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.

During this year’s Independent Activities Period (IAP), students, researchers, and collaborators across seven time zones came together to tackle urgent technical challenges facing Ukraine as the full-scale war enters its fourth year. 

A four-week hackathon, Build for Ukraine 2.0, brought MIT students and Ukrainian collaborators into a shared innovation environment where power outages, air-raid alerts, and subzero temperatures were part of the daily reality of teamwork.

The event was co-led by the MIT-Ukraine Program, MIT Edgerton Center, and MIT Lincoln Laboratory Beaver Works, with support from Mission Innovation X, MathWorks, and MIT.nano.

Designed and taught as an IAP subject EC.S01/EC.S11 (Build for Ukraine 2026), the hackathon paired technically diverse participants with Ukrainian organizations seeking near-term solutions to problems arising directly from wartime conditions.

“It’s not every working group that has to reschedule team meetings because some members are in Ukraine and just had a blackout,” says Hosea Siu ’14, SM ’15, PhD ’18, one of the lead organizers. “This class is unusual — in the most meaningful ways.”

A collaborative class built for real-world urgency

Build for Ukraine centered on co-design and rapid prototyping with in-country partners. Organizers spent the fall gathering challenge statements from stakeholders in Ukraine, Taiwan, the United Kingdom, Spain, and across the United States. The goal: identify problems where a small, interdisciplinary team could make measurable progress in one month.

The participant pool reflected MIT’s open IAP structure. First-year undergraduates worked alongside senior engineers, international researchers, and Ukrainian colleagues participating remotely despite frequent blackouts. Many joined meetings from darkened apartments in Kyiv, Kharkiv, and Cherkasy — often relying on unstable heaters and backup battery packs. One participant excused himself from a design review due to an air-raid alert.

“These groups developed what I call ‘quantum entanglement,’” says Svetlana Boriskina, a principal research scientist at MIT and director of the Multifunctional Metamaterials Laboratory in the Department of Mechanical Engineering. “They were sharing data in real time across continents, while experiencing the war’s impacts directly and indirectly.”

Setting the foundation: briefings and technical overviews

The first week introduced participants to the geopolitical, technical, and humanitarian landscape that would frame their work. Topics included:

• War context and co-design practices. Boriskina and Elizabeth Wood, faculty director of the MIT-Ukraine Program and professor of history at MIT, outlined current conditions in Ukraine. Student mentor Natalie Dean ’26 (vice president of MIT’s Assistive Technology Club) led a session on co-design — emphasizing partnership with, not for, Ukrainian collaborators.
• Extreme-environment engineering. Boriskina introduced two possible technical tracks proposed by her collaborators at Kharkiv Institute of Physics and Technology: radiation-hardened materials and self-powered sensors for extreme environments, and acoustic analysis for monitoring supercritical water cooling systems in nuclear reactors. One team, later known as HotPot, adopted the latter challenge.
• AI, Open Source Intelligence, and disinformation. Phil Tinn ’16, a research scientist at SINTEF and an affiliate of the MIT-Ukraine Program, along with specialists from IN2, described how disinformation narratives travel across platforms, from Telegram to global social media. Cambridge University researcher Jon Roozenbeek discussed early threat-signal detection using pricing fluctuations in fake SMS verifications. Ukrainian partners presented on large language model bias propagation, bot detection, and media-anomaly analysis — groundwork for the eventual VibeTracking team.
• Explosive ordnance disposal. Experts from MineSight and the U.S. Army National Guard detailed the scale of landmine contamination in Ukraine — by some estimates affecting a third of the country. These sessions inspired Clearview Interface, which worked on improving visual feedback for de-mining tools.
• Drone detection. Engineers from Skyfall and MIT’s student community introduced acoustic, radiofrequency (RF), and fiber-optic-tether detection methods for drones — leading to two separate teams: Birdwatch (acoustic detection) and Hrobachki (RF detection).

Five teams, seven time zones, and one month of development

Nearly 90 people joined the project through Discord, and by the end of week one, five core teams had formed. Roles blurred: Undergraduates mentored professionals; Ukrainian engineers supplied real-time operational data; and faculty offered rapid problem-solving guidance. Each team completed a Preliminary Design Review, Critical Design Review, and final presentation to an audience of more than 80 people, online and in person.

Despite the compressed timeline, the teams delivered promising prototypes and analyses with potential real-world application.

Team highlights

Clearview Interface — Visualizing metal-detector data for safer de-mining

Two undergraduates from Olin College developed a method for converting complex metal-detector audio signals — often an overwhelming sequence of indistinguishable beeps — into intuitive visual information. Their approach could help de-miners identify object types more quickly and accurately, enhancing both safety and mapping. The team reverse-engineered commercial detector outputs and produced a preliminary interface they plan to refine this spring.

HotPot — Acoustic monitoring for nuclear-reactor cooling systems

This team of seven (five at MIT and two from the Kharkiv Institute of Physics and Technology) worked to detect transitions from water to supercritical states inside steam pipes — a critical safety parameter in nuclear facilities that have remained in operation during wartime. Combining physics simulations, hardware engineering, and acoustics, the group analyzed data from Ukrainian partners and proposed a model capable of identifying supercritical conditions via remote monitoring.

Birdwatch — Acoustic detection of fiber-optic-controlled drones

With drones frequently used along the front and often tethered to fiber-optic control lines that evade RF detection, the Birdwatch team built an audio-based detection system using a network of cameras and microphones. They trained their model on drone signatures recorded across MIT’s campus and integrated early detections into a decision-support tool to help operators interpret and act on the alerts.

Hrobachki — Radiofrequency localization for long-range drones

Two MIT students, along with collaborators at Kenyon College, Olin College, and a partner in Cherkasy, Ukraine, focused on RF detection for drones operating beyond front-line distances. They established nodes at MIT, Olin, and the town of Milton, Massachusetts, demonstrating the feasibility of distributed RF sensing for aerial threat identification.

VibeTracking — Following the movement of disinformation narratives

The smallest team — a master’s student in Lviv supported by several advisors — collaborated with IN2 to build a large-language-model pipeline that classifies and groups narratives across platforms such as Telegram and X. Their system demonstrated the likely propagation path of a specific narrative, illustrating how early-stage disinformation can be identified before it reaches mainstream channels.

Resilience, connection, and next steps

On the final day of presentations, specialists from Ukrainian universities, industry partners, and MIT-affiliated programs filled the room and populated the Zoom call. Their response was enthusiastic, not only because of what the teams produced in four weeks, but because of the collaborative networks formed under difficult conditions.

“The most important outcome is the community that emerged,” Boriskina says. “These teams built tools — but they also built relationships that will carry this work forward.”

Organizers expect several projects to continue this spring through research internships, Undergraduate Research Opportunity Program projects, and follow-on collaborations with Ukrainian institutions.

Students interested in joining ongoing Build for Ukraine projects can email the MIT-Ukraine Program. To support MIT-Ukraine initiatives, contact Svitlana Krasynska.

As one of the first students in MIT’s new Music Technology and Computation Graduate Program, Mariano Salcedo ’25 is researching the intersection between artificial intelligence and music visuals.

Specifically, his graduate research focuses on neural cellular automata (NCA), which merges classical cellular automata with machine learning techniques to grow images that can regenerate.

When paired with a stimulus like music, these images can “show” sounds in action.

“This approach enables anyone to create music-driven visuals while leveraging the expressive and sometimes unpredictable dynamics of self-organized systems,” Salcedo says. Through the web interface Salcedo has designed, users can adjust the relationship between the music’s energy and the NCA system to create unique visual performances using any music audio stream.

“I want the visuals to complement and elevate the listening experience,” he says.

Last year Salcedo, the Alex Rigopulos (1992) Fellow in Music Technology and Computation, earned a BS in artificial intelligence and decision making from MIT, where he explored signal processing in machine learning and how a classical understanding of signals can inform how we understand AI. Now he’s one of five master’s students in the Music Technology and Computation Graduate Program’s inaugural cohort.

The program, directed by professor of the practice in music technology Eran Egozy ’93, MNG ’95, is a collaboration between MIT Music and Theater Arts in the School of Humanities, Arts, and Social Sciences, and the School of Engineering. It invites practitioners to study, discover, and develop new computational approaches to music. It also includes a speaker series that exposes students and the broader MIT community to music industry professionals, artists, technologists, and other researchers.

Rigopulos ’92, SM ’94, is a video game designer, musician, and former CEO of Harmonix Music Systems, a company he co-founded with Egozy in 1995. Harmonix is now a part of Epic Games, where Rigopulos is the director of game development for music.

“MIT is where I was first able to pursue my passion for music technology decades ago, and that experience was the springboard for a long and fulfilling career,” says Rigopulos. “So, when MIT launched an advanced degree program in music technology, I was thrilled to fund a fellowship to help propel this exciting new program.”

Egozy is enthusiastic about Salcedo’s work and his commitment to further exploring its possibilities. “He is a beautiful example of a multidisciplinary researcher who thinks deeply about how to best use technology to enhance and expand human creativity,” he says.

Salcedo has been selected to deliver the student address at the 2026 Advanced Degree Ceremony for the School of Humanities, Arts, and Social Sciences. “It’s an honor and it’s daunting,” he says. “It feels like a huge responsibility,” though one he’s eager to embrace. His selection also pleases Egozy. “I am super excited that Maraino was chosen to deliver this year’s keynote,” he enthuses.

Changing gears

Growing up in Mexico and Texas, Mariano Salcedo couldn’t readily indulge his passion for creating music. “There are no bands in Mexican public schools,” he says. While some families could pay for instruments and lessons, others like Salcedo’s were less fortunate.

“I’ve always loved music,” he continues. “I was a listener.”

Salcedo began his MIT journey as a mechanical engineering student, applying to MIT through the Questbridge program. “I heard if you like engineering and science that attending MIT would be a great choice,” he recalls. “Nerds are welcomed and embraced.” While he dutifully worked toward completing his MechE curriculum, music and technology came calling after a chance encounter with an LLM.

“I was introduced to an LLM chatbot and was blown away,” he recalls. “This was something that was speaking to me. I was both awed and frightened.” After his encounter with the chatbot, Salcedo switched his major from mechanical engineering to artificial intelligence and decision making.

“I basically started over after being two thirds of the way through the MechE curriculum,” he says. He learned about the possibilities available with AI but also confronted some of the challenges bedeviling researchers and developers including its potential power, ensuring its responsible use, human bias, limited access for people from underrepresented groups, and a lack of diversity among developers. He decided he might be able to change that picture.

“I thought one more person in the field could make a difference,” he says.

While completing his undergraduate studies, Salcedo’s love of music resurfaced. “I began DJ’ing at MIT and was hooked,” he says. While he hadn’t learned to play a traditional instrument, he discovered he could create engaging soundscapes with technology. “I bought a digital audio work station to help me make music,” he continues.

Egozy and Salcedo met in 2024 while Salcedo completed an Undergraduate Research Opportunities Program rotation as a game developer in Egozy’s lab. “He was incredibly curious and has grown tremendously over a very short time period,” Egozy says. Egozy became an informal, though important, mentor to Salcedo. “He brings great energy and thoughtfulness to his work, and to supporting others in the [music technology and computation graduate] program,” Egozy notes.

Salcedo also took a class with Egozy, 21M.385/21M.585/6.4450 (Interactive Music Systems), which further fed his appetite for the creativity he craved while also allowing him to indulge his fascination with music’s possibilities. By taking advantage of courses in the HASS curriculum, he further developed his understanding of music theory and related technologies.

“I took a class with professor Leslie Tilley, 21M.240 (Critically Thinking in Music), which helped establish a valuable framework for understanding music making,” he says, “while a class like 6.3000 (Signal Processing) helped me connect intuition with science.”

Working across disciplines

While Salcedo is passionate about his music and his research, he’s also invested in building relationships with his fellow students. He’s a member of the fraternity Sigma Nu, where he says he “found a home and community.” He also took a MISTI trip to Chile in summer 2023, where he conducted music technology research. Salcedo praises the culture of camaraderie at MIT and is grateful for its influence on his work as a scholar. “MIT has taught me how to learn,” he says.

Professors encouraged him to present his research and findings. He presented his work — Artificial Dancing Intelligence: Neural Cellular Automata for Visual Performance of Music — at the Association for the Advancement of Artificial Intelligence conference in Singapore in January 2026.

Salcedo believes his research can potentially move beyond music visualization. “What if we could improve the ways we model self-organized systems?” he asks. “That is, systems like multicellular organisms, flocks of birds, or societies that interact locally but exhibit interesting behaviors.” Any system, Salcedo says, where the whole is more than the sum of its parts.

Developing the technology used to design his application can potentially help answer important ethical questions regarding AI’s continued expansion and growth. The path to his work’s development is both daunting and lonely, but those challenges feed his work ethic.

“It’s intimidating to pursue this path when the academy is currently focused on LLMs,” he says. “But it’s also important to explain and explore the base technology before digging into more nuanced work, which can help audiences understand it better.” Knowing that he has the support of his professors helps Salcedo maintain excitement for his ideas. “They only ask that we ground our interests in research,” he says.

His investigations are impacting his work as a musician. “My music has gotten more interesting because of the classes I’m taking,” he says. He’s also interested in understanding whose music the academy and the world hears, exploring biases toward Western music in the canon and exploring how to reduce biases related to which kinds of music are valued.

“The work we do as technologists is far less subjective than we’re led to believe,” he believes.

Salcedo is especially grateful for the support he’s received during his time at MIT. “Program faculty encourage a variety of pursuits,” he says, “and ask us to advance our individual aims rather than focusing on theirs.” During his time in the graduate program, he notes with enthusiasm how often he’s been challenged to pursue his ideas.

Ultimately, Salcedo wants people to experience the joy he feels working at the intersection of the humanities and the sciences. Music and technology impact nearly everyone. Inviting audiences into his laboratory as participants in the creative and research processes offers the same kind of satisfaction he gets from crafting a great beat or solving for a thorny technical challenge. Helping audiences understand his work’s value fuels his drive to succeed.

“I want users to feel movement and explore sounds and their impact more fully,” he says.

Proteins are far more than nutrients we track on a food label. Present in every cell of our bodies, they work like nature’s molecular machines. They walk, stretch, bend, and flex to do their jobs, pumping blood, fighting disease, building tissue, and many other jobs too small for the eye to see. Their power doesn’t come from shape alone, but from how they move. 

In recent years, artificial intelligence has allowed scientists to design entirely new protein structures not found in nature tailored for specific functions, such as binding to viruses, or mimicking the mechanical properties of silk for sustainable materials. But designing for structure alone is like building a car body without any control over how the engine performs. The subtle vibrations, shifts, and mechanical dynamics of a protein are just as critical to its functions as its form.

Now, MIT engineers have taken a major step toward closing the gap with the development of an AI model known as VibeGen. If vibe coding lets programmers describe what they want and then AI generates the software, VibeGen does the same for living molecules: specify the vibe — the pattern of motion you want — and the model writes the protein. 

The new model allows scientists to target how a protein flexes, vibrates, and shifts between shapes in response to its environment, opening a new frontier in the design of molecular mechanics. VibeGen builds on a series of advances from the Buehler lab in agentic AI for science — systems in which multiple AI models collaborate autonomously to solve problems too complex for any single model.

“The essence of life at fundamental molecular levels lies not just in structure, but in movement,” says Markus Buehler, the Jerry McAfee Professor of Engineering in the departments of Civil and Environmental Engineering and Mechanical Engineering. “Everything from protein folding to the deformation of materials under stress follows the fundamental laws of physics.”

Buehler and his former postdoc, Bo Ni, identified a critical need for what they call physics-aware AI: systems capable of reasoning about motion, not just snapshots of molecular structure. “AI must go beyond analyzing static forms to understanding how structure and motion are fundamentally intertwined,” Buehler adds.

The new approach, described in a paper March 24 in the journal Matter, uses generative AI to create proteins with tailor-made dynamics.

Training AI to think about motion 

The revolution in AI-driven protein science has been, overwhelmingly, a revolution in structure. Tools like AlphaFold solved the decades-old problem of predicting a protein’s three-dimensional shape. Existing generative models learned to design new shapes from scratch. But in focusing on the folded snapshot — the protein frozen in place — the field largely set aside the property that makes proteins work: their motion. “Structure prediction was such a grand challenge that it absorbed the field’s attention,” Buehler says. “But a protein’s shape is just one frame of a much longer film, and the design space extends through space and time, where structure sits on a much broader manifold.” Scientists could design a protein with a particular architecture. They couldn’t yet specify how that protein would move, flex, or vibrate once it was built.

VibeGen does something no protein design tool has done before. It inverts the traditional problem. Rather than asking, “What shape will this sequence produce?” it asks, “What sequence will make a protein move in exactly this way?”

To build VibeGen, Buehler and Ni turned to a class of AI diffusion models, the same underlying technology that powers AI image generators capable of creating realistic pictures from pure noise. In VibeGen’s case, the model starts with a random sequence of amino acids and refines it, step by step, until it converges on a sequence predicted to vibrate and flex in a targeted way.

The system works through two cooperating agents that design and challenge each other. A “designer” proposes candidate sequences aimed at a target motion profile. A “predictor” evaluates those candidates, asking whether they’ll actually move the way the designer intended. The two models iterate back and forth like an internal dialogue, until the design stabilizes into something that meets the goal. By specifying this vibrational fingerprint as the design input, VibeGen inverts the usual logic: dynamics becomes the blueprint, and structure follows.

“It’s a collaborative system,” Ni says. “The designer proposes, the predictor critiques, and the design improves through that tension.”

Most sequences VibeGen produces are entirely de novo, not borrowed from nature, not a variation on something evolution already made. To confirm the designs actually work, the team ran detailed physics-based molecular simulations, and the proteins behaved exactly as intended, flexing and vibrating in the patterns VibeGen had targeted.

One of the study’s most striking findings is that many different protein sequences and folds can satisfy the same vibrational target — a property the researchers call functional degeneracy. Where evolution converged on one solution, VibeGen reveals an entire family of alternatives: proteins with different structures and sequences that nonetheless move in the same way. “It suggests that nature explored only a fraction of what’s possible,” Buehler says. “For any given dynamic behavior, there may be a large, untapped space of viable designs."

A new frontier in molecular engineering

Controlling protein dynamics could have wide-ranging applications. In medicine, proteins that can change shape on cue hold enormous potential. Many therapeutic proteins work by binding to a target molecule — a virus, a cancer cell, a misfiring receptor. How well they bind often depends not just on their shape, but on how flexibly they can adapt to their target. A protein that is engineered with motion could grip more precisely, reduce unintended interactions, and ultimately become a safer, more effective drug.

In materials science, which is an area of Buehler’s research, mechanical properties at the molecular scale affect their performance. Biological materials like silk and collagen get their strength and resilience from the coordinated motion of their molecular building blocks. Designing proteins that are stiffer, flexible, or vibrate in a certain way could lead to new sustainable fibers, impact-resistant materials, or biodegradable alternatives to petroleum-based plastics.

Buehler envisions further possibilities: structural materials for buildings or vehicles incorporating protein-based components that heal themselves after mechanical stress, or that adjust in response to heavy load.

By enabling researchers to specify motion as a direct design parameter, VibeGen treats proteins less like static shapes and more like programmable mechanical devices. The advance bridges artificial intelligence, medicine, synthetic biology, and materials engineering — toward a future in which molecular machines can be designed with the same precision and intentionality as bridges, engines, or microchips.

“VibeGen can venture into uncharted territory, proposing protein designs beyond the repertoire of evolution, tailored purely to our specifications. It’s as if we’ve invented a new creative engine that designs molecular machines on demand,” Buehler adds.

The researchers plan to refine the model further and validate their designs in the lab. They also hope to integrate motion-aware design with other AI tools, building toward systems that can design proteins to be not just dynamic, but multifunctional; machines that sense their environment, respond to signals, and adapt in real-time.

The word “vibe” comes from vibration, and Buehler sees the connection as more than wordplay. “We've turned 'vibe' into a metaphor, a feeling, something subjective,” he says. “But for a protein, the vibe is the physics. It is the actual pattern of motion that determines what the molecule can do, the very machinery of life.”

The research was supported by the U.S. Department of Agriculture, the MIT-IBM Watson AI Lab, and MIT’s Generative AI Initiative. 

The National Association of Collegiate Directors of Athletics (NACDA) has announced that MIT Director of Athletics G. Anthony Grant, head of the MIT Department of Athletics, Physical Education, and Recreation, is among 28 winners of the 2025-26 NACDA Athletic Director of the Year (ADOY) Award.

The ADOY Award highlights the efforts of athletics directors at all levels for their commitment and positive contributions to student-athletes, campuses, and their surrounding communities. Grant is currently in his sixth year at MIT, leading one of the most comprehensive Division III athletics programs in the country. In his role, he directs a department featuring 33 intercollegiate teams, including four Division I rowing programs, while providing opportunities for over 800 student-athletes.

MIT achieved remarkable success under Grant's leadership during the 2024-25 academic year, winning four NCAA championships. Women's swimming and diving captured the first national title in program history, while the women's cross country and track and field program swept all three NCAA championships in 2024-25, a historic first for an NCAA Division III women's program and the first MIT women's titles in cross country, as well as women's indoor and outdoor track and field. 

The year also saw MIT win 13 individual national champions, with 158 student-athletes earning All-American honors, 166 named All-Region, 227 named All-Conference, and 24 named CSC Academic All-America. Multiple head and assistant coaches claimed national, regional, and conference recognition. Nine teams claimed conference titles, while MIT earned seven NCAA/national top 10 finishes, as men's indoor track and field (7th), men's swimming and diving (9th) and men's lightweight crew joined the four national title winners.

Despite having begun his tenure at MIT just weeks prior to the start of the Covid-19 pandemic, MIT has continued to excel and grow under Grant's leadership. The Engineers have won six NCAA team national championships, finishing in the top seven of the NACDA LEARFIELD Directors' Cup standings every year since MIT returned to play following the pandemic. Most recently, MIT finished sixth in the final LEARFIELD Directors' Cup standings for the 2024-25 academic year, marking the 10th time the Engineers finished in the top 10, while MIT captured the NEWMAC Women's Presidents Cup for the 10th straight season and 11th time overall in 2024-25.

Grant was instrumental in negotiating an exciting re-branding effort that included the transition of the team uniforms and other apparel to Nike, as he worked in conjunction with BSN Sports as the official apparel provider. He also increased fundraising efforts with a record-breaking year for annual gifts in 2022. To wit, Grant has overseen several key initiatives, including a record-breaking fundraising campaign and a $5 million renovation to the varsity athletics Sports Performance Center that reopened in 2024-25. Most recently, Grant announced a state-of-the-art facility upgrade and turf renovation of the Fran O'Brien Baseball Field and Briggs Softball Field, with work currently underway. 

In addition to the on- and off-field accomplishments of MIT's student-athletes and coaches, Grant has intentionally strengthened department culture by focusing on MIT's mission and shared values and behaviors, which were re-branded in 2020 under his leadership. Grant embodies an open-door leadership style, creating an environment where staff at all levels feel comfortable engaging with him. He values feedback and open communication, and fosters a supportive, respectful, and inclusive environment. He actively supports employee initiatives and has worked with student-athlete leaders to enhance the Student-Athlete Advisory Committee to improve real-time feedback collection and engagement at meetings. 

Grant came to MIT from Metropolitan State University of Denver, where he also served as the director of athletics. Prior to MSU Denver, Grant served as the interim director of athletics at Millersville University in Pennsylvania, where he also worked as associate director of athletics for seven years. In addition, Grant has served as the athletic academic coordinator at the University of Iowa. 

He earned his master's degree from Temple University in sport and recreation, along with a PhD in health and sport studies with a specialization in athletic administration from the University of Iowa. His leadership extends beyond MIT, as he is also involved with the National Association of Collegiate Directors of Athletics, the National Association of Division III Athletics Administrators (NADIIIAA), and the Minority Opportunities Athletic Association. Most recently, he was named to the NADIIIAA Board of Directors for 2025-26. 

The ADOY Award program is in its 28th year and has recognized a total of 633 deserving athletics directors to date. The award spans seven divisions (NCAA FBS, FCS, Division I-AAA, II, III, NAIA/Other Four-Year Institutions and Junior College/Community Colleges). Winners will be recognized in conjunction with the 61st Annual NACDA and Affiliates Convention at Mandalay Bay Resort in Las Vegas, Nevada, at the beginning of the Association-Wide Featured Session on Tuesday, June 9. Additional history surrounding the ADOY award, including a list of past winners, can be found here.

Most diabetes patients must carefully monitor their blood sugar levels and inject insulin multiple times per day, to help keep their blood sugar from getting too high.

As a possible alternative to those injections, MIT researchers are developing an implantable device that contains insulin-producing cells. The device encapsulates the cells, protecting them from immune rejection, and it also carries an on-board oxygen generator to keep the cells healthy.

This device, the researchers hope, could offer a way to achieve long-term control of type 1 diabetes. In a new study, they showed that these encapsulated pancreatic islet cells could survive in the body for at least 90 days. In mice that received the implants, the cells remained functional and produced enough insulin to control the animals’ blood sugar levels.

“Islet cell therapy can be a transformative treatment for patients. However, current methods also require immune suppression, which for some people can be really debilitating,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science. “Our goal is to find a way to give patients the benefit of cell therapy without the need for immune suppression.”

Anderson is the senior author of the study, which appears today in the journal Device. Former MIT research scientist Siddharth Krishnan, who is now an assistant professor of electrical engineering at Stanford University, and former MIT postdoc Matthew Bochenek are the lead authors of the paper. Robert Langer, the David H. Koch Institute Professor at MIT, is also a co-author.

Insulin on demand

Islet cell transplantation has already been used successfully to treat diabetes in patients. Those islet cells typically come from human cadavers, or more recently, can be generated from stem cells. In either case, patients must take immunosuppressive drugs to prevent their immune system from rejecting the transplanted cells.

Another way to prevent immune rejection is to encapsulate cells in a protective device. However, this raises new challenges, as the coating that surrounds the cells can prevent them from receiving enough oxygen.

In a 2023 study, Anderson and his colleagues reported an islet-encapsulation device that also carries an on-board oxygen generator. This generator consists of a proton-exchange membrane that can split water vapor (found abundantly in the body) into hydrogen and oxygen. The hydrogen diffuses harmlessly away, while oxygen goes into a storage chamber that feeds the islet cells through a thin, oxygen-permeable membrane.

Cells encapsulated within this device, they found, could produce insulin for up to a month after being implanted in mice.

“A month is a good timeframe in that it shows basic proof-of-concept. But from a translational standpoint, it’s important to show that you can go quite a bit longer than that,” Krishnan says.

In the new study, the researchers increased the lifespan of the devices by making them more waterproof and more resilient to cracking. They also improved the device electronics to deliver more power to the oxygen generator. The implant is powered wirelessly by an external antenna placed on the skin, which transfers energy to the device. By optimizing the circuitry, the researchers were able to increase the amount of power reaching the oxygen-generating system.

The additional power allowed the device to produce more oxygen, helping the encapsulated cells to survive and function more effectively. As a result, the cells were able to generate much more insulin over time.

Protein factories

In studies in rats and mice, the researchers showed that the new device could function for at least 90 days after being implanted under the skin. During this time, donor islet cells were able to produce enough insulin to keep the animals’ blood sugar levels within a healthy range.

The researchers saw similar results with islet cells derived from induced pluripotent stem cells, which could one day provide an indefinite supply that could be used for any patient who needs them. These islets didn’t fully reverse diabetes, but they did achieve some control of blood sugar levels.

“We’re hoping that in the future, if we can give the cells a little bit longer to fully mature, that they’ll secrete even more insulin to better regulate diabetes in the animals,” Bochenek says.

The researchers now plan to study whether they can get the devices to last for even longer in the body — up to two years, or longer.

“Long-term survival of the islets is an important goal,” Anderson says. “The cells, if they’re in the right environment, seem to be able to survive for a long time. We are excited by the duration we’ve already achieved, and we will be working to extend their function as long as possible.”

The researchers are also exploring the possibility of using this approach to deliver cells that could produce other useful proteins, such as antibodies, enzymes, or clotting factors.

“We think that these technologies could provide a long-term way to treat human disease by making drugs in the body instead of outside of the body,” Anderson says. “There are many protein therapies where patients must receive repeated, lengthy infusions. We think it may be possible to create a device that could continuously create protein therapeutics on demand and as needed by the patient.”

The research was funded, in part, by Breakthrough TID, the Leona M. and Harry B. Helmsley Charitable Trust, the National Institutes of Health, and a Koch Institute Support (core) Grant from the National Cancer Institute.

Drugs that block enzymes called tyrosine kinases are among the most effective targeted therapies for cancer. However, they typically work for only 40 to 80 percent of the patients who would be expected to respond to them.

In a new study, MIT researchers have figured out why those drugs don’t work in all cases: Many of these tumors have turned on a backup survival pathway that helps them keep growing when the targeted pathway is knocked out.

“This seems to be hardwired into the cells and seems to be providing activation of a critical survival pathway in cancer cells,” says Forest White, the Ned C. and Janet C. Rice Professor of Biological Engineering at MIT. “This pathway allows the cells to be resistant to a wide variety of therapies, including chemotherapies.”

Additionally, the researchers found that they could kill those drug-resistant cancer cells by treating with both a tyrosine kinase inhibitor and a drug that targets the backup pathway. Clinical trials are now underway to test one such combination in lung cancer patients.

White is the senior author of the study, which appears this week in the Proceedings of the National Academy of Sciences. Cameron Flower PhD ’24, who is now a postdoc at Dana-Farber Cancer Institute and Boston Children’s Hospital, is the paper’s lead author.

Tumor survival

Tyrosine kinases are involved in many signaling pathways that allow cells to receive input from the external environment and convert it into a response such as growing or dividing. There are about 90 types of these kinases in human cells, and many of them are overactive in cancer cells.

“These kinases are very important for regulating cell growth and mitosis, and pushing the cell from a nondividing state to a dividing state depends on the activity of a lot of different tyrosine kinases,” Flower says. “We see a lot of mutations and overexpression of these kinases in cancer cells.”

These cancer-associated kinases include EGFR and BCR-ABL. Many cancer drugs targeting these kinases, including imatinib (Gleevec), have been approved to treat leukemia and other cancers. However, these drugs are not effective for all of the patients whose tumors overexpress tyrosine kinases — a phenomenon that has puzzled cancer researchers.

That lower-than-expected success rate motivated the MIT team to look into these drugs and try to figure out why some tumors do not respond to them.

For this study, the researchers examined six different cancer cell lines, which originally came from lung cancer patients. They chose two cell lines with EGFR mutations, two with mutations in a tyrosine kinase called MET and two with mutations in a tyrosine kinase called ALK. Each pair included one line that responded well to the tyrosine kinase inhibitor targeting the overactive pathway and one line that did not.

Using a technique called phosphoproteomics, the researchers were able to analyze the signaling pathways that were active in each of the cells, before and after treatment. Phosphoproteomics is used to identify proteins that have had a phosphate group added to them by a kinase. This process, known as phosphorylation, can activate or deactivate the target protein.

The researchers’ analysis revealed that the drugs were working as intended in all of the cancer cells. Even in resistant cells, the drugs did knock out signaling by their target kinase. However, in the cells that were resistant, an alternative network was already turned on, which helped the cells survive in spite of the treatment.

“Even before the therapy begins, the cells are in a state that intrinsically is resistant to the drug,” Flower says.

This survival network consists of signaling pathways that are regulated by another type of kinases known as SRC family kinases. Activation of this network appears to help cancer cells proliferate and possibly to migrate to new locations in the body. In addition to lung cancer, researchers from White’s lab have also found SRC family kinases activated in melanoma cells, where they also play a role in drug resistance, and in glioblastoma, a type of brain cancer.

“As inhibitors for SRC kinases are also drugs, the work suggests that combining inhibitors of driver oncogenes with SRC inhibitors could increase the number of patients who would benefit. This strategy merits testing in new clinical trials,” says Benjamin Neel, a professor of medicine at NYU Grossman School of Medicine, who was not involved in the study.

These findings might also explain why some patients who initially respond to tyrosine kinase inhibitors end up having their tumors recur later; the cells may end up activating this same survival pathway, but not until sometime after the initial treatment.

Combating resistance

The researchers also found that treating the resistant cells with both a tyrosine kinase inhibitor and a drug that inhibits SRC family kinases led to much greater cell death rates. By coincidence, a clinical trial testing the combination of a tyrosine kinase inhibitor called osmertinib and an SRC inhibitor is now underway, in patients with lung cancer. The MIT team now hopes to work with the same drug company to run a similar trial in pancreatic cancer patients.

The researchers also showed that they could use phosphoproteomics to analyze patient biopsy samples to see which cells already have the SRC pathways turned on.

“We are really excited to watch these clinical trials and to see how well patients do on these combinations. And I really think there’s a future for using tyrosine phosphoproteomics to guide this clinical decision-making,” White says.

This therapy might also be useful for patients whose tumors are originally susceptible to tyrosine kinase inhibitors but then later become resistant by turning on SRC pathways.

“Among the sensitive cells, some of them are able to upregulate this survival pathway and survive, which might be the residual disease that’s still there after treatment,” White says. “One of the interesting avenues here is, could we improve therapy for almost everybody, regardless of whether their tumors have intrinsic or adaptive resistance?”

The research was funded by the National Institutes of Health and the MIT Center for Precision Cancer Medicine.

Particle accelerators reveal the heart of nuclear matter by smashing together atoms at close to the speed of light. The high-energy collisions produce a shower of subatomic fragments that scientists can then study to reconstruct the core building blocks of matter.

An MIT-led team has now used the world’s most powerful particle accelerator to discover new properties of matter, through particles’ “near-misses.” The approach has turned the particle accelerator into a new kind of microscope — and led to the discovery of new behavior in the forces that hold matter together.

In a study appearing this week in the journal Physical Review Letters, the team reports results from the Large Hadron Collider (LHC) — a massive underground, ring-shaped accelerator in Geneva, Switzerland. Rather than focus on the accelerator’s particle collisions, the MIT team searched for instances when particles barely glanced by each other.

When particles travel at close to the speed of light, they are surrounded by an electromagnetic halo that flattens when particles pass close but don’t collide. The pancaked energy fields produce extremely high-energy photons. Occasionally, a photon from one particle can ping off another particle, like an intense, quantum-sized pinprick of light.

The MIT team was able to pick out such near-miss pinpricks, or what scientists call “photonuclear interactions,” from the LHC’s particle-collision data. They found that when some photons pinged off a particle, they kicked out a type of subatomic particle, known as a D0 meson, that the scientists could measure for the first time.

D0 mesons are subatomic particles that contain a charm quark, a rare type of quark not normally found in ordinary nuclear matter. Quarks are the fundamental building blocks of all matter, and are bound by gluons, which are massless particles that are the invisible glue, or “strong force” that holds matter together. The rare charm quarks can only be created in high-energy interactions. As such, they provide an especially clean, unambiguous probe of quarks and gluons inside a nucleus.

Through their measurements of D0 mesons , the researchers could estimate how tightly gluons are packed, and, essentially, how strong the strong force is within a particle’s nucleus.

“Our result gives an indication that when nuclear matter is squeezed together, then gluons start behaving in a funny way,” says lead author Gian Michele Innocenti, an assistant professor of physics at MIT. “We need to know how these gluons behave in these extreme conditions because gluons keep the universe together. And at this point, photonuclear interactions are the best way we have to study gluon behavior.”

The study’s co-authors include members of the CMS Collaboration — a global consortium of physicists who operate and maintain the Compact Muon Solenoid (CMS) experiment, which is one of the largest detectors within the LHC that was used to collect the study’s data.

Bringing a “background” into focus

With each run, the Large Hadron Collider fires off needle-thin beams of particles in opposite directions around a 27-kilometer-long underground ring. When the beams cross paths, particles can collide. If the collisions happen to take place in a region of the ring where the CMS detector is set up, the detector can record the collisions, and scientists can then analyze the aftermath to reconstruct the fragments that make up the original particles.

Since the LHC began operations in 2008, the focus has been overwhelmingly on the detection and analysis of “head-on” collisions. Physicists have known that by accelerating particle beams, they would also produce photonuclear interactions — near-miss events where a particle might collide not with another particle, but with its cloud of photons. But such light-nucleus interactions were thought to be simply noise.

“These photonuclear events were considered a background that people wanted to cancel,” Innocenti says. “But now people want to use it as a signal because a collision between a photon and a nucleus can essentially be like a super-high-accuracy microscope for nuclear matter.”

When a photon pings off a particle, the abundance, direction, and energy of the produced D0 meson relates directly to the energy and density of the gluons in the nucleus. If scientists can detect and measure this photon interaction, it would be like using an extremely small and powerful flashlight to illuminate the nuclear structures. But until now, it was assumed that photonuclear interactions would be impossible to pick out amid the various physics processes that can occur in such collisions.

“People didn’t think it was possible to remove the huge mess of all these other collisions, to zoom in on single photons hitting single nuclei producing a D0 meson,” Innocenti says. “We had to devise a system to recognize those very rare photonuclear interactions while data was being taken of particle collisions.”

Illuminating charm

For their new study, Innocenti and his colleagues first simulated what a photonuclear interaction would look like amid a shower of other particle collisions. In particular, they simulated a scenario in which a photon pings off a nucleus and produces a D0 meson. Although these events are rare, D0 mesons are among the most abundant particles that contain a charm quark. The team reasoned that if they could detect signs of a charm quark in D0 mesons that are produced in a photonuclear interaction, it could give valuable information about the gluons that hold the nucleus together.

With their simulations, the researchers then developed an algorithm to detect photonuclear interactions. They implemented the algorithm at the CMS detector to search for signals in real-time during the LHC’s particle-colliding runs.

“We had to collect tens of billions of collisions in order to extract a few hundred of these rare instances where a photon hits a nucleus and produces one of these exotic D0 meson particles,” Innocenti explains.

From this enormous dataset, the team identified a clean sample of these rare events by exploiting CMS’s advanced detector capabilities to select near-miss events and reconstruct the properties of the D0 mesons.

Through this process, the team detected instances of D0 meson production and then worked back to calculate properties of the particles’ charm quarks and the gluons that would have held them together in the original nucleus. 

“We are constraining what happens to gluons when they are squeezed in ions that are very large that are traveling very fast,” Innocenti says. “So far, our data confirms what people expect in terms of high-density nuclear matter. In reality, this is the first time we’ve shown this kind of measurement is feasible. ”

The team is working to improve the measurement’s accuracy in order to provide a clearer picture of how quarks and gluons are arranged inside a nucleus.

“Gluons are a very strong force that keeps the universe together,” Innocenti says. “The description of the strong force is at the basis of everything we see in nature. Now we have a way to either fully confirm, or show deviations from, that description.”

This work was supported, in part, by the U.S. Department of Energy, including support from a DOE Early Career Research Program award, and it builds on the contributions of a large MIT team of graduate students, undergraduate researchers, scientists, and postdocs.

Inside a giant autonomous warehouse, hundreds of robots dart down aisles as they collect and distribute items to fulfill a steady stream of customer orders. In this busy environment, even small traffic jams or minor collisions can snowball into massive slowdowns.

To avoid such an avalanche of inefficiencies, researchers from MIT and the tech firm Symbotic developed a new method that automatically keeps a fleet of robots moving smoothly. Their method learns which robots should go first at each moment, based on how congestion is forming, and adapts to prioritize robots that are about to get stuck. In this way, the system can reroute robots in advance to avoid bottlenecks.

The hybrid system utilizes deep reinforcement learning, a powerful artificial intelligence method for solving complex problems, to figure out which robots should be prioritized. Then, a fast and reliable planning algorithm feeds instructions to the robots, enabling them to respond rapidly in constantly changing conditions.

In simulations inspired by actual e-commerce warehouse layouts, this new approach achieved about a 25 percent gain in throughput over other methods. Importantly, the system can quickly adapt to new environments with different quantities of robots or varied warehouse layouts.

“There are a lot of decision-making problems in manufacturing and logistics where companies rely on algorithms designed by human experts. But we have shown that, with the power of deep reinforcement learning, we can achieve super-human performance. This is a very promising approach, because in these giant warehouses even a 2 or 3 percent increase in throughput can have a huge impact,” says Han Zheng, a graduate student in the Laboratory for Information and Decision Systems (LIDS) at MIT and lead author of a paper on this new approach.

Zheng is joined on the paper by Yining Ma, a LIDS postdoc; Brandon Araki and Jingkai Chen of Symbotic; and senior author Cathy Wu, the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering (CEE) and the Institute for Data, Systems, and Society (IDSS) at MIT, and a member of LIDS. The research appears today in the Journal of Artificial Intelligence Research.

Rerouting robots

Coordinating hundreds of robots in an e-commerce warehouse simultaneously is no easy task.

The problem is especially complicated because the warehouse is a dynamic environment, and robots continually receive new tasks after reaching their goals. They need to be rapidly redirected as they leave and enter the warehouse floor.

Companies often leverage algorithms written by human experts to determine where and when robots should move to maximize the number of packages they can handle.

But if there is congestion or a collision, a firm may have no choice but to shut down the entire warehouse for hours to manually sort the problem out.

“In this setting, we don’t have an exact prediction of the future. We only know what the future might hold, in terms of the packages that come in or the distribution of future orders. The planning system needs to be adaptive to these changes as the warehouse operations go on,” Zheng says.

The MIT researchers achieved this adaptability using machine learning. They began by designing a neural network model to take observations of the warehouse environment and decide how to prioritize the robots. They train this model using deep reinforcement learning, a trial-and-error method in which the model learns to control robots in simulations that mimic actual warehouses. The model is rewarded for making decisions that increase overall throughput while avoiding conflicts.

Over time, the neural network learns to coordinate many robots efficiently.

“By interacting with simulations inspired by real warehouse layouts, our system receives feedback that we use to make its decision-making more intelligent. The trained neural network can then adapt to warehouses with different layouts,” Zheng explains.

It is designed to capture the long-term constraints and obstacles in each robot’s path, while also considering dynamic interactions between robots as they move through the warehouse.

By predicting current and future robot interactions, the model plans to avoid congestion before it happens.

After the neural network decides which robots should receive priority, the system employs a tried-and-true planning algorithm to tell each robot how to move from one point to another. This efficient algorithm helps the robots react quickly in the changing warehouse environment.

This combination of methods is key.

“This hybrid approach builds on my group’s work on how to achieve the best of both worlds between machine learning and classical optimization methods. Pure machine-learning methods still struggle to solve complex optimization problems, and yet it is extremely time- and labor-intensive for human experts to design effective methods. But together, using expert-designed methods the right way can tremendously simplify the machine learning task,” says Wu.

Overcoming complexity

Once the researchers trained the neural network, they tested the system in simulated warehouses that were different than those it had seen during training. Since industrial simulations were too inefficient for this complex problem, the researchers designed their own environments to mimic what happens in actual warehouses.

On average, their hybrid learning-based approach achieved 25 percent greater throughput than traditional algorithms as well as a random search method, in terms of number of packages delivered per robot. Their approach could also generate feasible robot path plans that overcame congestion caused by traditional methods.

“Especially when the density of robots in the warehouse goes up, the complexity scales exponentially, and these traditional methods quickly start to break down. In these environments, our method is much more efficient,” Zheng says.

While their system is still far away from real-world deployment, these demonstrations highlight the feasibility and benefits of using a machine learning-guided approach in warehouse automation.

In the future, the researchers want to include task assignments in the problem formulation, since determining which robot will complete each task impacts congestion. They also plan to scale up their system to larger warehouses with thousands of robots.

This research was funded by Symbotic.

Like many people who end up going into physics, Sophia Henneberg had a hard time, when she was young, choosing between that discipline and mathematics. Both subjects came easily to her, and she — unlike many of her peers — thought they were fun. Henneberg grew up in a small town in central Germany, and it was not until one week before applying to college that she decided on physics, reasoning that it would still give her the chance to do plenty of math, while also affording opportunities to connect with a broad range of applications. 

Midway through her undergraduate studies at Goethe University in Frankfurt, she started taking courses in plasma physics and almost instantly knew that she had found her niche. “Most of the visible material in the universe is in the form of hot, ionized gas called plasma, so studying that is really fundamental,” she says. “And there’s this amazing application, fusion, which has the potential to become an unlimited energy source.”

Early on, Henneberg resolved to try to make that potential a reality, and she’s been pursuing that goal at MIT since becoming the Norman Rasmussen Career Development Assistant Professor in the Department of Nuclear Science and Engineering in fall of 2025. Her research focus is on stellarators — a kind of fusion machine that has been overshadowed for many decades by another fusion device called the tokamak.  Both of these machines rely on magnetic confinement — using powerful magnetic fields to compress a plasma into a tiny volume causing some of the atoms within this dense cluster to fuse together, unleashing energy in the process. In the tokamak, the plasma assumes the shape of a donut. In a stellarator, the plasma is also contained within a rounded loop, only this one resembles a twisted donut.

As a PhD candidate at the University of York (in the United Kingdom), Henneberg studied the instabilities that can arise in tokamaks, where plasma temperatures often exceed 100 million degrees Celsius and currents induced within the plasma can attain speeds of roughly 100 kilometers per second. In such an ultra-extreme setting — more than six times hotter than the core of the sun — sudden surges of energy, leading to something akin to small-scale solar flares, can breach the magnetic cage enclosing the plasma, thereby disrupting the fusion process and possibly damaging the reactor itself. Henneberg started hearing about stellarators in her classes and, after a bit of research, she came to realize that “they could be much more stable if you design them in the right way.”

In 2016, she began a postdoctoral fellowship at the Max Planck Institute (MPI) for Plasma Physics in Greifswald, Germany, joining the Stellarator Theory Group. Greifswald may well have been the best place for her to carry out stellarator research, given that the world’s biggest and most advanced reactor of this type, Wendelstein 7-X (W7-X), was based there, and experiments were just starting in the year she arrived.

Her main assignment at MPI was to work on stellarator optimization, figuring out the best way to design the reactor to meet the engineering and physics goals — a task not unlike that of tuning a car to achieve maximum fuel efficiency or, for a racecar, maximum speed. Henneberg’s interest in optimization continues to this day, remaining central to her research agenda at MIT.

“If you want to design a stellarator, there are two principal components you can look at,” she says. The first relates to the shape of the boundary, or cage, into which the plasma will ultimately be confined. This shape is constrained by magnetic fields that are generated, in turn, by a series of superconducting coils that might range in number anywhere from around 4 to 50. In stellarators, the coils tend to be bent rather than circular. That gives rise to twists in the magnetic fields, but it also makes the coils more complicated and likely more expensive. Henneberg has come up with ways to simplify the optimization process — one of which involves designing the plasma boundary and the shape of the coils in the same step rather than looking at them separately. 

“We’ve now reached the point where stellarator performances can exceed those of tokamaks, because we’re able to optimize them very well, but you have to put the effort in,” she says. “You can’t get good performance out of just any twisty donut.”

In a 2024 paper, Henneberg and her former Greifswald colleague, Gabriel Plunk, introduced the notion of a stellarator-tokamak hybrid reactor. The goal, they wrote, is both “simple and compelling: to combine the strengths of the two concepts into a single device” that outperforms either of the existing modes.

One of Henneberg’s major preoccupations at present is exploring ways of converting a tokamak into a stellarator that basically entails adding just a few coils — of the bent variety — that can be turned on or off. “This can be an easy way for people in the tokamak community to think more about the possible benefits of the stellarator,” she says. While no one has yet built a hybrid, at least one university has secured funding to do so.

Interest in stellarators has been steadily mounting in recent years, a fact that delights Henneberg. When she started working in this area almost a decade ago, the field of stellarator optimization was tiny and there were very few people she could converse with. There’s much more research going on today, which means that more ideas are coming out, along with some exciting results. Commercial interest is growing as well, and Henneberg has been in contact with several stellarator startup companies, including Type One Energy and Thea Energy in the United States and Proxima Fusion and Gauss Fusion in Germany.

“It seems to me that most new startups these days are focusing on stellarators,” Henneberg says. “With so many companies now entering the field, it can seem like the technical issues involved in fusion are already solved, but there are still many interesting open questions. I’m working on improved designs that advance both the physics and the economic feasibility.”

That’s where her students come in. She believes that one part of her role as an MIT professor is to train the next generation of stellarator experts — people who will help, for instance, to design effective coils that are easy to make, as well as to improve reactor performance overall. 

During her first term, she co-taught the renowned Fusion Design (22.63) course alongside MIT Professor Dennis Whyte. This course has had a remarkable influence on the fusion community, leading to nine published papers with over 1,000 citations and inspiring the creation of several companies. In the fall 2025 version of this course, students were charged with comparing designs for stellarators with machines that relied on a different way of confining the plasma called magnetic mirrors.

After just a few months at MIT, Henneberg has been impressed with her students, calling them “highly motivated and a lot of fun to work with.” She’s confident that her research group will soon be making progress.

She is also happy to be affiliated with MIT’s Plasma Science and Fusion Center, which is internationally recognized as a leading university laboratory in this field. “It’s great to have so many experts [primarily in tokamaks] in one place that I can work with and learn from,” Henneberg says. “Because of my interest in hybrid reactors, my research will really benefit from all the expertise here on the tokamak side.”

Each spring, river herring populations migrate from Massachusetts coastal waters to begin their annual journey up rivers and streams to freshwater spawning habitat. River herring have faced severe population declines over the past several decades, and their migration is extensively monitored across the region, primarily through traditional visual counting and volunteer-based programs. 

Monitoring fish movement and understanding population dynamics are essential for informing conservation efforts and supporting fisheries management. With the annual herring run getting underway this month, researchers and resource managers once again take on the challenge of counting and estimating the migrating fish population as accurately as possible. 

A team of researchers from the Woodwell Climate Research Center, MIT Sea Grant, the MIT Computer Science and Artificial Intelligence Lab (CSAIL), MIT Lincoln Laboratory, and Intuit explored a new monitoring method using underwater video and computer vision to supplement citizen science efforts. The researchers — Zhongqi Chen and Linda Deegan from the Woodwell Climate Research Center, Robert Vincent and Kevin Bennett from MIT Sea Grant, Sara Beery and Timm Haucke from MIT CSAIL, Austin Powell from Intuit, and Lydia Zuehsow from MIT Lincoln Laboratory — published a paper describing this work in the journal Remote Sensing in Ecology and Conservation this February. 

The open-access paper, “From snapshots to continuous estimates: Augmenting citizen science with computer vision for fish monitoring,” outlines how recent advancements in computer vision and deep learning, from object detection and tracking to species classification, offer promising real-world solutions for automating fish counting with improved efficiency and data quality. 

Traditional monitoring methods are constrained by time, environmental conditions, and labor intensity. Volunteer visual counts are limited to brief daytime sampling windows, missing nighttime movement and short migration pulses, when hundreds of fish pass by within the span of a few minutes. While technologies like passive acoustic monitoring and imaging sonar have advanced continuous fish monitoring under certain conditions, the most promising and low-cost option — manual review of underwater video — is still labor-intensive and time-consuming. With the growing demand for automated video processing solutions, this study presents a scalable, cost-effective, and efficient deep learning-based system for reliable automated fish monitoring. 

The team built an end-to-end pipeline — from in-field underwater cameras to video labeling and model training — to achieve automated, computer vision-powered fish counting. Videos were collected from three rivers in Massachusetts: the Coonamessett River in Falmouth, the Ipswich River (Ipswich), and the Santuit River in Mashpee. 

To prepare the training dataset, the team selected video clips with variations in lighting, water clarity, fish species and density, time of day, and season to ensure that the computer vision model would work reliably across diverse real-world scenarios. They used an open-source web platform to manually label the videos frame-by-frame with bounding boxes to track fish movement. In total, they labeled 1,435 video clips and annotated 59,850 frames. 

The researchers compared and validated the computer vision counts with human video reviews, stream-side visual counts, and data from passive integrated transponder (PIT) tagging. They concluded that models trained on diverse multi-site and multi-year data performed best and produced season-long, high-resolution counts consistent with traditionally established estimates. Going one step further, the system provided insights into migration behavior, timing, and movement patterns linked to environmental factors. Using video from the 2024 Coonamesset River migration, the system counted 42,510 river herring and revealed that upstream migration peaked at dawn, while downstream migration was largely nocturnal, with fish utilizing darker, quieter periods to avoid predators.

With this real-world application, the researchers aim to advance computer vision in fisheries management and provide a framework and best practices for integrating the technology into conservation efforts for a wide range of aquatic species. “MIT Sea Grant has been funding work on this topic for some time now, and this excellent work by Zhongqi Chen and colleagues will advance fisheries monitoring capabilities and improve fish population assessments for fisheries managers and conservation groups,” Vincent says. “It will also provide education and training for students, the public, and citizen science groups in support of the ecologically and culturally important river herring populations along our coasts.”

Still, continued traditional monitoring is essential for maintaining consistency in long-term datasets until fisheries management agencies fully implement automated counting systems. Even then, computer vision and citizen science should be seen as complementary. Volunteers will be necessary for camera maintenance and for contributing directly to the computer vision workflow, from video annotation to model verification. The researchers envision that integrating citizen observations and computer vision-generated data will help create a more comprehensive and holistic approach to environmental monitoring.

This work was funded by MIT Sea Grant, with additional support provided by the Northeast Climate Adaptation Science Center, an MIT Abdul Latif Jameel Water and Food Systems seed grant, the AI and Biodiversity Change Global Center (supported by the National Science Foundation and the Natural Sciences and Engineering Research Council of Canada), and the MIT Undergraduate Research Opportunities Program.

Batteries that use solid metal as their charge-carrying electrolyte could potentially be a safer and far more energy-dense alternative to lithium-ion batteries. However, these solid-state batteries have been plagued by the formation of metallic cracks called dendrites that cause them to short circuit.

The problem has so far prevented such batteries from becoming a major player in energy storage. But now, research from MIT could finally help engineers find a way to get past this hurdle.

For decades, many researchers have treated dendrites as largely the result of mechanical stress — like cracks that form on the sidewalk when a tree root grows underneath. But MIT engineers have discovered the exact opposite: Faster dendrite growth was associated with lower stress levels in a commonly used battery electrolyte material. Using a new technique that allowed them to directly measure the stress around growing dendrites, the researchers found cracks formed at stress levels as low as 25 percent of what would be expected under mechanical stress alone.

The experiments, published in Nature today, instead revealed another culprit: chemical reactions caused by high electrical currents that weaken the electrolyte and make it more susceptible to dendrite growth. Researchers had previously proposed that such reactions cause dendrite growth, but the new study provides the first experimental data on the interplay between chemical and mechanical stress in dendrite formation.

“Direct measurement techniques allowed us to see how tough the material is as we cycle the cell,” says Cole Fincher, the paper’s first author and an MIT PhD student in materials science and engineering. “What we saw was that if you just test the ceramic electrolyte on the benchtop, it’s about as tough as your tooth. But during charging, it gets a lot weaker — closer to the brittleness of a lollipop.”

The findings reveal why developing stronger electrolytes alone hasn’t solved the decades-old dendrite problem. It also points to the importance of developing more chemically stable materials to finally fulfill the promise of high-density solid-state batteries.

“There’s a large community of researchers that are constantly trying to discover and design better solid electrolytes to enable the solid-state battery,” says senior author Yet-Ming Chiang, MIT’s Kyocera Professor of Materials Science and Engineering. “This study provides guidance in those efforts. We discovered a new mechanism by which these dendrites grow, allowing us to explore ways to design around it to make solid-state batteries successful.”

Joining Fincher and Chiang on the paper are MIT PhD student Colin Gilgenbach; Thermo Fisher Scientific scientists Christian Roach and Rachel Osmundsen; MIT.nano researcher Aubrey Penn; MIT Toyota Professor in Materials Processing W. Craig Carter; MIT Kyocera Professor of Materials Science and Engineering James LeBeau; University of Michigan Professor Michael Thouless; and Brown University Professor Brian W. Sheldon.

Measuring stress

Dendrites have presented a major roadblock to battery development since the 1970s. One reason lithium-ion batteries have become ubiquitous while other approaches have stalled is that their commonly used graphite anodes are less susceptible to dendrite formation. That’s a shame because solid-state batteries that use lithium metal as an anode and a solid electrolyte could theoretically store far more energy in the same sized package with less weight. They could thus enable longer-lasting phones and laptops, or electric cars with double the range of today’s options.

“There’s no more energy-dense form of lithium than lithium metal,” Chiang says. “But the dendrite problem has limited progress with solid-state batteries.”

Lithium metal is soft like taffy. Fincher, who has been studying the dendrite problem in the labs of Chiang and Carter, says one puzzle is how such a soft material can penetrate into the hard electrolyte materials being explored for use in solid-state batteries.

“The ceramics that have been used in these applications are stiff, like a coffee mug, so it’s been hoped that solid-state batteries would stop this relatively soft dendrite from growing,” Fincher explains.

Believing that mechanical stress causes dendrites, scientists have worked to develop stronger electrolytes that can withstand more mechanical stress. Some researchers have proposed that chemical reactions play a role in dendrite formation, but how those reactions worked with mechanical stress was not known.

For their Nature study, the researchers set out to directly observe mechanical and chemical changes in a commonly used solid-state electrolyte material as dendrites grew. Solid-state batteries are typically organized like a sandwich, which makes it hard to look inside the middle electrolyte layer. For their first experiment, the researchers developed a special solid-state battery cell in which the ceramic layers can be observed from the side, allowing the researchers to watch dendrite growth occurring in the electrolyte.

The researchers also used a measurement technique called birefringence microscopy to precisely measure the stress around the dendrite, which Fincher developed as part of his PhD thesis.

“It works the same way as polarized sunglasses when you look at something like a windshield,” Fincher explains of the technique. “When light comes through, residual stresses in the glass enable light of some orientations to pass faster than others, and that can give rise to observable rainbow patterns. These patterns can be used to measure stress.”

The technique gave the researchers a way to both visualize and quantify stress around actively growing dendrites for the first time, leading to the unexpected findings.

“Normally you would expect that the faster a dendrite grows, the more stress it creates,” Chiang says. “Instead, we observed exactly the opposite. The faster it grew, the lower the stress around it, meaning the solid electrolyte is breaking under a lower stress, and therefore it’s been embrittled.”

In fact, the dendrites grew at stress levels far weaker than expected. Fincher describes the weaker electrolyte as electrochemically corroded.

“Imagine you test a piece of glass one day, and the next day it’s only a quarter as strong,” Chiang says. “It was very surprising.”

Led by LeBeau, the researchers then cooled the electrolyte to extremely low temperatures and applied a powerful imaging technique called cryogenic scanning transmission electron microscopy that allowed them to study the area around the dendrite on nearly atomic scales. The imaging revealed that the passage of ionic current through the material had caused chemical reactions that made it more brittle.

“The electric current drives the flow of lithium ions through the solid electrolyte,” Chiang explains. “That causes a highly concentrated flow of lithium ions at the dendrite tip. We believe that leads to a chemical reduction of the material compound, which leads to its decomposition into new phases. You start with a crystalline phase of the electrolyte, then there’s a volume contraction after the deposition that is consistent with the embrittlement we see.”

Toward better batteries

The experiment was done on one of the most stable electrolytes used in solid-state batteries, making the researchers confident the findings will carry over to other electrolyte materials.

“This tells us we have to look for electrolyte materials that are even more stable, especially when in contact with lithium metal, which chemically speaking is very reducing,” Chiang says. “This will help direct the search for new materials.”

For instance, Chiang says now that they understand more about the chemical changes causing embrittlement, researchers could explore materials that actually get tougher as cracks grow.

The researchers say it will take more work to figure out what electrochemical reactions are taking place to make the electrolyte so much weaker. But they say their approach for directly observing stresses could also help improve materials for use in devices like fuel cells and electrolyzers.

The work was supported by the center for Mechano-Chemical Understanding of Solid Ionic Conductors, a Department of Energy Engineering Frontiers Research Center, the National Science Foundation, and Fincher’s Department of Defense Science and Engineering Graduate Fellowship, and was carried out using MIT.nano facilities.

QS World University Rankings has placed MIT in the No. 1 spot in 12 subject areas for 2026, the organization announced today.

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

MIT also placed second in seven subject areas: Architecture/Built Environment; History of Art; Biological Sciences; Economics and Econometrics; Marketing; Natural Sciences; and Statistics and Operational Research.

For 2026, universities were evaluated in 55 specific subjects and five broader subject areas.

Quacquarelli Symonds Limited subject rankings, published annually, are designed to help prospective students find the leading schools in their field of interest. Rankings are based on research quality and accomplishments, academic reputation, and graduate employment.

MIT has been ranked as the No. 1 university in the world by QS World University Rankings for 14 straight years.

The next time you’re scrolling your phone, take a moment to appreciate the feat: The seemingly mundane act is possible thanks to the coordination of 34 muscles, 27 joints, and over 100 tendons and ligaments in your hand. Indeed, our hands are the most nimble parts of our bodies. Mimicking their many nuanced gestures has been a longstanding challenge in robotics and virtual reality.

Now, MIT engineers have designed an ultrasound wristband that precisely tracks a wearer’s hand movements in real-time. The wristband produces ultrasound images of the wrist’s muscles, tendons, and ligaments as the hand moves, and is paired with an artificial intelligence algorithm that continuously translates the images into the corresponding positions of the five fingers and palm.

The researchers can train the wristband to learn a wearer’s hand motions, which the device can communicate in real-time to a robot or a virtual environment.

In demonstrations, the team has shown that a person wearing the wristband can wirelessly control a robotic hand. As the person gestures or points, the robot does the same. In a sort of wireless marionette interaction, the wearer can manipulate the robot to play a simple tune on the piano and shoot a small basketball into a desktop hoop. With the same wristband, a wearer can also manipulate objects on a computer screen, for instance pinching their fingers together to enlarge and minimize a virtual object.

The team is using the wristband to gather hand motion data from many more users with different hand sizes, finger shapes, and gestures. They envision building a large dataset of hand motions that can be plumbed, for instance, to train humanoid robots in dexterity tasks, such as performing certain surgical procedures. The ultrasound band could also be used to grasp, manipulate, and interact with objects in video games, design applications, or other virtual settings.

“We think this work has immediate impact in potentially replacing hand tracking techniques with wearable ultrasound bands in virtual and augmented reality,” says Xuanhe Zhao, the Uncas and Helen Whitaker Professor of Mechanical Engineering at MIT. “It could also provide huge amounts of training data for dexterous humanoid robots.”

Zhao, Gengxi Lu, and their colleagues present the wristband’s new design in a paper appearing today in Nature Electronics. Their MIT co-authors are former postdocs Xiaoyu Chen, Shucong Li, and Bolei Deng; graduate students SeongHyeon Kim and Dian Li; postdocs Shu Wang and Runze Li; and Anantha Chandrakasan, MIT provost and the Vannevar Bush Professor of Electrical Engineering and Computer Science. Other co-authors are graduate students Yushun Zheng and Junhang Zhang, Baoqiang Liu, Chen Gong, and Professor Qifa Zhou from the University of Southern California.

Seeing strings

There are currently a number of approaches to capturing and mimicking human hand dexterity in robots. Some approaches use cameras to record a person’s hand movements as they manipulate objects or perform tasks. Others involve having a person wear a glove with sensors, which records the person’s hand movements and transmits the data to a receiving robot. But erecting a complex camera system for different applications is impractical and prone to visual obstacles. And sensor-laden gloves could limit a person’s natural hand motions and sensations.

A third approach uses the electrical signals from muscles in the wrist or forearm that scientists then correlate with specific hand movements. Researchers have made significant advances in this approach, however these signals are easily affected by noise in the environment. They are also not sensitive enough to distinguish subtle changes in movements. For instance, they may discern whether a thumb and index finger are pinched together or pulled apart, but not much of the in-between path.

Zhao’s team wondered whether ultrasound imaging might capture more dexterous and continuous hand movements. His group has been developing various forms of ultrasound stickers — miniaturized versions of the transducers used in doctor’s offices that are paired with hydrogel material that can safely stick to skin.

In their new study, the team incorporated the ultrasound sticker design into a wearable wristband to continuously image the muscles and tendons in the wrist.

“The tendons and muscles in your wrist are like strings pulling on puppets, which are your fingers,” Lu says. “So the idea is: Each time you take a picture of the state of the strings, you’ll know the state of the hand.”

Mapping manipulation

The team designed a wristband with an ultrasound sticker that is the size of a smartwatch, and added onboard electronics that are about as small as a cellphone. They attached the wristband to a volunteer’s wrist and confirmed that the device produced clear and continuous images of the wrist as the volunteer moved their fingers in various gestures.

The challenge then was to relate the black and white ultrasound images of the wrist to specific positions of the hand. As it turns out, the fingers and thumb are capable of 22 degrees of freedom, or different ways of extending or angling. The researchers found that they could identify specific regions in their ultrasound images of the wrist that correlate to each of these 22 degrees of freedom. For instance, changes in one region relate to thumb extension, while changes in another region correlate with movements of the index finger.

To establish these connections, a volunteer wearing the wristband would move their hand in various positions while the researchers recorded the gestures with multiple cameras surrounding the volunteer. By matching changes in certain regions of the ultrasound images with hand positions recorded by the cameras, the team could label wrist image regions with the corresponding degree of freedom in the hand. But to do this translation continuously, and in real-time, would be an impossible task for humans.

So, the team turned to artificial intelligence. They used an AI algorithm that can be trained to recognize image patterns and correlate them with specific labels and, in this case, the hand’s various degrees of freedom. The researchers trained the algorithm with ultrasound images that they meticulously labeled, annotating the image regions associated with a specific degree of freedom. They tested the algorithm on a new set of ultrasound images and found it correctly predicted the corresponding hand gestures.

Once the researchers successfully paired the AI algorithm with the wristband, they tested the device on more volunteers. For the new study, eight volunteers with different hand and wrist sizes wore the wristband while they formed various hand gestures and grasps, including making the signs for all 26 letters in American Sign Language. They also held objects such as a tennis ball, a plastic bottle, a pair of scissors, and a pencil. In each case, the wristband precisely tracked and predicted the position of the hand.

To demonstrate potential applications, the team developed a simple computer program that they wirelessly paired with the wristband. As a wearer went through the motions of pinching and grasping, the gestures corresponded to zooming in and out on an object on the computer screen, and virtually moving and manipulating it in a smooth and continuous fashion.

The researchers also tested the wristband as a wireless controller of a simple commercial robotic hand. While wearing the wristband, a volunteer went through the motions of playing a keyboard. The robot in turn mimicked the motions in real-time to play a simple tune on a piano. The same robot was also able to mimic a person’s finger taps to play a desktop basketball game.

Zhao is planning to further miniaturize the wristband’s hardware, as well as train the AI software on many more gestures and movements from volunteers with wider ranging hand sizes and shapes. Ultimately, the team is building toward a wearable hand tracker that can be worn by anyone, to wirelessly manipulate humanoid robots or virtual objects with high dexterity.

“We believe this is the most advanced way to track dexterous hand motion, through wearable imaging of the wrist,” Zhao says. “We think these wearable ultrasound bands can provide intuitive and versatile controls for virtual reality and robotic hands.”

This research was supported, in part, by MIT, the U.S. National Institutes of Health, the U.S. National Science Foundation, the U.S. Department of Defense, and Singapore National Research Foundation through the Singapore-MIT Alliance for Research and Technology.

Alex Tang’s dream of becoming a physician started in grade school when he read Lisa Sanders’ “Diagnosis” column in The New York Times Magazine. Although he often encountered unfamiliar medical terms, Tang was captivated by the magic of medicine, as Sanders described how physicians turned puzzling sets of symptoms into concrete diagnoses and treatment plans for patients.

A decade later, Tang is one step closer to achieving his dream. The MIT senior has challenged himself academically, dual-majoring in chemistry and biology and minoring in biomedical engineering. “All of the courses have encouraged me to think about problems through different lenses,” he says.

Tang has also challenged himself as the editor-in-chief of MIT’s student newspaper, The Tech, and as a competitive triathlete. In the fall, he will begin medical school, where he hopes to develop clinical skills and continue honing his scientific abilities. Ultimately, he aspires to pursue a career as a physician-scientist, focusing on how cancers respond to and resist treatment. He wants to help convert those insights into novel therapies that can be tailored to individual cancer patients.

“I want to advance precision oncology, ensuring that each patient receives the most effective, personalized treatment possible,” he says.

Thriving in the lab

Originally from Massachusetts, Tang was eager to make the most of his MIT experience, especially because of its extensive research opportunities. “Both my parents worked in the Cambridge biotech space, and being able to contribute to innovative science here has been a priority,” he says.

Early on, Tang gravitated toward oncology after joining the Nir Hacohen Lab at the Broad Institute, an interest cemented after taking 7.45 (Cancer Biology), which was taught by professors Tyler Jacks and Michael Hemann. Fascinated by how new cancer therapies were changing patients’ lives, he joined a project with implications for patients with difficult prognoses: For the last three-and-half years, Tang has been studying the effects of combined immunotherapy and targeted molecular therapy on tumors in patients with metastatic colorectal cancer.

“I hope my work can provide clarity for patients and physicians, and empower them to be confident in their options for care,” Tang says.

Last year, Tang was awarded a prestigious Goldwater Scholarship, which supports undergraduates who go on to become leading scientists, engineers, and mathematicians in their respective fields.

In addition to gaining technical skills, Tang has found working in the Hacohen Lab to be enriching in other important ways.

“What’s been great about research is learning from experts in the field who become your role models,” he says, “They are at the frontiers of investigating the most challenging questions in the field, and iterating through the scientific process with them is such a joy.”

Looking forward to medical school, he hopes to complement his basic science research with work that is more clinically involved.

“I want to bridge the gap between fundamental discoveries and tangible improvements in patient care,” Tang says. He has already set out on this mission, recently leading the development of a prognostic assay in lung cancer.

Breaking news

After stopping by the booth for MIT’s student newspaper, The Tech, during Campus Preview Weekend, Tang knew he wanted to join and contribute to a publication that has long chronicled MIT’s history and culture. Starting as a news writer and later serving as editor-in-chief, he learned how to write under pressure, reported on major campus events, and balanced leadership with collaboration.

“It’s been such an honor and pleasure to document people across the diverse MIT community who are all contributing to the character of the Institute in different ways,” he says.

It’s an activity he’ll drop everything for.

“When we have things come up and we have to do a breaking news story or we have some editorial thing that needs to be managed, I’ll just stop working to sort out whatever’s happening,” he says. “I think that’s what passion really is about.”

His journey with The Tech has not always been easy. In the summer between his first and second year, he found himself solely responsible for producing the paper’s news content amidst a staff shortage while the paper was facing financial difficulties.

“Coming into sophomore fall, I focused on recruiting more staff and seeking out ways to get more funding,” Tang says. “The paper wouldn’t be here without the people, both students and faculty advisors alike, who bought into The Tech’s mission.”

Though he hopes to pursue a career in medicine, Tang has found journalism to be integral in shaping how he will connect and communicate with patients and colleagues.

“You are responsible for taking someone’s story, breaking it down, and retelling it in your own words in a way that you feel would resonate with the audience and serve the community,” he says.

An outlet through triathlon

Despite his busy schedule, Tang prioritizes staying active and maintaining fitness. A former competitive swimmer in high school and now a triathlete, he still finds himself drawn back to the water when everything around him feels fast-paced.

“Swimming, biking, and running are good ways to de-stress,” Tang says. “It’s therapeutic in the sense that you can just let go. The race is just that culmination of letting it go at a more elevated level.”

He credits MIT’s infrastructure for helping him stay committed to training. “My dorm is steps away from the pool and the track,” he says. “The convenience is superb.”

Tang has found success in competitions, most recently placing third in his age group at the 2025 Boston Triathlon. In fact, it is the feeling of accomplishment that pushes him every day.

“There are many days when you want to take it easy, but you have to remember the joy waiting for you at the end of the race when you’ve put in the work,” he says. “It motivates me to be conscious and aware of what I’m doing in practice.”

During the summer, Tang and his younger brother go out for long runs in the Boston suburbs. “It is great to have my brother push me every day,” Tang says. “There has been no one more supportive of me than my family.”

Active Surfaces, a startup based on solar-energy technologies rooted in MIT research, is well on its way to developing what co-founder Richard Swartwout SM ’18, PhD ’21 calls “solar 2.0.” The company’s technology is in response to a need Swartwout recognized while observing energy challenges in India during an MIT Energy Initiative (MITEI) fellowship.

Within the last two years, the company has raised more than $10 million in venture capital, corporate investment, and state grants, most recently announcing in October an investment from the Tokyo-based electric utility Electric Power Development Co. Active Surfaces also opened their current manufacturing development site — a 5,000-square-foot facility — in 2024 in Woburn, Massachusetts, that is now filled with industrial roll-to-roll printers and other equipment being cost-optimized before the equipment is scaled up for a first-of-its-kind commercial-scale manufacturing plant.

Based on more than 10 years of MIT research and resulting patents — three held by Swartwout — collaborators at Active Surfaces have developed a novel approach to solar. Instead of silicon, the “solar 1.0” technology that dominates today, their solar cells are made of perovskite, a class of materials that are cheap, abundant, lightweight, flexible, and highly efficient at absorbing and emitting light.

“We need to start thinking about more and more places to put solar,” Swartwout says, “and we need to dramatically cut the cost of manufacturing and installing it.” Active Surfaces is now designing the solar technology that can meet those goals.

In recent years, homeowners, electric utilities, and others have adopted silicon-based systems, and in 2024 installed solar capacity worldwide exceeded 2 terawatts. However, some experts believe that by 2050 the world will need 20 terawatts of installed solar capacity in order to meet rapidly increasing demand for electricity while also reducing carbon emissions.

A long-standing target

Silicon technology was fine for its original purpose — generating electricity for NASA’s early spacecraft — and later for utility setups in remote locations. No matter that the silicon solar cells are brittle and require heavy racks to support them. Swartwout first became aware of the limitations of silicon solar during a trip he took to India to observe energy challenges encountered by people in remote areas in 2016 as part of his fellowship from MITEI’s Tata Center for Technology and Design. In talking with residents, Swartwout heard repeatedly that people didn’t trust solar sources of electricity because the brittle panels “fail very prematurely in those sorts of locations.”

Motivated by that early experience, plus the need for rapid worldwide growth in solar generation, Swartwout and Shiv Bhakta MBA ’24, SM ’24 co-founded Active Surfaces in 2022. The pair provides an unusual blend of expertise: Bhakta, the CEO and former civil and environmental engineering and business student through the Leaders for Global Operations program, offers strong strategic market experience, while Swartwout, the CTO and a former student in electrical engineering and computer science, spent a decade at MIT working on solar R&D and printed electronics innovation.

Other research groups have worked with perovskites, but the most promising compositions and manufacturing techniques were toxic, and managing their toxicity made large-scale manufacturing impractical. The Active Surfaces process instead uses a novel perovskite ink consisting entirely of nontoxic components. Layers of electronic material are deposited onto a thin substrate, and an electrode is deposited onto the surface to make a module. The solar modules are then protected from the environment using an epoxy that dries within seconds under an ultraviolet lamp. The module, now as thin as 15 microns thick, can readily be attached to any surface.

The finished solar film generates as much electricity as an equivalent surface area of silicon cell, and the confirmed durability under realistic temperatures and humidity exceeds 10 years. The lightweight, mechanically robust solar film is easy to install — an advantage that brings the overall cost way down compared to the cost of silicon solar. For a conventional rooftop silicon system, as much as half of the total cost is often for installation. “That’s because those panels are not designed to be easily deployed through general construction,” says Swartwout. “A flexible solar panel is much more in line with how we do construction. To put it on your roof, you would just unroll it like you would unroll an asphalt shingle or a roofing membrane.”

In addition, the flexible films can be fabricated by a cost-effective mass-production method called roll-to-roll manufacturing, in which material is continuously unrolled from one spool and rewound onto another. The machines operate at high speed, and the capital investment required is low. As a result, says Swartwout, “there isn’t much benefit to having centralized manufacturing, so you can think about a distributed manufacturing model.” That solves another problem with the current silicon solar technology: China now manufactures almost all solar cells, and, notes Swartwout, “many countries don’t want to have their energy supply chains totally dependent on China. With our technology, you can have regionalized manufacturing locally … more like today’s auto market.”

Growing up but not cutting ties

While Active Surfaces’ films are not yet full-sized, they have been growing rapidly, Swartwout says. “Within three months, our product went from lab-scale to 6 inches by 6 inches, and then within another four months or so, it went from that size to 6 inches by 2 feet — the biggest size that our current machines can process.” But, he adds, the 6x6 sample is “representative of what a minimum viable manufacturing process would be.”

The company continues to maintain its close ties to MIT. Several MIT professors are among the startup’s advisors. And the company is located just 15 miles from MIT, so staff members are frequently at MIT.nano, especially to make use of inspection tools like scanning electron microscopes and occasionally to use fabrication facilities not available at their own lab. In addition, the startup sometimes sponsors work at MIT.nano, in particular when they need a next-generation extension on one of the MIT patents. Swartwout calls the startup–MIT relationship a “good synergy,” and comments that they set up Active Surfaces “with that in mind.”

Swartwout is optimistic about what’s ahead for Active Surfaces. “We think that we have a really huge market. So the upfront capital that our investors are committing is worth the end-stage growth of what [our technology] could actually do for the future energy landscape as a whole.”

“Guys, have the buzzers been tested?”

On Saturday, Feb. 21, volunteers for the 2026 MIT Science Bowl High School Regional hustled around the spacious auditorium, setting up chairs and buzzers and laying out sharpened pencils. The room slowly quieted as all high schoolers filed in, dressed in matching, dark green Science Bowl T-shirts.

By late afternoon, after rounds and rounds of fast-paced questioning, the auditorium pulsed with tension and anxiously bouncing knees as the final seconds of the competition ticked down.

“Patients with Tay–Sachs disease —” began the moderator, Gideon Tzafriri, president of the Science Bowl and a senior at MIT.

A buzzer cut him off.

“Interrupt,” Tzafriri announced.

The entire audience seemed to hold their breath. A student from Lexington High School Team 1 offered their answer: “lysosome.”

“Correct.”

Moments later, the Lexington, Massachusetts, team sealed the match. The room erupted into cheers, with students vaulting from their seats and rushing down to hug and congratulate their teammates. The final score of the 2026 MIT Science Bowl was 148 to 52, with Lexington High School Team 1 winning against Philips Exeter Team 1.

“I think I can speak for all of us when I say we feel ecstatic,” said Jerry Xu, one of the members of the winning team. “It’s been a long-term collaborative effort, we’ve been practicing for many years. We’ve worked together as a team for so long, it’s just such a great feeling to be here with my friends.”

Around Xu, the rest of his teammates proudly nodded.

The 2026 MIT High School Regional Science Bowl marked the Institute’s first time hosting a regional competition, expanding its long-running involvement with the national tournament. While MIT has hosted the national high school competition for eight years, this regional event created a new qualifying pathway for New England schools vying for a place at the National Science Bowl in Washington.

The competition involves round-robin style questions on complex biology, chemistry, and physics questions, and some topics lie well beyond the scope of regular high school classes. In a long day of tough science questions and rapidly beeping buzzers, the event had brought together 26 teams from 14 schools across Massachusetts, New Hampshire, and Rhode Island.

“The whole team put immense effort into learning about science, enjoying themselves, having fun, and trusting the process,” said Nicholas Gould, the Lexington High School team’s coach and their physics teacher. “It’s not about the win, it’s the process of getting there, the experiences they take with them and what they learn about themselves and each other.”

For many competitors, the draw wasn’t just the chance to win a medal, but to further their knowledge.

“I came here because I wanted to be on a science team just because I like science, and my experience has been pretty amazing,” said Vritti Mehra, a student at Portsmouth High School in New Hampshire.

Others spoke of the importance of representation.

“I’m proud to be a girl in this tournament because as you can see, there are not a lot of females here. But I’m very glad that I’m part of this community because of the friendliness, the competition, and this fostered a love for science for me,” said Katherine Wang, from Lexington High School Team 3, who has been competing since sixth grade. “My mom has a PhD, so she really inspires me to become the best.”

The regional marked a beginning to MIT, and an end for many graduating seniors, both competitors and volunteers.

“Most of us have been doing Science Bowl since middle school, so this feels like a culmination of everything we’ve done,” said William Jung, another member of the winning team.

For Tzafriri, the president of the bowl, the event carried a similar resonance, since he also competed in the event himself when he was in high school.

“It’s nice to finally finish off something that I started in high school,” said Tzafriri.

As the event came to an end, the winning team lined up at the front of the auditorium, with proud grins and the golden medals around their necks glistening under fluorescent lights. Cameras flashed in quick succession as the event’s organizers and volunteers watched proudly from either side.

“I get to help kids have fun with science and actively participate in science,” said Jiaxing Wang, one of the event’s organizers. “The Science Bowl is something I discovered in my junior year of high school: It was very late in the cycle, so I want to be able to help kids like me to compete and have the experience they deserve and desire.”

For Lexington’s seniors, this event sends them to Washington. For MIT, it signals something larger: a continuous investment into young scientists, encouraging a future full of possibility.

Artificial intelligence holds promise for helping doctors diagnose patients and personalize treatment options. However, an international group of scientists led by MIT cautions that AI systems, as currently designed, carry the risk of steering doctors in the wrong direction because they may overconfidently make incorrect decisions.

One way to prevent these mistakes is to program AI systems to be more “humble,” according to the researchers. Such systems would reveal when they are not confident in their diagnoses or recommendations and would encourage users to gather additional information when the diagnosis is uncertain.

“We’re now using AI as an oracle, but we can use AI as a coach. We could use AI as a true co-pilot. That would not only increase our ability to retrieve information but increase our agency to be able to connect the dots,” says Leo Anthony Celi, a senior research scientist at MIT’s Institute for Medical Engineering and Science, a physician at Beth Israel Deaconess Medical Center, and an associate professor at Harvard Medical School.

Celi and his colleagues have created a framework that they say can guide AI developers in designing systems that display curiosity and humility. This new approach could allow doctors and AI systems to work as partners, the researchers say, and help prevent AI from exerting too much influence over doctors’ decisions.

Celi is the senior author of the study, which appears today in BMJ Health and Care Informatics. The paper’s lead author is Sebastián Andrés Cajas Ordoñez, a researcher at MIT Critical Data, a global consortium led by the Laboratory for Computational Physiology within the MIT Institute for Medical Engineering and Science.

Instilling human values

Overconfident AI systems can lead to errors in medical settings, according to the MIT team. Previous studies have found that ICU physicians defer to AI systems that they perceive as reliable even when their own intuition goes against the AI suggestion. Physicians and patients alike are more likely to accept incorrect AI recommendations when they are perceived as authoritative.

In place of systems that offer overconfident but potentially incorrect advice, health care facilities should have access to AI systems that work more collaboratively with clinicians, the researchers say.

“We are trying to include humans in these human-AI systems, so that we are facilitating humans to collectively reflect and reimagine, instead of having isolated AI agents that do everything. We want humans to become more creative through the usage of AI,” Cajas Ordoñez says.

To create such a system, the consortium designed a framework that includes several computational modules that can be incorporated into existing AI systems. The first of these modules requires an AI model to evaluate its own certainty when making diagnostic predictions. Developed by consortium members Janan Arslan and Kurt Benke of the University of Melbourne, the Epistemic Virtue Score acts as a self-awareness check, ensuring the system’s confidence is appropriately tempered by the inherent uncertainty and complexity of each clinical scenario.

With that self-awareness in place, the model can tailor its response to the situation. If the system detects that its confidence exceeds what the available evidence supports, it can pause and flag the mismatch, requesting specific tests or history that would resolve the uncertainty, or recommending specialist consultation. The goal is an AI that not only provides answers but also signals when those answers should be treated with caution.

“It’s like having a co-pilot that would tell you that you need to seek a fresh pair of eyes to be able to understand this complex patient better,” Celi says.

Celi and his colleagues have previously developed large-scale databases that can be used to train AI systems, including the Medical Information Mart for Intensive Care (MIMIC) database from Beth Israel Deaconess Medical Center. His team is now working on implementing the new framework into AI systems based on MIMIC and introducing it to clinicians in the Beth Israel Lahey Health system.

This approach could also be implemented in AI systems that are used to analyze X-ray images or to determine the best treatment options for patients in the emergency room, among others, the researchers say.

Toward more inclusive AI

This study is part of a larger effort by Celi and his colleagues to create AI systems that are designed by and for the people who are ultimately going to be most impacted by these tools. Many AI models, such as MIMIC, are trained on publicly available data from the United States, which can lead to the introduction of biases toward a certain way of thinking about medical issues, and exclusion of others.

Bringing in more viewpoints is critical to overcoming these potential biases, says Celi, emphasizing that each member of the global consortium brings a distinct perspective to a broader, collective understanding.

Another problem with existing AI systems used for diagnostics is that they are usually trained on electronic health records, which weren’t originally intended for that purpose. This means that the data lack much of the context that would be useful in making diagnoses and treatment recommendations. Additionally, many patients never get included in those datasets because of lack of access, such as people who live in rural areas.

At data workshops hosted by MIT Critical Data, groups of data scientists, health care professionals, social scientists, patients, and others work together on designing new AI systems. Before beginning, everyone is prompted to think about whether the data they’re using captures all the drivers of whatever they aim to predict, ensuring they don’t inadvertently encode existing structural inequities into their models.

“We make them question the dataset. Are they confident about their training data and validation data? Do they think that there are patients that were excluded, unintentionally or intentionally, and how will that affect the model itself?” he says. “Of course, we cannot stop or even delay the development of AI, not just in health care, but in every sector. But, we must be more deliberate and thoughtful in how we do this.”

The research was funded by the Boston-Korea Innovative Research Project through the Korea Health Industry Development Institute.

Methane is a powerful greenhouse gas that is second only to carbon dioxide in driving up global temperatures. But it doesn’t linger in the atmosphere for long thanks to molecules called hydroxyl radicals, which are known as the “atmosphere’s detergent” for their ability to break down methane. As the planet warms, however, it’s unclear how the air-cleaning agents will respond.

MIT scientists are now shedding some light on this. The team has developed a new model to study different processes that control how levels of hydroxyl radical will shift with warming temperatures.

They find that the picture is complicated. As temperatures increase, so too will water vapor in the atmosphere, which will in turn boost the molecule’s concentrations. But rising temperatures will also increase “biogenic volatile organic compound emissions” — gases that are naturally released by some plants and trees. These natural emissions can reduce hydroxyl radical and dampen water vapor’s boosting effect.

Specifically, the team finds that if the planet’s average temperatures rise by 2 degrees Celsius, the accompanying rise in water vapor will increase hydroxyl radical levels by about 9 percent. But the corresponding increase in biogenic emissions would in turn bring down hydroxyl radical levels by 6 percent. The final accounting could mean a small boost, of about 3 percent, in the atmosphere’s ability to break down methane and other chemical compounds as the planet warms.

“Hydroxyl radicals are important in determining the lifetime of methane and other reactive greenhouse gases, as well as gases that affect public health, including ozone and certain other air pollutants,” says study author Qindan Zhu, who led the work as a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS).

“There’s a whole range of environmental reasons why we want to understand what’s going on with this molecule,” adds Arlene Fiore, the Peter H. Stone and Paola Malanotte Stone Professor in EAPS. “We want to make sure it’s around to chemically remove all these gases and pollutants.”

Fiore and Zhu’s new study appears today in the Journal of Advances in Modeling Earth Systems (JAMES). The study’s MIT co-authors include Jian Guan and Paolo Giani, along with Robert Pincus, Nicole Neumann, George Milly, and Clare Singer of Lamont-Doherty Earth Observatory and the Columbia Climate School, and Brian Medeiros at the National Center for Atmospheric Research.

A natural neutralizer

The hydroxyl radical, known chemically as OH, is made up of one oxygen atom and one hydrogen atom, along with an unpaired electron. This configuration makes the molecule extremely reactive. Like a chemical vacuum cleaner, OH easily pulls an electron or hydrogen atom away from other molecules, breaking them down into weaker, more water-soluble forms. In this way, OH reduces a vast range of chemicals, including some air pollutants, pathogens, and ozone. And changes in OH are a powerful lever on methane.

“For methane, the reaction with OH is considered the most important loss pathway,” Zhu says. “About 90 percent of the methane that’s removed from the atmosphere is due to the reaction with OH.”

Indeed, it’s thanks to reactions with hydroxyl radical that methane can only stick around in the atmosphere for about a decade — far shorter than carbon dioxide, which can linger for 1,000 years or longer. But even as OH breaks down methane already in the atmosphere, more methane continues to accumulate. Rising methane concentrations, in addition to human-derived emissions of carbon dioxide, are driving global warming, and it’s unclear how OH’s methane-clearing power will keep up.

“The questions we’re exploring here are: What are the main processes that control OH concentrations? And how will OH respond to climate change?” Fiore says.

An aquaplanet’s air

For their study, the researchers developed a new model to simulate levels of OH in the atmosphere under a current global climate scenario, compared to a future warmer climate. Their model, dubbed “AquaChem,” is an expansion of a simplified model that is part of a suite of tools developed by the Community Earth System Model (CESM) project. The model that the team chose to build off is one that represents the Earth as a simplified “aquaplanet,” with an entirely ocean-covered surface.

Aquaplanet models allow scientists to study detailed interactions in the atmosphere in response to changes in surface temperatures, without having to also spend computing time and energy on simulating complex dynamics between the land, water, and polar ice caps.

To the aquaplanet model, Zhu added an atmospheric chemistry component that simulates detailed chemical reactions in the atmosphere consistent with the applied surface temperatures. The chemical reactions that she modeled represent those that are known to affect OH concentrations.

OH is primarily produced when ozone interacts with sunlight in the presence of water vapor. For instance, scientists have found that OH levels can vary depending certain anthropogenic and natural emissions, all of which Zhu incorporated separately and together into the AquaChem model in order to isolate the impact of each process on OH.

The emissions in particular include carbon monoxide, methane, nitrogen oxides, and volatile organic compounds (VOCs), some of which are emitted through human practices, and others that are given off by natural processes. One type of naturally-derived VOCs are “biogenic” emissions — gases, such as isoprene, that some plants and trees emit through tiny pores called stomata during transpiration.

Into the AquaChem model, Zhu plugged in data that were available for each type of emissions from the year 2000 — a year that is generally considered to represent the current climate in a simplified form. She set the aquaplanet’s sea surface temperatures to the zonal annual mean of that year, and found that the model accurately reproduced the major sensitivities of OH chemistry to the underlying chemical processing as simulated in a more complex chemistry-climate model.

Then, Zhu ran the model under a second, globally warming scenario. She set the planet’s sea surface temperatures to warm by 2 degrees Celsius (a warming that is likely to occur unless global anthropogenic carbon emissions are mitigated). The team looked at how this warming would affect the various types of emissions and chemical processes, and how these changes would ultimately affect levels of OH in the atmosphere.

In the end, they found the two biggest drivers of OH levels were rising water vapor and biogenic emissions. They found that global warming would increase the amount of water vapor to the atmosphere, which in turn would boost production of OH by 9 percent. However, this same degree of warming would also increase biogenic emissions such as isoprene, which reacts with and breaks down OH, bringing down its levels by 6 percent.

The team recognizes that there are many other factors that affect the response of isoprene emissions to surface warming. Rising CO2, not considered in this study, may dampen this temperature-driven response. Of all the factors that can shift OH levels under global warming, the researchers caution that biogenic emissions are the most uncertain, even though they appear to have a large influence. Going forward, the scientists plan to update AquaChem to continue studying how biogenic emissions, as well as other processes and climate scenarios, could sway OH concentrations.

“We know that changes in atmospheric OH, even of a few percent, can actually matter for interpreting how methane might accumulate in the atmosphere,” Zhu says. “Understanding future trends of OH will allow us to determine future trends of methane.”

This work was supported, in part, by Spark Climate Solutions and the National Oceanic and Atmospheric Administration. 

The sense of support and community was palpable when Sojun Park, a postdoc at the MIT Center for International Studies (CIS), delivered a recent presentation on The Global Diffusion of AI Technologies and Its Political Drivers. The event, part of the CIS Global Research and Policy Seminar, filled the venue with audience members from across MIT. 

“My work is directly connected to what CIS faculty have previously done on international trade and security,” Park said afterwards. “If I hadn’t received a postdoctoral fellowship and come to MIT, I wouldn’t have been able to think through the security implications of my intellectual property research. I’ve been tremendously motivated by these scholars.”

Park’s time at CIS has been both grounding and transformative, offering him a scholarly home that has shaped his research and helped broaden his intellectual horizons.

Pursuing interdisciplinary research and connections 

Before pursuing a tenure-track position, Park set his sights on conducting research at MIT. When he came across a public posting about the CIS Postdoctoral Associate Program, he took a chance and applied.

“My own research is interdisciplinary, and I knew that I could really benefit from the interdisciplinary environment at MIT, and specifically at CIS, where faculty are coming not only from political science, but also affiliated with the Department of Economics and MIT Sloan [School of Management],” he says.

Park was thrilled to receive the paid fellowship, which offers an academic year at MIT and dedicated office space at CIS. At MIT, he is free to use his time toward his own research, and has found value in pursuing topics that are of interest to the CIS community — whether it’s AI or global governance. He’s published prolifically along the way, including two articles in the Review of International Organizations and the Review of International Political Economy.

He’s also continued to work on his forthcoming book, “From Privilege to Prosperity: Knowledge Diffusion and the Global Governance of Intellectual Property,” which examines how technologies can be transferred legitimately across borders. “By 'legitimately,' I am asking under what circumstances would firms volunteer to share their technologies? I’m interested in institutions and institutional environments that allow large businesses to share their technologies with smaller businesses based in the development world that may not possess the ability to come up with their own technologies,” he explains.

During the spring 2026 semester, he is collaborating with the center’s Undergraduate Fellows Program. This program enables postdocs to work on their research projects with MIT undergraduates. Park is working with two CIS undergraduate fellows to develop a new dataset examining international trade in green technologies. This opportunity reconnects Park to his early academic experiences in South Korea that set him on the path to MIT.

Path to MIT

“Students in South Korea are trained to be problem-solvers,” explains Park, who was born and raised in Seoul. The country’s rigorous college entrance exams reward those who can answer the most questions quickly and accurately in a limited amount of time.

While taking a test in high school, Park stumbled over a question that he couldn’t answer, regardless of how much time he spent concentrating on it. He handed in the exam, but took the problem home and spent hours puzzling over it — he just couldn’t let it go. “In hindsight, I see this as the moment I decided that I wanted to become a scholar,” Park says.

While majoring in international studies and economics (statistics) at Korea University, he had the opportunity to participate in a semester-long exchange program at the University of Texas at Austin. There, Park enrolled in a political science course on game theory that explored how individual state actors’ decisions influenced one another’s choices and outcomes in trade, conflict, and diplomacy. The instructor used the ongoing war between North and South Korea as a case study, demonstrating the unique circumstances for escalation or de-escalation depending upon how the key actors made choices along the way.

“I saw for the first time how quantitative methods could be applied to international relations and political economy,” Park says — and he knew that his next step was going to be graduate work in the United States. He began a joint MA and PhD program in political science at Princeton University the following year, supported by a Fulbright Fellowship.

Park’s 2025 dissertation examined the global governance of intellectual property rights — and it was timely. He began his PhD program in 2018, “the point at which the U.S. and China trade war had just begun.” During the pandemic, he was moved by the ongoing debates regarding vaccine inequality. “I realized then that intellectual property was at the center of these global economic challenges.” With little political science research on the topic, he “set out to create a systemic framework” to study it.

Simultaneously, he served as a teaching assistant in undergraduate courses in statistical analysis and realized that he deeply enjoyed the experience of teaching and interacting with students. It was a very different experience from his own college years. 

“In South Korea, it’s common for the learning environment to be one in which the professor just delivers lectures, but I found that in the United States’ higher education system, the classroom is truly interactive. I learned something from each of my students.” Soon, Park was certain that he not only wanted to build a career in academic research, but also a future that heavily incorporated teaching and mentoring students.

Before graduating, he spent a year at Georgetown University as a predoctoral fellow affiliated with the Mortara Center for International Studies. This experience enabled him to explore the policy implications of his research and engage with policymakers in Washington — skills he will draw on in his new position.

Lasting lessons from CIS

Park recently accepted a position as assistant professor at the National University of Singapore. Beginning fall 2026, he will be teaching graduate students affiliated with the school of public policy — most of whom will have career experience as practitioners in the public or private sectors. 

He’ll take many lessons from MIT to his new academic home, he says. “Based on what I learned in the United States, I’ll make the learning environment in the graduate courses I teach much more interactive and collaborative.”

At CIS, Mihaela Papa, director of research and principal research scientist, and Evan Lieberman, the center’s director and professor of political science, connected Park to associated faculty whose research interests were related with his own. “Meeting with all of these scholars whose research relates in some way to intellectual property rights made me think about how my own interests can expand to other topics,” Park explains. 

But the biggest takeaway of all is that he learned how to share his own research with scholars who study unfamiliar topics, to exchange ideas and discover commonality. “I’ll never stop using the communication skills that I got here at MIT," Park says.