14 sessions organized by the MIT Climate Project and eight MIT departments, labs, centers, and initiatives — including the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), the MIT Sloan Sustainability Initiative, the Center for Transportation and Logistics (CTL), MIT Lincoln Laboratory, MIT Open Learning, the MIT Initiative for New Manufacturing (INM), the MIT Climate Policy Center, and the Priscilla King Gray (PKG) Center for Social Impact.

“The MIT Climate Project is a whole-of-MIT mobilization, but no single institution can deliver the climate solutions the world needs — from reducing greenhouse gas emissions to adapting to a changing climate and building more-resilient communities and systems,” said Wang, who is also the Ford Professor of Engineering in the Department of Mechanical Engineering. “Climate Week New York is important because it convenes the range of stakeholders and sectors that must work together to confront these challenges. When we connect the MIT community with this global network, we uncover powerful possibilities to strengthen not only our own efforts, but the world’s capacity for change.”

One location, numerous events

Climate Week NYC was held Sept. 21-27 at venues across Manhattan and other New York boroughs. Utilizing multiple spaces at the Dream Downtown Hotel in the Chelsea neighborhood of Manhattan, the MIT coalition attracted more than 700 attendees for events ranging from small, private conversations to workshops and panel presentations.

Larger sessions included “The Future of Data Centers: Technologies to Change the Paradigm.” “Data centers are at an inflection point, facing interconnected technical, operational, economic, and community constraints that demand cross-sector dialogue and innovation,” says Gang Chen, the Carl Richard Soderberg Professor of Power Engineering and faculty director of the Climate Project at MIT.

Chen, who leads the Data Centers of the Future frontier for the Climate Project, convened a panel of experts across research and industry to address technologies that can change the paradigm. “Technology can't solve all the challenges we’re facing with data centers, but technology has a significant role to play in shaping a future role that is more sustainable and better for the communities that are home to these facilities,” Chen says. “This session was a productive conversation on data center challenges and the potential solutions to overcome them.” 

The workshop “Next-Generation Super Pollutant Solutions: Challenges and Opportunities,” hosted by Jesse Kroll, a faculty director and lead for the Super Pollutants frontier for the Climate Project, convened speakers from the Environmental Defense Fund, Spark Climate Solutions, and across MIT labs and initiatives. 

Accounting for nearly half of all global anthropogenic warming to date, super pollutants currently lack viable solutions for adequate abatement. Many super pollutants have shorter atmospheric lifespans than carbon dioxide, with solutions providing an “emergency brake” to decrease peak warming in our lifetimes. Investments in tackling super pollutants can generate economic benefits, including lowering health-care costs and increasing productivity, and require cross-disciplinary teams to develop and advance the next-generation solutions to meaningfully address super pollutant emissions. 

“Super pollutant mitigation is getting a lot of attention as an ‘emergency brake’ for near-term climate warming. But a huge fraction of our super pollutant emissions simply cannot be mitigated with current technologies and approaches,” said Kroll, the Peter de Florez Professor in the Department of Civil and Environmental Engineering. “Our session focused on the innovation — technical and otherwise — needed to tackle these hard-to-abate pollutants.”

Other events included:

• “2026 State of Supply Chain Sustainability Report” with the MIT CTL
• “Building Flood Resilience” with MIT Lincoln Laboratory
• “Climate Communication for Impact” from the MIT Climate Project
• “Climate Impact Founder and Funder Connect” with the PKG Center for Social Impact
• “Educating Tomorrow's Climate Leaders: An MIT Perspective” from the MIT Climate Project
• “Trading for Food Security in a Changing Climate” with J-WAFS 
• “Industrial Decarbonization: Pathways to Productivity and Growth” with MIT INM
• “Mobilizing Climate Knowledge for Action” with MIT Open Learning
• “Rethinking Climate Innovation” from the MIT Climate Project
• “What is Sectoral Acceleration and How Do We Fund It” with the Sloan Sustainability Initiative
   

Rethinking the climate innovation pipeline with the Bezos Earth Fund

A critical climate challenge is moving from breakthrough technology to real-world impact at scale. MIT and the Bezos Earth Fund brought together leaders from industry, venture capital, government, academia, philanthropy, and startups to explore solutions for a stronger innovation pipeline. 

A panel of MIT faculty and alumni spinout leaders Asegun Henry, Seonghoon Woo, Ariel Furst, and Assil Halimi, moderated by Ray Rothrock, venture capitalist and life member of the MIT Corporation, explored the period between a promising scientific invention and commercial deployment. For many breakthroughs that can benefit climate and nature, that journey requires more early-stage science and engineering research, specialized testing infrastructure, validation, patient capital, and pathways to demonstration and pilot projects.

“A breakthrough in the lab is not yet impact in the world. For climate and energy technologies, we need to think about the entire journey — from discovery and invention through validation, commercialization, and deployment — and build better pathways through the gaps along the way,” Wang said in a conversation with Tom Taylor, Bezos Earth Fund president and CEO. 

Tapping into global nexus to find and scale solutions

New York Climate Week is a global nexus for climate, where the connections required to develop, test, and scale potential solutions form. Across the board, MIT sessions addressed the need for solutions to be large in magnitude, technically feasible, and contextually realistic. 

 “Even when a technology is low-cost, it doesn’t mean it will diffuse naturally or get widely adopted,” said Claire Walsh, global director of policy and communications at MIT’s Abdul Latif Jameel Poverty Action Lab. “Frontier technologies are often more expensive to start, so that means it’s even more important for scientists and engineers to think about end user adoption, and their incentives and constraints, from the start.”

Patients with glioblastoma, an aggressive type of brain tumor, usually undergo surgery to remove the tumor. However, it’s difficult for surgeons to remove all of the cancer cells, and the tumor often recurs.

MIT researchers have now designed an implantable drug-delivery device that they hope could help prevent recurrence of glioblastoma. Their device contains a reservoir that can release drugs over an extended period, along with ultrasound transducers that use sound waves to help drugs spread farther through the brain and bypass the blood-brain barrier.

Such a device could be implanted in the brain during surgery, then gradually release drugs that would help kill the remaining tumor cells. After implantation, a wireless controller can be used to program the exact ultrasound dosages to be delivered, enhancing the reach of the delivered therapy.

“We have 24 transducers in one ultrasound array, which can help a given drug bypass the blood-brain barrier and enhance the drug infusion. The device also gives doctors options in terms of the size, the length, and the number of infusions,” says Canan Dagdeviren, an associate professor of media arts and sciences at MIT and the senior author of the study.

In a paper appearing today in the journal Device, the researchers showed that their ultrasound device allowed molecules to spread further after being released, in tissue models and in a mouse study. 

MIT graduate student Sarah Ornellas and Jason Hou PhD ’26 are the lead authors of the study.

Enhanced by ultrasound

Glioblastoma is a rare but deadly cancer, with a little more than 10,000 cases diagnosed in the United States per year. On average, patients survive 12 to 15 months after diagnosis. Patients typically undergo surgery to remove as much of the tumor as possible, followed by radiation and chemotherapy.

Chemotherapy drugs are usually given either as pills or an intravenous infusion, but in recent years, scientists have developed drug-delivery wafers and hydrogels that can be implanted directly in the skull. That can help to eliminate the side effects of chemotherapy and ensure that a higher concentration of the drug reaches the brain.

Those devices work by passive diffusion of drugs, but the MIT team wanted to design a new device that would allow for greater control of the timing of drug release. They also wanted to incorporate ultrasound arrays to enhance the distribution of drug molecules. 

Previous research has shown that ultrasound helps drug molecules to disperse more widely, by creating convective flows that help travel them longer distances. The mechanical oscillations generated by ultrasound waves also temporarily increase the permeability of the blood-brain barrier, helping drug molecules get into the brain.

Dagdeviren had previously designed a tiny cannula, about as thin as a human hair, that could be implanted in the brain to deliver drugs. She also built an implant called ImPULS, which uses tiny ultrasound transducers to deliver deep brain stimulation.

In the new study, her lab combined these technologies to create LUCID (Long-term Ultrasound-enhanced Convective Injection Device) — a flexible implant as thin as a sheet of cardstock. A drug-delivery cannula is 3D-printed directly onto an array of 24 miniature ultrasound transducers. These transducers generate ultrasound waves right at the tip of the needle, helping drug molecules to diffuse farther into tissue after they are released.

“Getting a drug into the brain is only part of the challenge. It also needs to spread through the surrounding tissue. We brought a delivery channel and a tiny ultrasound array together in one implant to help molecules reach a larger area, even during slow infusion,” says Hou.

The implant’s reservoir carries about 100 microliters of fluid, and infusion is supplied by a passive osmotic pump, while ultrasound can be controlled wirelessly through Bluetooth. The device also contains a small battery that can be recharged wirelessly. 

In tests in a “tissue phantom” — a gel-like material engineered to mimic human tissue — the researchers showed that ultrasound-aided delivery spread drug molecules much farther than when the drugs were delivered without ultrasound. 

“By enhancing that distribution locally and programmably with ultrasound, you can reduce systemic toxicity in nontarget organs, while the therapy that you’re using has a better chance of reaching whatever tumor cells are within the affected area,” Ornellas says.

Wider distribution

The researchers also tested their system in mice, using it to deliver an MRI contrast agent. When the ultrasound array was activated, the contrast agent spread further through the brain than when ultrasound was not used.

If developed for use in patients, the drug cannula and ultrasound array would be placed inside the skull, while the part of the device containing the battery and other electronics could sit outside the skull, the researchers say.

In addition to delivering small-molecule drugs, this technology could also be used to deliver immunotherapies or nucleic acids, including gene therapies. It could also be potentially used in organs other than the brain.

“We started with the brain as a follow-up to our ImPULS technology, but eventually this can be used for other soft tissue treatments for different types of drugs, different types of interventions in deep body tissue,” Dagdeviren says. “We are showing that we can make any kind of payload be distributed in a better way.”

Other authors of the paper include Michal Nowicki, a research associate at Massachusetts General Hospital; Jerry Li, a recent graduate of Harvard University; Heloise Leblanc, a graduate student at Boston University; Betul Serra Tulu, an MIT undergraduate; David Sadat, a research specialist at MIT; Marco Mineo, an instructor in neurosurgery at Harvard Medical School; Steve Ramirez, an associate professor of psychological and brain sciences; and E. Antonio Chiocca, a professor of neurosurgery at Harvard Medical School and Massachusetts General Hospital. 

The research was funded by the MIT Media Lab Consortium and the National Institutes of Health.

With the Big Bang, the universe burst into existence as a hot and dense soup of electrons and subatomic particles. This primordial ionized plasma, initially smaller than a single atom, rapidly expanded and cooled. In the process, particles in the soup slowed enough to bind with electrons, forming electrically neutral hydrogen. 

As this neutral hydrogen accumulated, the effect was like a shroud, preventing light and other forms of radiation from freely passing through. Around 380,000 years after the Big Bang, the universe was plunged into a cosmic “dark age.” 

Now, a new computer simulation is giving scientists a detailed view of how the first galaxies, stars, and other structures could have unfolded from that time, to eventually pull the universe out of its dark age. 

In a paper appearing today in the Monthly Notices of the Royal Astronomical Society (MNRAS), physicists from MIT, Harvard University, and elsewhere present Lumina — a large-volume, high-resolution simulation that follows the early universe from the dark ages through the next 2 billion years of cosmic evolution. 

Two pivotal transformations

Lumina covers a huge patch of the early universe that spans 500 megaparsecs, or about 1.6 billion light-years wide. In that space, the simulation tracks the evolution of dark matter, gas, stars, and radiation (such as photons), across enormous cosmic scales and also zooming down to the detail of an individual developing galaxy. 

Over the 2 billion years that Lumina simulates, it captures the emergence of two huge transformations in cosmic history: hydrogen re-ionization and helium re-ionization.

Hydrogen re-ionization is a period when early stars were able to push out enough ultraviolet light to interact with neutral hydrogen and strip it of its electron. This “re-ionizing” prevented the hydrogen from absorbing photons, instead allowing light to travel freely. Hydrogen re-ionization helped to lift the veil of neutral hydrogen — a process that Lumina captures in detail for the first time. 

The simulation also tracks helium re-ionization, a process similar to its hydrogen counterpart, in which much higher-energy light breaks apart neutral helium. 

In its detailed simulations, Lumina revealed that hydrogen re-ionization was likely driven by light from early galaxies and stars. In contrast, helium re-ionization was fueled by much more energetic early supermassive black holes in their active, accreting phases. Together, this represents the first time a simulation has captured both hydrogen and helium re-ionization.

“Lumina does everything from small-scale star and galaxy formation to large-scale re-ionization of hydrogen and helium, in a volume that is 100 times larger than previous best simulations,” says study author Mark Vogelsberger, a professor of physics at MIT. 

He and his colleagues are making Lumina available to the scientific community so that scientists can compare its detailed simulations of the evolution of early cosmic structures with snapshots taken by new and future telescopes. Then, they might begin to piece together the processes that shaped the first galaxies, stars, and structures in the universe. 

The study’s MIT co-authors are Xuejian (Jacob) Shen and Teodora-Elena Bluichi. Additional authors include first author Oliver Zier (a former postdoc in the Vogelsberger Lab), Rongrong Liu, Sonja Koehler, and Lars Hernquist of the Harvard and Smithsonian Center for Astrophysics; Aaron Smith of the University of Texas at Dallas; Rahul Kannan of York University in Canada, and Volker Springel and Rüdiger Pakmor of Max Planck Institute for Astrophysics in Germany.

Cosmic computation

Lumina takes its name from the Latin word meaning “lights.” At the heart of Lumina is IllustrisTNG, which was previously developed by scientists at MIT and elsewhere, including members of the Lumina team. IllustrisTNG is a large-scale simulation that tracks the interactions of dark matter, gas, and other processes involved in forming galaxies, from the Big Bang to the present day. 

In building Lumina, the team refined IllustrisTNG’s code to enable the simulation to track the formation of galaxies with the same level of detail but throughout a much larger volume. They combined this leveled-up galaxy model with a model of radiation transport, which simulates how different forms of radiation such as ultraviolet light interact at extremely large, cosmic scales to capture processes such as hydrogen re-ionization. 

The new and improved simulation resolves extremely fine details across huge scales. In practice, the simulation encompasses half a trillion individual elements, including dark matter particles and gas cells, which is about 30 times higher-resolution than IllustrisTNG. Lumina captures all this detail and evolves it forward in time, across an enormous patch of about 500 megaparsecs, which is 100 times larger in volume than previous simulations. 

Running the calculations for every single cell over 2 billions years of cosmic time, and across extremely large and very small scales, involves a significant amount of computing power. The team ran Lumina on Frontier, one of the world’s most powerful supercomputers, based at Oak Ridge National Laboratory in Tennessee. 

“At peak scale, the calculation brings together the equivalent of more than 100,000 CPU cores and around 15,000 GPUs,” says Shen. “Making all of those processors communicate efficiently while continuously evolving trillions of interacting pieces of information is itself an extraordinary feat of computer engineering.”

Full zoom

Lumina begins its simulations at around 45 million years after the Big Bang, in the midst of the dark ages, when neutral hydrogen dominated the early universe. The researchers set the simulation with initial conditions approximating what physicists theorize should have existed in such a dark cosmic period. 

They then let Lumina run to calculate how matter at those times, in the form of gas and dark matter, interacts across the simulation’s half-a-trillion cells. Simultaneously, the simulation calculates where and how radiation, such as ultraviolet light from stars, emerges and interacts with its surroundings.

On the project website, the team provides a number of videos that depict the various scales, time periods, physical processes, and layers of cosmic structures that Lumina simulates. Examples include a “zoom-in” from the full, large-scale patch of the universe to a single, disk-shaped galaxy; and a time-lapse of the full volume, over 2 billion years, that captures the pattern of hydrogen as it is re-ionized over time. 

“On the one hand, it’s evolving dark matter as well as the gas in the universe, and on the other, it’s also tracking how radiation travels,” Zier explains. “We see dark matter and gas start to clump in these over-densities. And when we zoom in, we can see gas is falling into these dark matter haloes. Zooming in more, we see this is where the first galaxies form. And the first stars form in those first galaxies. Those stars then create radiation. The simulation then tracks that radiation, and we can zoom way out to see how that radiation travels out from stars, through the universe, until at some point it ionizes some neutral hydrogen.”

“Other simulations cannot zoom in as far as this,” Vogelsberger notes. “The difference between the smallest and largest scales that we simulate is larger than in any other simulation.”

Looking ahead, the team plans to apply Lumina to map the large-scale structure of the early universe. The simulation can also help to predict the gravitational-wave patterns that early galaxies and black holes might produce. Whatever Lumina simulates could soon be compared with actual observations from new and upcoming telescopes.

“One of Lumina's major advantages is its sheer size,” Shen says. “It produces enormous populations of simulated galaxies, finally allowing us to make comparisons with the very large galaxy samples that upcoming surveys will observe.”

This research was supported, in part, by NASA and the National Science Foundation, and used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Advanced Scientific Computing Research programs in the Office of Science of the U.S. Department of Energy.

Legal scholar Martha Minow delivered this fall’s Compton Lecture at MIT on Thursday, examining the civic foundations of democracy — and describing how artificial intelligence is undermining it, but could be used to help reinforce traditional U.S. governance. 

“It’s not a good time for democracy or constitutionalism,” said Minow, who is the 300th Anniversary University Professor at Harvard University, and a prominent expert in constitutional law and human rights. She noted a litany of challenges to democracy in recent years, including violations of laws and norms, the stifling of free speech, a diminution of congressional authority, disregard of legal rulings, the common vilification of others in society, and more. 

Recent Gallup polling, Minow observed, shows 77 percent of people saying that the founders of the U.S. would be disappointed in the contemporary condition of the country. 

“Many people genuinely wonder whether this nation’s system of government and rule of law, ignited 250 years ago, will survive,” Minow said.  

Her remarks assessed the state of the U.S. in terms of what she called four key “ingredients” of democracy: education, reliable and accessible information, security from violence, and fairness. Minow evaluated how AI has, among other things, influenced these areas of life — but also suggested ways people could use contemporary technology to help. 

“It’s very familiar to hear blame attributed to digital technologies and experts of all stripes, but a turnaround, I believe, is genuinely possible if people at MIT and elsewhere pour time and talent towards real and much-needed solutions,” Minow said. 

A substantial portion of her remarks focused on the pitfalls of AI in education. That issue compounds some other troubling trends: The U.S. already has large local and regional disparities in educational funding, Minow noted, while schools have actually become significantly more segregated in economic and ethnic terms over the last three decades. 

In this context, AI threatens to further weaken independent-thinking skills, Minow suggested, just when greater understanding of civic issues is absolutely vital. 

“As AI surges, I think we have to learn to be smarter about how to use it, how to regulate it, and how to actually educate people about the costs of mindless using,” Minow said. She added: “Dominant AI platforms supercharge the strategies that are deployed by social media companies, inducing passivity in people … Leading AI models and interfaces and sycophantic elements endanger the development particularly of young people’s capabilities to think, to remember, and to engage in critical thinking.” 

That trend away from cognitive effort, she suggested, can be changed — perhaps through AI tools that act more like tutors and are designed to enhance people’s deep thinking.

“Existing LLMs, model training, and interface design can offer nudges and questions and hints rather than replacing student work, but there’s so much more that could be developed, and more effectively, to be trustworthy, and to deepen human activities and curiosity, rather than replacing people,” Minow said.

To the audience, she added, “AI tools could do much more of that … And I believe that you, the people here, could develop better tools than the ones that are out there. And make better assessments, more meaningful and cheating-resistant.” 

Minow’s talk, “Constituting Democracy in the Era of AI,” was delivered to a large audience in MIT’s Huntington Hall, Room 10-250 on campus.

MIT President Sally A. Kornbluth delivered introductory remarks to the audience. The Karl Taylor Compton Lecture Series, introduced in 1957, is the highest-profile event of its kind at MIT. Karl Taylor Compton was MIT’s ninth president, serving from 1930 to 1948, and then becoming chair of the MIT Corporation from 1948 to 1954.

“He guided MIT through the Great Depression and World War II,” Kornbluth said, “transforming the Institute from an outstanding school for training job-ready engineers to a great global research university.” 

She added: “He was also a deeply committed patriot who helped harness the intellectual power of America’s research universities to serve the nation during World War II.” 

Kornbluth called Minow “a legal scholar of extraordinary intellectual scope,” and a “dedicated educator whose work has shaped how we think about the law and our own humanity, as individuals and as a society.” 

Minow has been a faculty member at Harvard Law School since 1981, and served as dean of the school from 2009 through 2017. Minow earned her BA in history from the University of Michigan, an MA in education from Harvard, and a JD from Yale University.

Minow’s books include “Making All the Difference” (1990), “Partners Not Rivals” (2002), and “When Should Law Forgive?” (2020). 

In her talk, Minow also discussed the civic effects of misinformation, threats of violence, and multiple dimension of societal fairness. Modern media technology has led to a 75 percent reduction in journalists in recent decades, Minow observed, with an attendant rise in corruption in places without local media. Civic-minded technologists, she proposed, should work towards establishing a widely-used “information commons,” or many forms of them, to help people access more reliable information. 

Meanwhile, when it comes to basic security in society, Minow warned, “We’re on the brink right now. I know a lot of judges, and every one of them has a credible threat of violence against them. In America. This is not acceptable.” 

For all the challenges to democracy and traditional civic norms, however, Minow sounded positive notes throughout her remarks, pointing out that there are many opportunities to create new forms of reliable information, education, and community relations. 

“We have to actually invent the world that we want to live in,” she offered. 

Minow’s remarks were followed by a Q&A session in which Kornbluth read aloud questions submitted by the audience — and asked her to characterize her concerns about present trends. 

“I worry about the loss of the Enlightenment,” Minow said. “I worry about the loss of the belief that reason, and testing hypotheses, and rejecting myths in the face of evidence, and the toleration and rights and expansion of participation that came along with the Enlightenment, that’s what concerns me the most. That’s why the disinformation issue for me is so important, that’s why the loss of critical thinking in schools is so important.”

She added: “I’ve spent much of my own career thinking about mass violence. What happens when people don’t understand each other, and are afraid. And it’s terrible, and we don’t want to be there. And I do view the Enlightenment as a time when people learned that actually having mass wars is a bad thing, and coming up with toleration is a good thing, and testing our ideas in light of evidence other people can share can produce a better life for everybody. I worry we’re abandoning that right now.”

At the MIT School of Humanities, Arts, and Social Sciences (SHASS) 75th Anniversary Symposium, speakers celebrated the school’s value and contributions, while exploring how artificial intelligence is transforming many aspects of teaching, research, and society.

The symposium was held Sept. 24-25 in the Linde Music Building’s Thomas Tull Concert Hall. Scholars, students, staff, and alumni from across SHASS and MIT gathered for the event, which kicked off with welcoming remarks from MIT leadership. 

“How should we think about MIT’s School of Humanities, Arts, and Social Sciences? With enthusiastic appreciation and gratitude,” said President Sally Kornbluth.

The school’s origins date back to the Lewis Committee Report, commissioned by MIT and published in 1949, which called for stronger integration between scientific and technical topics and humanistic scholarship and teaching.

Kornbluth noted that, much like when the school was founded just after World War II, the world faces uncertainty as it grapples with the broad implications of artificial intelligence.

“AI has suddenly arrived with enormous consequences for both research and education,” she said. “As we face the challenges of our own time, and our own society, it’s clear that MIT has never needed your particular insight and guidance more than we do now.”

In opening remarks, Provost Anantha Chandrakasan described the importance of a human-centered approach to technology, one that considers both its efficacy and its impacts. He lauded many of the new research projects happening through the MIT Human Insight Collaborative, a strategic initiative launched in 2024.

“Today — a time of rapid, AI-driven change — the arts, humanities, and social sciences are as important as ever,” he said. “To be able to contribute effectively to solving the world’s great challenges, it is not enough to gain technical mastery.”

Chancellor Melissa Nobles recalled how, during her tenure as SHASS dean from 2015 to 2021, reading the positive feedback from students in their SHASS course assessments reinforced the value of the school’s teaching.

“MIT students have a range of interests that draw them to our classes that may be invisible to their STEM professors, but that we very well know our students have,” said Nobles, who is also a professor of political science.

Agustín Rayo, the Kenan Sahin Dean of SHASS and professor of philosophy, noted that, while research in the school plays a key role in addressing global issues such as climate change and AI, the value of the work in SHASS should not be measured by practical application alone.

“Education should also help us ask what is worth doing, what do we owe one another, and what makes a life worth living,” Rayo said. “Some research matters because it helps us understand the histories, cultures, and social structures that have made us who we are. Some things matter because they enrich human life.”

Scholarship from across SHASS and beyond 

Over the symposium’s two days, research presentations, panel discussions, and performances offered attendees opportunities to engage with the role of SHASS in exploring today’s biggest societal questions.

“We gather not so much to look back over the past 75 years, but to showcase where we are now, and share what we urgently aim to tackle together in the years ahead,” said David Kaiser, Germeshausen Professor of the History of Science and professor of physics at MIT, who also served as chair of the symposium planning committee.

The first day included a session on teaching and learning innovations. Faculty presented on the success of educational programs housed within SHASS, including the MIT Indigenous Languages Initiative Master's Program, the Master in Data, Economics, and Design of Policy (DEDP), and MISTI, the hub for global experiences for MIT students.

Stephanie Seed, associate professor of literature, spoke about why she and others are working to reintegrate classic books into their teaching.

“MIT, of course, is an institution unusually oriented towards the future,” she said. “Our students are trained to imagine and create worlds that don’t yet exist. And it’s precisely this future orientation that makes reading the past especially important here.”

Eric Klopfer, professor of Comparative Media Studies/Writing and co-author of MIT’s recent report on AI and instruction, said this is a moment when instructors must reassess how courses are taught.

“I don’t know exactly what that looks like, but I do think it means something that’s more than modifying our curriculum. I think it really means rethinking what the educational experience is,” he said.

During a session on computing and society, panelists described different views and research into technology and how it affects humans.

“We project aspects of ourselves onto computational systems,” said MIT Professor D. Fox Harrell during his talk about seeing “selfness” in machines. 

“What makes an AI system is not just the code, not just the programming or the algorithm, it’s the fact that we narrate it as being intentional,” he said.

Program in Science, Technology, and Society Professor Sherry Turkle offered a skeptical view of human-technology interaction, particularly with AI chatbots, which she describes as “intimate machines.” 

“If social media came for our attention, I argue that chatbots are coming for our capacity for attachment, which is deeper and much more troubling,” said Turkle.

Professor David Autor, head of the Department of Economics, said it’s an exciting time to be working at MIT, where scholars are collaborating to explore AI’s impact on society.

“I don’t think there’s a close analogy to a moment when everyone felt the world change so quickly,” he said. “The stakes feel incredibly high.”

Celebrating the arts and engaging with the future 

The first day concluded with a rousing Music and Theater Arts performance showcase, which began with an excerpt from Stan Lai’s “A Dream Like A Dream,” a play directed and performed by students and instructors in class 21T.100 (Theater Arts Production).

“Variations on the Theme of SHASS 75,” a piece choreographed by Dan Safer, senior lecturer and director of dance programs, combined movement, lighting, and music in a celebration of both the human body and the school’s milestone anniversary.

Student and faculty musicians from a variety of styles and disciplines shared the stage, including Rambax MIT, MIT Concert Choir, and the MIT All-Star Jazz Combo. The showcase included stirring renditions of “Madrigal,” composed by Vice Provost for the Arts Keeril Makan, and “Prayer for Peace.”

On the second day of the symposium, several alumni presented on their current work and the impact of their SHASS experiences.

Jessica Coon PhD ’10, now a professor of linguistics at McGill University, spoke about the leading role MIT Linguistics plays in preserving endangered languages, and how her studies at MIT prepared her to carry on that work.

“SHASS gives us the tools not just to conduct research, but to communicate the impacts of this research across a variety of different audiences and in different ways,” she said.

Ankita Reddy ’19 double-majored in anthropology and biology and is now an MD/PhD student at the University of Pennsylvania. She highlighted her most impactful SHASS courses, including 21A.308 (Global Mental Health).

“This was the first time I was forced to consider how good health care looks different based on social systems and cultural practices,” she said. “SHASS made me more comfortable with, and more curious about, complexity.”

During the symposium’s final session, panelists engaged in a conversation about AI, art, and the implications for creatives in an era where their art can be co-opted and copied. 

“There’s so much praise for new and upgraded technologies,” remarked associate professor of literature Sandy Alexandre. “The question I consistently have is: What does it mean to be an upgraded human being? How are we innovating as technology is innovating?”

Philosopher Justin Khoo said AI’s role in art could be considered a “giant paint brush you don’t have much control over,” adding he could see the creation of new sub-genres of art that are human-only, AI-infused, and purely AI, for example.

Khoo closed by saying he encourages students to “think broadly, and really take seriously the humanistic education here at MIT.”

“A broad understanding of a set of concepts which are widely applicable, not just narrowly applicable, I think that’s what we need more than ever now,” he said.

As the symposium came to a close, attendee Kent Sahin praised the event.

“I’ve attended every session, and this is a fantastic program and a great celebration of the 75th anniversary,” he said. “Clearly, whether it’s AI impact, the impact of climate change, or the impact of political and social change, SHASS is in the right place at the right time.”

Gunter Stein, an expert on control systems and theory who was a longtime MIT adjunct professor and researcher who also worked at Honeywell Labs, died on July 11 in his home state of Minnesota. He was 84 years old. 

Throughout his career, Stein helped to reconcile competing schools of thought surrounding automated control systems, and he worked helped usher in an era of robust multivariable control.

Born in Germany, Stein emigrated with his family to the United States at a young age. The son of a tool and die maker at Fisher Body Works, Stein earned his BS from the General Motors Institute (now Kettering University) in Flint, Michigan, and his MS and PhD in electrical engineering from Purdue University in 1966 and 1969, respectively. He then joined Honeywell Labs, where he spent a more than 50-year career developing systems including aircraft flight controls, spacecraft altitude and orbit controls, and other navigation and control systems for applications as varied as launch boosters, reentry vehicles, ship positioning systems, torpedo engines and autopilots, and precision guided weapons. 

As an engineer at Honeywell, Stein’s incisive and rigorous way of approaching problem-solving quickly garnered attention, catching the eye of the then-director of the MIT Laboratory for Information and Decision Systems (LIDS), Michael Athans, when the laboratory and Honeywell began cooperating on a NASA contract to design the controls for the F-8 aircraft. Stein’s submission on behalf of Honeywell was, at the time, labeled the “most conservative” of the potential submissions, but eventually became the only control system successfully flight-tested. 

Noting Stein’s talent, Athans approached Stein with a pitch to join MIT in 1977. As Stein’s career and personal life were by that point deeply rooted in Minnesota, he was not interested in relocating full-time, but agreed to an adjunct position with the Department of Electrical Engineering and Computer Science (EECS), where he would spend one week per month giving lectures, helping advise graduate students, reading PhD theses, and acting as a principal investigator in LIDS. This arrangement would continue for the next 30 years, and would deeply shape MIT’s overall approach to control theory. 

“Stein immediately struck me as a brilliant engineer,” says Munther Dahleh, the William A. Coolidge Professor in EECS and a member of LIDS, who at the time of Stein’s arrival was a newly hired junior member of the faculty. “As a naive researcher who was more of an applied mathematician than a real engineer, I was struck by how Gunter could see through the mathematics and distill what was truly essential for applications.” 

As Dahleh’s career developed — he would eventually become an associate department head of EECS and the founding director of the Institute for Data, Systems, and Society — his regard for Stein only grew: “Through Gunter’s work at Honeywell and his collaborations with students and faculty at MIT and other universities, robust control entered virtually every area of control applications. He shaped the direction of our field for decades, and his ideas remain a driving force behind many of today’s control applications.”

“Gunter came to LIDS at a propitious time,” says Nils R. Sandell Jr. SM ’71, EE ’73, PhD ’74, who co-taught class 6.291 (Classical and Modern Methods for Control System Design) with Stein. “With the experience on the NASA project and on others, the emphasis had begun to shift from optimal control to robust control. Gunter was a key part of this evolution, with his keen insight, based on extensive experience, of how classical frequency domain control techniques for single-input, single-output systems dealt with model uncertainty.” 

Over the course of the next decades, Stein would work on systems for the B-2 bomber and F-47 aircraft, and for many years would serve as a member of the U.S. Air Force Scientific Advisory Board. “I can attest that, decades later, the flight control design methodology that Gunter and his colleagues at Honeywell developed is still being applied to our most advanced aircraft,” says Sandell. 

Alan Willsky, the Edwin Sibley Webster Professor of EECS (Emeritus), remembered his colleague at LIDS as both a practical and a theoretical force: “Gunter was one of the giants of automatic control. His work at Honeywell on advanced control systems is legendary, but what is equally impressive is his impact on control theory and his influence on generations of control researchers. The period of years when he split time between Minneapolis and MIT had major influences on how control is taught and researched here at LIDS.” 

Years of working with uncertainty and multivariable systems led Stein to think carefully and deeply about famous failures of engineering, including the nuclear reactor disaster at Chernobyl that captured the world’s attention in 1983. Stein saw the disaster as a stark warning to all designers of control systems, not only for nuclear power plants but for aircraft, spacecraft, and indeed all systems “with automatic controls that cannot be done manually and that, if done improperly, can have dire consequences for property, the environment, and human life.” 

In his highly influential 2003 Bode Lecture and essay for Control Systems Magazine, entitled “Respect the Unstable,” he wrote: “We must place renewed emphasis on stating and teaching the principles of our subject clearly and well. The applications out there are simply too serious for us to hide from responsibility under a cloak of mathematics.” Of that famous lecture, Dahleh muses, “his Bode Lecture, which marked the first time the award was given, solidified my view of his remarkable ability to understand very different applications from a common fundamental perspective ... He showed how the challenges posed by complex control engineering systems, from agile aircraft to the Chernobyl disaster, could be understood through the same fundamental ideas that explain the difficulty of controlling an inverted pendulum. Thirty years later, his lecture remains one of the most-cited Bode Lectures and one that has had a clear impact on our community.”

Among other honors, Stein was elected fellow of the IEEE in 1985; awarded the IEEE Control System Society's first Hendrik Bode Prize in 1989; elected to the National Academy of Engineering in 1994; and awarded the International Federation of Automatic Control's Nathaniel Nichols Prize in 1999. 

His impact on the field of control engineering is also measured by the regard of his colleagues, who uniformly remember him as warm, social, and deeply conscientious. 

“Gunter was a great engineer — the greatest I have known — and he was also a great human being,” says Sandell, who notes the great passion with which Stein, in the Bode lecture, enumerated his responsibilities toward society as an engineer. 

“On a personal level, Gunter was incredibly humble and unassuming, and always ready to offer help and support whenever asked,” says Dahleh. “He was a giant in our field and played a major role in shaping it. I am deeply grateful for the opportunity to have learned from him and to have had him as a colleague. He will be dearly missed.”

Predeceased by his parents and wife Nancy, Stein was survived by partner Ann Wynia, siblings Gerry (Lynn) Stein and Gisele Davis, and by many nieces and nephews. A skilled sailor and lifelong outdoorsman, Stein spent much of his life exploring the various coastlines and seas of the world, and the forests and lakes of his native Minnesota. Memorial donations can be made in Stein’s name to the Minnesota Nature Conservancy. 

Generative artificial intelligence models are rooted in ideas of mid-20th century engineers who thought some amount of irrationality was essential for a machine that could think like a human, contends Benjamin Lindquist, an assistant professor in the MIT History Section, who holds an MIT Schwarzman College of Computing shared position with the Department of Electrical Engineering and Computer Science (EECS) and is a principal investigator in the Laboratory for Information and Decision Systems. 

To mimic creative thinking, these AI pioneers intentionally injected randomness into algorithms designed to deterministically solve problems, Lindquist writes in a new paper that appears in the journal Past and Present. In the paper, he traces the origins of AI hallucinations back to this early research and suggests there will be inevitable tradeoffs between creativity and predictability when trying to build machines that mimic human behavior. MIT News spoke with Lindquist about these ideas.

Q: Why did early computer engineers believe they needed to inject randomness and irrationality into AI systems designed for logic and calculation? 

A: There is a long history of many figures in the world of science and art theorizing that chance plays an important part in discovery and creativity — in the ability to originate ideas. They equated creativity with unexpected leaps of logic, or even a dream-like state that allows you to think about things from a new perspective. 

In the early 1950s, one popular idea from John Pierce, who was a prominent electrical engineer at Bell Labs, was about math being valuable in the world of art. The idea was shared by a lot of people working in early computing. When we think of artwork that includes math, we may think of something very orderly and precise, but Pierce came to the opposite conclusion. He concluded that the utility of math is that it could remove order from art. Then in a very calculated way, math could add a burst of the unexpected as a means to deviate from clichés and add an element of irregularity which just might lead to insight. 

One popular way to add irregularity into otherwise predictable computers was through artificial (or random) neural networks. Many early neural networks were built by psychologists, who thought that by enabling scientists to build a model of the brain, artificial neural networks allowed scientists to observe what is happening inside, including how brains make productive mistakes. Rather than being black boxes, researchers believed these systems could open this black box of the mind and let scientists peer inside and see all the messy stuff that was really happening.

But there was another camp in the world of AI who thought that creative thinking was just “normal” thinking done better. It is interesting to look at these two very simplistic heuristics for understanding intelligence and creativity, and how they do and don’t mesh. The debate, then, was about trying to determine what human inventiveness boils down to, and then how to reconstitute human inventiveness in machine form. 

Q: How did these early computer engineers view AI, and how is it different from the way we think about AI today?

A: When we think of AI systems, we think of ChatGPT or Claude. We value and use these systems because they give answers that, most of the time, are correct. One of the things that was most interesting to me in this research was finding out that a lot of the early advocates of these systems valued them for exactly the opposite reason. They wanted a system that, on occasion, gave answers that deviated from their expectations. They already had systems that could deliver reasonable and expected answers. They saw neural networks as valuable because they could give unexpected, perhaps even strange and bizarre answers.

One reason we might view these systems differently today could be because of how they operate. Early on, these systems were confined to laboratories, so there weren’t really any real-world consequences of a system that gives a strange, or wrong, output. But now there are legal and monetary reasons why OpenAI or Anthropic doesn’t want a chatbot that gives unexpected or creative answers. There has been a “sanding down” of strangeness in these systems. They still potentially have that at their core, but it is something that is now largely suppressed.

Q: How did early neural networks that incorporated randomness to simulate human creativity evolve to become the dominant paradigm in AI?

A: For a long time, a specific kind of AI called “symbolic AI” was the dominant approach. Essentially, symbolic AI says the world is based on rules. The role of the AI researcher is to try and reconstruct the knowledge of the world in facts and propositions and feed it into a computer.

Neural networks, with their use of randomness to solve problems, started to gain traction in the 1950s but fell out favor early on. Frank Rosenblatt, a psychologist who was a very important early figure in neural networks, died prematurely; he died accidentally on his 43rd birthday in 1971. He was quite a charismatic and forceful personality, who made a lot of grand promises about what systems based on neural networks could do. By the time he died, a shift toward symbolic AI was already underway. It is possible if, had he lived, things might have turned out differently.

But neural networks never went away. By the 1980s they had shifted more into the world of cognitive science. To become more powerful, and more useful, neural networks needed a lot of data and computational power. That didn’t really arrive until the advent of the internet, when a lot of data became available and computing started to power up. Around 2012, neural networks started to outperform and outpace a statistical form of machine learning, and they kept growing from there.

Q: What lessons can we learn from studying AI’s history that could inform its development? 

A: I think there is a cautionary lesson here. The ideas and experiences of these early engineers tell us that we can work toward quashing hallucinations — we can work toward making AI perform a certain way so it doesn’t produce unexpected or unwanted answers — but there are going to be other consequences of that. These historical figures were onto something. There is a connection between the surprising and creative conclusions AI can offer and errors or hallucinations. There are tradeoffs when we build our systems to behave one way or the other. Maybe it is impossible to be completely at either end of the spectrum, but when we work toward one thing robustly, we often sacrifice something else unintentionally.

When Veronica Calzadilla Sosa transferred to MIT from Miami Dade College in Florida, she was an incoming second-year student with an interest in chemical engineering. She didn’t know how involved she would soon become as a student leader in the department.

She would also go on to discover her competitive side.

At the encouragement of a friend who was then a team captain, Calzadilla Sosa joined MIT’s chapter of American Institute of Chemical Engineers, and the two worked with the Department of Chemical Engineering to build up the team of students representing MIT in the organization’s lively chemical engineering competitions. As the organization’s competition chair last year and the vice president of external relations this year, she has fallen in love with the club and found joy in bringing students together to work toward a common goal and have fun along the way.

When she first took on the role, MIT was new to the competition, and students were participating in only one of several events. Now, they participate in three categories: ChemE Cube (where teams build a miniature chemical plant that fits inside a 1-cubic-foot cube), ChemE Jeopardy (a “Jeopardy!”-style trivia competition), and ChemE Sports (where teams operate and optimize a virtual chemical plan). 

Calzadilla Sosa also captained MIT’s first ChemE Sports team, working alongside two first-year students. At their first competition, their challenge involved optimizing a distillation column, drawing on concepts Calzadilla Sosa was learning in her separation processes class. The team placed second at regionals.

“The competition was challenging, technical, and at times stressful, but also incredibly fun and rewarding,” she said after the event. “Experiences like this remind me how much engineering extends beyond technical knowledge alone.” 

For Calzadilla Sosa, the experience was about more than the result. It gave her the chance to take on a leadership role, work through unfamiliar problems with her teammates, and help create an opportunity for students who might not otherwise have participated.

Building community has been particularly important to Calzadilla Sosa, who began her undergraduate education in Cuba before moving to the U.S. When she later transferred to the Institute after earning her associate degree from Miami Dade, where she was part of the Honors College, “I was a sophomore for the third time,” she jokes. At that point, many of her new classmates had already spent a year getting to know one another and finding their footing.

She began to find her place in an unexpected setting: office hours.

During her first chemical engineering class at MIT, Calzadilla Sosa regularly went to office hours for help with difficult problems. She soon noticed that she was not the only one struggling.

“I was there because I was struggling with a problem, but then I would see more people also struggling with the same exact things,” she says. “And that, for some reason, gave me this idea that I wasn’t alone in that sense.”

Those shared struggles became a starting point for conversations, friendships, and a support system. She learned that finding a community did not necessarily mean having everything figured out. 

“Sometimes you find your community simply by allowing yourself to struggle alongside other people,” she says.

Throughout her undergraduate experience, Calzadilla Sosa has also explored the many ways chemical engineering can be applied beyond the classroom. 

While studying in Miami, she interned with the U.S. Food and Drug Administration, analyzing data on toxic elements in food, and with the engineering consulting firm Jacobs, where she learned about water and wastewater infrastructure projects in the county. As an MIT student, she has been a materials intern at the medical device company Convatec, and a materials chemistry/chemical engineering intern at the startup Folia Materials. 

In the process, she has gotten a closer look at different industries and begun to figure out which ones interest her most. At MIT, she has become particularly interested in energy systems and how existing resources and infrastructure can be used more efficiently.

“I think exploring different areas is very valuable,” she says. “I find myself thinking ‘Maybe I could do this or I could do that. Maybe I don’t like this. Maybe I prefer doing another thing.’”

Outside of her studies, Calzadilla Sosa enjoys cooking and baking for family and friends, traveling, and going to concerts and dance performances. She also likes bringing people together, especially when she returns to her first home in Cuba and has the chance to reconnect with loved ones.

As graduation approaches, Calzadilla Sosa is excited to leave student life behind and see where her degree takes her. She has not settled on one career path, but she is comfortable with that uncertainty. After studying at multiple institutions and exploring different corners of chemical engineering, she knows there is still plenty left to discover.

“I spent so many years as an undergrad, so I’m really excited to go to industry and take that next step and see the results of my education,” she says.

As a child, you likely saw a few Disney movies depicting inanimate objects, such as clocks, cups, and toys, as interactive companions to humans — an act of pure magic, seemingly. But scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now doing something similar: transforming stationary items into self-aware tools that perceive and respond to human motion to complete a task.

Engineers have 3D-printed these dynamic items with built-in sensing, using conductive materials for sensors and traces (sort of like wires) inside. The issue: both components were typically fabricated using the same material, so they’d emit similar signals. It’s sort of like hearing two radio stations at the same time, a mixup that’s hard to interpret. This confuses, say, a glove that relays instructions to a robotic hand about how to handle a specific object. The device couldn’t filter out the noise or verify the angle of a user’s motions, leading a humanoid student to make errors.

Researchers at CSAIL and Tianjin University (TJU) in China may have found a way to 3D print more precise interactive items. With their “X-Hinges” software, users can customize a design, and the tool will automatically embed two different materials: a filament for the sensors designed to send the strongest signal possible, and another for the wire-like elements that don’t interfere. Interactions won’t get lost in translation, meaning users can fabricate objects that respond in real-time, such as small robots, household decor, object-detection systems, and toys.

With X-Hinges, users can put together an item by selecting and connecting different shapes, then choosing how certain parts move. The item won’t be limited to moving in just one way like previous approaches; instead, users can select up to three “axes:” compressing, up and down, or to the sides. Building a robotic hand, for example, you’d likely want its fingertips to move vertically and laterally. The new tool would then embed sensors where the object bends (in this case, its joints) to capture motion data from both angles. That way, the device can understand and respond to your interactions more dynamically once it’s 3D-printed.

“It’s kind of like adding a conscious element to everyday objects,” says Jiaji Li, MIT electrical engineering and computer science (EECS) postdoc and CSAIL researcher, who is a senior author on a paper introducing the work. “What you get is objects that better understand how they’re being used and have more ways to respond. In the same way an AI agent is programmed to make certain decisions based on our instructions, these creations have built-in sensing to adaptively react to human touch.”

Jiaji Li and lead author Xiang Chang, a TJU PhD student and visiting researcher at CSAIL, used X-Hinges to create many clever devices. For example, they made a glove that can teach a robot how to grasp blocks. It adjusts to the size of a user’s hands, then records how the joints in their fingers bend via sensors before rapidly relaying that information to a humanoid hand to mimic it. The glove could be useful in factories or homes, where a robot often needs to learn new interactions quickly.

The researchers also produced a small, origami-style lamp using X-Hinges. It senses when a human pinches it closed and adjusts its brightness accordingly. When you turn on this adaptive, portable light source (sort of like a reading light), it looks like a piece of folded-up paper that sprouts into a lamp.

X-Hinges can even assemble devices that identify which objects have been placed on it. You could put a banana on top, for instance, and it’ll recognize the fruit almost immediately based on the tactile data it’s recorded using its sensors. This advanced physical awareness could be integrated into detection systems in places such as airports and grocery stores. 

Behind each of the scientists’ creations is an easy-to-use interface that helps you design interactive objects from scratch. Users can choose how each part of their design looks and moves, just as the researchers did when making a video game controller that resembles a cartoon shark.

X-Hinges gives you four shapes to choose from: a custom option, cylinder, rectangle, and thin outline. To recreate the unique look of a shark’s tail, the researchers designed their own shape. They then chose how the toy bent, opting for its tail to move up and down, sort of like a joystick. Finally, the program embedded the sensors, and the scientists 3D-printed their device.

The researchers say that X-Hinges’ diverse motions are a novel feature compared to past attempts to 3D-print responsive everyday objects. “Most methods only allow for one axis of motion, often due to signal interference. X-Hinges enables your 3D-printed item to move from three angles,” says Chang. “Ultimately, you get a design with the intended movement you want. It also records motion data in each of those areas at the same time, making the device responsive to different kinds of interactions.”

The tool could help realize the untapped potential of the seemingly mundane. Objects we use every day for a specific purpose, like a water bottle for drinking or a lamp for lighting, could become interactive gadgets. Much like how a chatbot uses a sort of digital intelligence to answer your prompts, an object could leverage a kind of physical intelligence to execute a physical task when users interact with it.

For now, though, X-Hinges faces a calibration bottleneck. Each time an item is 3D-printed, its layout of electrical elements varies slightly, so two devices that appear identical from the outside may not make the same sensor readings. This is crucial if you’re building a deformable fitness glove, for instance, for two separate users. To fix this, Chang and Li built a computer vision system that can recalibrate outputs to align, ensuring data is accurate across two of the same items, although they hope to develop a built-in signal recalibration mechanism in the future.

That ambition traces back to the throughline in Jiaji Li’s own research: letting actuation and sensing “grow” directly inside a 3D-printed object, instead of adding them on afterward. He previously built printed tendon-driven mechanisms that gave objects the ability to move; X-Hinges is how he’s now building on the ability to sense. The next step, he says, is combining the two in a single print — it’s actuation and sensing born together in the same fabrication process, opening the door to new physical platforms for embodied intelligence and AI agents.

Chang and Li wrote the paper with MIT associate professor of EECS and CSAIL principal investigator Stefanie Mueller and recent TJU graduate Haiyang Yan. Their work was supported, in part, by a postdoctoral research fellowship from Zhejiang University and the MIT-GIST Program.

The researchers will present their work at the ACM Symposium on User Interface Software and Technology in early November.

Entrepreneurship and MIT have become a classic pairing, with a storyline that seems to write itself: A researcher develops a brilliant innovation in the lab, spins out a company, and brings a product to market that saves lives or improves society. It happens, sure — but long-term startup success is far from guaranteed.

That’s the challenge that prompted the launch of the MIT Kavanaugh Translational Fellows Program a decade ago, giving scholars who want to turn academic research into solutions to pressing challenges the time, tools, and business training to improve their chances of success.

“MIT has this world-class research facility and faculty and everything, but it also has world-class entrepreneurial programs,” says Nick Diaco, an MIT postdoc and 2025 Kavanaugh Fellow, in a new video about the program. “You really need both if you actually want to take an idea from the lab and put it into the real world and put it into situations where it’s actually affecting people’s lives.”

The program’s focus reflects a fundamental challenge for academic innovators: developing a promising technology is only the beginning. Turning it into a viable business requires making difficult decisions about customers, markets, financing, and other factors that may fall outside a typical researcher’s expertise.

“Even in a place like MIT, the majority of those people who choose to start businesses or bring that product to another business, the majority are going to fail,” said philanthropist Bart Kavanaugh at a May event announcing the 2026 fellows. Kavanaugh is one of the namesakes of the Saks-Kavanaugh Foundation, which supports the fellowship. He and his wife, Betty Saks, run the organization.

The foundation, he explained, analyzed what distinguishes successful startups. The selection process for the fellowship, he told the three new fellows — John Zhang, Maximiliano Jara Fornerod, and Xinyuan Zhang — is intended to identify researchers who have the potential to succeed.

The three are developing technologies ranging from a faster way to manufacture custom optical lenses to at-home strep throat tests and infrared detectors that can operate without energy-intensive cryogenic cooling.

They join a growing legacy of Kavanaugh Fellows whose research has moved toward commercialization, including Sublime Systems, a manufacturer of low-carbon cement; SiTration, which develops technology for extracting materials; and Stratagen Bio, which develops tools for quantitative biomarker assessment.

The yearlong program, managed by MIT’s Department of Materials Science and Engineering, gives MIT scholars time to focus on the business side of their ideas and develop the planning and decision-making skills needed to move promising research beyond the lab.

“If while you’re doing your research, you’re able to set aside some time to investigate the commercial potential before you leave the university, you get a really good picture on, 'is this a good idea for commercialization?'” says Diana Mojahed in the video. Mojahed was a postdoc at MIT when she became a 2023 Kavanaugh Fellow and is now the CEO of Lightfinder, which makes handheld spectrometers for health care, manufacturing, and telecommunications.

“It’s so much more than just achieving good specs with whatever you’re trying to achieve. There has to be a market for it. The unit economics need to work out. There’s a lot that goes into building a company.”

Learn more about the Kavanaugh Translational Fellows Program.

Building a nuclear power plant is one of the world’s most complex construction projects. It requires thousands of trucks to ship parts, often to remote regions, where huge teams of skilled workers like electricians and welders come together to assemble everything over many years.

Financing such projects is difficult, in part because no one wants to risk loaning money to a project that might never generate power and revenue, whether that’s due to technical failures, the inability to recruit enough talent, or regulatory hurdles.

Stated this way, it’s no surprise the average nuclear plant costs twice as much as originally expected and faces delays of many years. Those cost overruns and delays have ground the nuclear industry to a near halt: When Georgia finally turned on its Vogtle Unit 3 reactor in 2023 (seven years late), it was the first new reactor constructed in the U.S. in over 30 years.

Blue Energy wants to make deploying nuclear power plants more like wind, solar, and gas projects. The company prefabricates huge blocks of its nuclear plants at shipyards, where workers and equipment already produce huge steel structures for the oil and gas industry every day, then ships the blocks on barges to the site of the plant for final assembly.

“The nuclear problem is a construction problem,” says Blue Energy founder and CEO Jake Jurewicz ’14, SM ’15, who grew up in the construction industry and studied the differences between nuclear and oil and gas projects at MIT. “On paper, nuclear technology is almost perfect: It operates above 90 percent capacity, it’s zero carbon, dispatchable, extremely high reliability, and has predictable cash flow. We don’t have enough nuclear power because we’re really bad at building it. But there’s already a huge manufacturing supply base for offshore oil and gas and offshore wind. If we can point that toward building nuclear plants, and finance it the same way, we can reinvigorate the industry.”

Blue Energy’s prefabricated blocks weigh around 1,500 tons and are designed to be easily assembled at their destination to complete a nuclear power unit over the course of a single year. The company is further reducing barriers to financing and speeding up construction timelines by designing its early plants to run on gas initially before switching to nuclear reactors, which it hopes will generate revenue within three years from the start of construction.

The company has already gained approval from the Nuclear Regulatory Commission for its gas-to-nuclear approach and has also secured an agreement with GE Vernova Hitachi Nuclear Energy for its first project, a 2.5 gigawatt hybrid nuclear power plant in Victoria, Texas, that is scheduled to begin producing power in 2030. This September, Blue Energy submitted the first part of its application to the NRC to begin construction on its Texas project, making it just one of five companies to do so in the current nuclear development era.

“Our first site is a great power generation project for that community because it's going to generate a lot of excess power,” Jurewicz says. “It’s going to show a new model for the world: This is a way the U.S. and its allies can deliver a turnkey nuclear power plant and turnkey energy sovereignty.”

A new blueprint for nuclear

Jurewicz grew up in Chicago, where he worked as a construction draftsman through high school. When he arrived at MIT, he double majored in nuclear engineering and physics, then stayed at MIT for a masters in the Department of Nuclear Science and Engineering. He also minored in energy studies through the MIT Energy Initiative.

Jurewicz’s master’s thesis explored ways nuclear power plant construction could apply lessons from the offshore oil and gas industry.

“If you’re trying to solve the construction problem, find parallel industries where people have solved it before,” Jurewicz says. “That’s why I looked at offshore oil and gas as well as nuclear shipyards in the U.S. and South Korea. We build oil and gas plants all the time, so what looks different about the way we build and execute an oil and gas plant relative to how we build a nuclear plant? They’re both mostly steel welding.”

Shipyards have several advantages over other sites for building nuclear power plants. For one, they already have thousands of skilled workers and loads of specialized equipment. They can also manufacture things in controlled environments, enabling increased automation and reducing uncertainty.

Following graduation, Jurewicz worked in corporate strategy at the utility company Exelon Energy, where he sponsored research at MIT. He originally considered starting Blue Energy as a graduate student with an approach that included creating a new passive safety system and going through a new regulatory insurance framework.

When he founded Blue Energy in 2023, he wanted to minimize risks with a more conventional reactor design. That includes prefabricating functional chunks of the reactor — what the company calls “Blue Blocks” — at a shipyard using standard manufacturing approaches that meet nuclear licensing and quality assurance requirements.

“The 1,500-ton Blue Block prefabricated modules are fully functional mechanically and electrically, they have plumbing — everything is delivered ready to run directly to the site,” Jurewicz says. “Then we have this gas-to-nuclear technology that allows us to get things going earlier with gas by building the whole nuclear steam turbine system right away and energizing it with steam from gas combustion turbines, which means we can finance it as a gas plant, so the cost of capital goes down. It dramatically lowers the cost of the project, and it reduces risk. Then we switch it with the nuclear reactor.”

Blue Energy’s nuclear reactor will be a small modular light water reactor that has already been approved by the Nuclear Regulatory Commission and is made by GE Vernova Hitachi Nuclear Energy.

Blue Energy’s first power plant in Texas will provide 1 gigawatt of power using two GE Vernova gas turbines in 2030 and then add another 1.5 gigawatts of power from up to five small modular reactors beginning in 2032.

“It will be pretty easy to add more modular reactors to the site, so we can lower the cost to that community to provide things like water desalination, which is a big issue in south Texas,” Jurewicz says. “This power infrastructure is clean, reliable, and resilient through hurricanes or any other weather scenario that can happen in that community. It creates hundreds of high-paying permanent jobs and the foundation for a lot of local economic growth.”

Faster, cheaper nuclear

Historically, nuclear power plants have taken 10-plus years of construction. Blue Energy believes it can shorten that to about 36 months. The company is projecting power from later projects to reach about $5,000 per kilowatt. For context, the Vogtle nuclear plant delivers power at more than twice that cost.

Jurewicz believes Blue Energy’s lower prices could finally inject much-needed life into the U.S. nuclear industry.

“Despite all of the excitement around nuclear, you haven’t seen real power purchase agreements get signed because there’s a stalemate on who’s going to take the construction overrun risk,” Jurewicz says. “The government doesn’t want to take it. The construction companies don’t have the balance sheet to take it. The utilities can’t take it. Even the hyperscalers won’t take a two-or-three-times cost overrun risk. Blue Energy is introducing a fifth party to break the stalemate, which is the shipyards and fab yards, which are best positioned to take the risk because they can make things in a controlled fabrication environment, so they'll take the risk on construction in their own yards.”

At MIT’s McGovern Institute for Brain Research, Professor Fan Wang tackles innovative research every day. Her work centers on a fundamental question in neuroscience: How does the brain interact with the body to shape our sensations, emotions, and actions?

Wang and the students in her lab study the neural circuits underlying experiences such as touch and pain, as well as the sensory and motor systems that allow animals to carry out behaviors like eating, drinking, moving, and vocalizing.

This research is inherently exploratory. Understanding how the brain generates complex sensations and behaviors often requires following unexpected findings and pursuing questions whose answers are not immediately clear.

Wang brings this same openness to her mentorship style, giving those within her lab the freedom to explore while providing the scientific guidance needed to navigate uncertainty.

“Innovative research is often inherently high-risk and requires continuous exploration, and adjustment of direction,” Wang says. 

She does her best to share the excitement of promising results alongside her students while also working to alleviate their stress when everything doesn’t go to plan. Ultimately, she aims to create a research process that is “both intellectually stimulating and genuinely enjoyable” for her advisees.

For all these efforts, Wang was honored as “Committed to Caring” through a student-driven nomination and selection process.

Creating space for discovery

Research rarely follows a perfectly predictable path. New results can require revisiting hypotheses, changing direction, or returning to questions that had already been answered. Wang sees this uncertainty as a fundamental part of the research process.

She meets with members of her lab regularly to discuss their work and investigate problems together. These conversations serve to provide both feedback and structure, while also allowing them to work together through the frustrations that can accompany difficult research.

One nominator describes Wang’s “rigorous yet thoughtful scientific training” as tailored to each student’s personality and interests. For this student, weekly or biweekly meetings provide opportunities to review progress and plans, receive detailed guidance, and get critical feedback that supports both academic and professional growth.

Wang strives to create a challenging research environment that is also steeped in encouragement. This is particularly important when students are pursuing questions without obvious answers. When these sorts of questions arise, Wang is quick to work through uncertainty as a team.

For Wang, the goal is not to eliminate the uncertainty that comes with research, but to help students become comfortable navigating it. When results point in an unexpected direction, researchers can return to the questions, discuss what they are seeing, and determine where the evidence should lead them next.

Tailoring support to the student

Wang’s mentorship extends beyond experiments and research questions. She recognizes that each of her advisees is different, with unique interests, relationships, and experiences, and she tries to understand the type of support they need in order to flourish.

Her influence extends beyond the students she directly advises. As a member of the graduate affairs committee for the department, Wang meets with first-year PhDs to offer career advice and help them navigate the challenges of graduate school. Her nominators describe her as “compassionate, approachable, and deeply supportive.”

Wang also recognizes that circumstances outside the laboratory can affect a student’s ability to focus on research. “When something difficult happens in a student’s life, the most important thing I can do is be there to listen with genuine care and without judgment,” she says. “I do my best to support them as a whole person, not just as a researcher, and to be flexible when they need it.”

That flexibility can mean slowing things down, helping a student take a challenge one step at a time, or simply giving them space to talk. At the same time, Wang continues to emphasize the real goals at the heart of graduate education: asking difficult questions and responding thoughtfully to unexpected results.

One nominator describes Wang as bringing “warmth to the lab” — sharing food, engaging in conversations, and showing genuine concern for everyone’s mental well-being. Wang’s gestures create an environment where they feel supported both as researchers and as people.

Fostering trust

Wang describes her position as something of a “mother hen” philosophy. She feels a deep sense of responsibility for every student who joins her lab, and genuinely wants each of them to succeed.

For Wang, mutual trust is what allows mentorship to become an authentic connection. Her advisees can pursue uncertain ideas and navigate difficult moments knowing that their relationship with their mentor does not depend on always getting the right answer. 

“When students know that I truly care about them as people, not just as producers of data, it builds trust,” Wang reflects. “They understand that they are not just workers hired to complete a research project, and that I do not value or judge them solely by their output.”