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.

Over the past 80 years, America’s bold, sustained investment in scientific research, and the discoveries, ideas and innovations that flowed from it made America a world leader. The nation’s scientific leadership has been essential to our shared prosperity and national security, and delivered real benefits for all Americans.

On June 16, Scientific American released a special section, “The Young American Scientists,” which celebrates early-career professionals actively engaged in scientific research, and features commentary from MIT faculty on why they continue to be so devoted to curiosity-driven science, demonstrating how their hard work and dedication make Americans safer, healthier, and more prosperous. Among the section’s profiles are many MIT faculty, students, and alumni, who share their advice for young scientists and their reasons for optimism in uncertain times.

President Sally Kornbluth emphasizes the importance of curiosity-driven research, noting that discovery “is part of our American DNA and has yielded vast returns to the citizens of this country and the world.” She adds, “what’s needed is a rededication to public investment in American science. Even if I were not the leader of a premier scientific institution, this is what I’d say. Investing in American science is not a gamble; if you look back in time, there is no question about the benefits.”

Adds Institute Prof. Robert Langer: “What American science has done over the past 50, 100 years has been remarkable.”

Scientific American notes that at MIT, that commitment to discovery is reflected in initiatives such as Curiosity on a Mission and the Generative AI Impact Consortium, which are aimed at finding “solutions to real-world problems in a way that is beneficial to society.” “On one hand, we’re at a time, technologically, where things could not be more exciting [and] our science [could not be] more cutting-edge. At the same time, we’ve never seen a situation where people felt so uncertain about the continuity of science funding, particularly when it comes to the basic discovery science that fuels the economy and will fuel societal impact a decade or two from now,” says Kornbluth.

The first sparks

Witnessing invention can spark a lifelong fascination with science. After the launch of Sputnik, the world’s first artificial satellite, Prof. Alan Lightman “became entranced with the idea of building a rocket” of his own. In his essay “My childhood in science,” Lightman describes how these early scientific memories and experiments have shaped him to be a well-rounded writer and physicist.

“Now more than ever, when much of the world, including the U.S., has lost its moral compass, leading to a dog-eat-dog mentality, we need science combined with literature, philosophy, history and art. We need to discover not only the physical world but also our own humanity,” writes Lightman.

Likewise, Prof. John Urschel, a former NFL player, emphasizes the importance of collaboration and having a wide range of interests. 

“A lot of good research happens when people can draw on tools, techniques and insights from different areas, disciplines and even fields. I hope we can encourage promising young scientists to establish strong, broad backgrounds and to communicate frequently with those outside their particular areas,” says Urschel.

Invention and discovery

Scientific American highlights students and alumni looking to better the world by doing everything from investigating neurological disease to securing our energy future. 

At MIT, Visiting Scientist Alice Stanton developed miBrain, a 3D tissue model of the human brain, to help scientists develop personalized treatments for Alzheimer’s and Parkinson’s. Stanton has developed a miniature version of miBrain, a brain-on-a-chip, to better test therapeutics.

Stanton notes “the road to effective treatments is long and bumpy,” compounded by cuts to federal funding. “When we have a loved one who gets sick, we want a treatment—we want something to cure them. It doesn’t come out of thin air,” she explains.

Bob Mumgaard PhD ‘08, CEO of Commonwealth Fusion Systems is working to commercialize fusion power. “Whether in areas such as fusion—or in drugs by design for diseases such as Alzheimer’s and Parkinson’s or in [the creation of] materials we never thought possible—our ability to use new tools to tackle some of these big, meaty problems is super exciting,” Mumgaard emphasizes. 

Graduate student Alex Zhang tackles context rot: the phenomenon when AI language models degrade as they produce more information. To solve this issue, Zhang develops recursive language models (RLMs) that enable the model to work with itself to reevaluate reasoning.

“The types of research that I want to work on are things that I think should be shared for the benefit of people in general,” says Zhang. 

The benefits of scientific collaboration 

What happens when scientific disciplines join forces at MIT?

Prof. Emery Brown highlighted the MIT Health and Life Sciences Collaborative (HEALS), noting that the effort brings together scientists and engineers from a variety of backgrounds to tackle the most pressing health challenges of our times.  

Brown explains that with President Kornbluth’s support, HEALS encourages “faculty to look more deeply into solving health care problems. The enthusiasm for HEALS has been contagious across the campus.”  

MIT alumna Lucy Jones PhD ‘81, who is known for her work advancing public safety during earthquakes and for developing the first American earthquake drill called the Great ShakeOut, shared the necessity of collaboration in developing scientific solutions for pressing real-world problems.

 “Solutions have to be done in collaboration, which means spending time with policymakers,” says Jones. 

Jones also shares how scientific advances in computing have helped make Americans around the country safer when the ground starts to shake.

“My first year in grad school, I was reading paper seismograms. Now everything is computerized. We used to do field deployments; now we have permanent networks. We’re starting to use fiber‑optic cables as seismometers,” says Jones. “Computers have changed everything, including science.”

The state of American science 

Within the profiles, interviewees were asked what needs to change in American science right now. Many expressed concerns with federal funding. 

“I’m fortunate to work with extraordinary students and postdocs, but the infrastructure that lets them do their best work is under real stress: funding instability at the National Institutes of Health and the National Science Foundation, immigration uncertainty for international scientists and an erosion of public trust in expertise,” says Prof. Feng Zhang.

Zhang developed CRISPR-based genome editing tools, which could increase our understanding human diseases and lead to new treatments. “We can lose the lead rapidly if we do not protect our innovation ecosystem,” he says.

Positive developments include the progress Prof. Alan Guth has witnessed in cosmology. 

“With new techniques, we’re able to unravel, to make sense out of, what we’re observing,” says Guth. “A lot of progress has been made on those lines, so in terms of the physics of the field, I think things are going great. But to me, the real problem is the prospects for future funding.”

Langer shares his faith in the durability and strength of America’s science and innovation ecosystem. 

“I look at the history of American innovation and education over the past 250 years, and it’s been spectacular,” says Langer. “Plenty of times there’ve been setbacks. We’ve had world wars, you know, we’ve had depressions, and people keep persisting and keep learning. They keep discovering and they keep inventing. So that gives me a lot of cause for hope. This is not the worst time by any means.”

Summer is the perfect time to curl up with a good book — and MIT authors have had much to offer in the past year. The following titles represent a selection of books published in the past 12 months by MIT faculty and staff.

Looking for more literary works from the MIT community? Enjoy our book lists from 2025,  2024, 2023, 2022, and 2021.

Happy reading!

Fiction and poetry

“We (the People of the United States)” (Penguin Books, 2026)
By Joshua Bennett, the Distinguished Chair of the Humanities at MIT and professor of literature

Bennett marks the 250th anniversary of the founding of the U.S. with a book-length work of poetry about the country and some of its distinctive figures. The piece features remarkable people or inventions from each of the 50 states, meditating on their place in the nation’s cultural fabric.

“The Race for Daphne” (Finishing Line Press, 2026)
By Sarah C. Beckmann, communications and marketing associate in the MIT Media Lab

A poetry collection structured as a crew race exploring girlhood, womanhood, and motherhood through the experiences of a rower and writer. These poems subvert the historical dominance of male heroes by celebrating ordinary female heroism, while examining love, home, and what it means to be an American woman today.

“Jezelle: Thief of Forks” (Self-published, 2026)
By Scott Austin Tirrell, director of administration and finance in the Art, Technology, and Culture Program

Abandoned by her father and raised by the streets of Grafton Notch, Jezelle survives by trusting no one. When a strange magic awakens within her, it offers more than escape — it offers power. But in a city that preys on broken children, power makes her valuable, dangerous, and hunted. To claim the life stolen from her, Jezelle must decide what she is willing to become.

Science and Engineering

“Phenomenal Moments: Revealing the Hidden Science Around Us” (Candlewick Press, 2025)
By Felice Frankel, research scientist in the Department of Chemical Engineering

Enlisting readers to “be the scientist” through vivid fine-art photographs, science photographer Felice Frankel zooms in and out on beautiful and brilliant moments all around us to reveal the chemical, natural, or physical processes — from viscosity and venation to chlorophyll and capillary action — behind scientific phenomena.

“Syntax: A Cognitive Approach” (MIT Press, 2025)
By Edward A. F. Gibson, professor of brain and cognitive sciences

This book lays out the grammar of a language from the perspective of a cognitive scientist, outlining the components of language structure and the model of syntax that Gibson advocates: dependency grammar, in which a word is connected to another word via a dependency arc to form a larger compositional meaning. This formalism can explain numerous aspects of word order universals across languages.

“Birds Up Close: An Engineer Explores Their Hidden Wonders” (MIT Press, 2026)
By Lorna J. Gibson, professor post-tenure in the Department of Materials Science and Engineering 

A renowned engineer and lifelong birder, Gibson explores the hidden microscopic structures and engineering principles that keep birds aloft and alive — how an egg forms, how a bird generates lift, how woodpeckers safely drill their holes, and much more. She also considers the longer view of birds in their habitats and natural history. Her up-close look at avian mysteries provides a perspective like no other, for the expert ornithologist and curious observer alike.

“Carbon Renewal” (MIT Press, 2025)
By Howard J. Herzog, senior research engineer at the MIT Energy Initiative, and Niall Mac Dowell

In “Carbon Renewal,” Herzog and MacDowell discuss how technology and policy can come together to help us reach “net-zero” climate targets. The authors explore the rapidly evolving world of carbon dioxide removal (CDR), presenting the technological pathways of enhancing the land sink, biomass-based carbon capture and storage, engineered removal methods, and ocean-based carbon removal. They also discuss barriers facing CDR as well as ethical implications of this process. 

“Climate Change, Drinking Water Security, and Public Health: Global Challenges and Solutions” (Springer Nature, 2026)
Chapters by Libby Hsu, associate director of academics at MIT D-Lab

In her chapter, “Drinking Water Status Around the World and Its Effect on Health,” Hsu discusses the Earth’s water resources, which are found in a variety of settings. In her chapter, “Waterless and Low-Water Sanitation Technologies that Improve Quality of Life and Conserve Water Resources,” she shares her experience with sanitation challenges in the Global South and how that has reinforced the value of waterless and low-water sanitation technologies that are suitable for scaling around the world.

“A Pox on Fools: The True Believers, Grifters, and Cynics Who Convinced Us to Reject Vaccines” (Penguin Random House, 2026)
By Thomas Levenson, professor of science writing in MIT Comparative Media Studies/Writing

In his latest book, Levenson searches for the origins of the most common arguments against vaccines: that they are unnatural; that they are more dangerous than the illnesses they claim to prevent; and that they are an affront to freedom. “A Pox on Fools” explores the human impulse to question and wonder — sometimes past the point at which the very act of questioning turns deadly.

“The Shape of Wonder: How Scientists Think, Work, and Live” (Penguin Random House, 2025)
By Alan Lightman, professor of the practice of the humanities in MIT Comparative Media Studies/Writing, and Martin Rees

Lightman and Rees pull back the curtain on the field of science, revealing that scientists are driven by the same sense of curiosity, wonder, and responsibility toward a future that shapes us all. They guide us through the fascinating lives and minds of scientists around the world and throughout time, and provide an inside peek at what makes scientists tick — their daily lives, passions, and concerns about the societies they live in.

“Uncertainty in Climate Change Research: An Integrated Approach” (Springer Nature, 2025)
Chapter by Jennifer Morris, principal research scientist at the MIT Center for Sustainability Science and Strategy and the MIT Energy Initiative, and John Reilly, senior lecturer in the MIT Sloan School of Management

Understanding future emissions scenarios is essential for preparing for climate change. The chapter “Emissions and Concentration Scenarios” examines how socioeconomic uncertainty contributes to overall climate change projections, and identifies key drivers of greenhouse gas emissions. It reviews the history of emissions scenarios and compares various approaches, including IPCC methods and formal uncertainty analysis techniques. The chapter concludes with lessons learned from over 40 years of socioeconomic scenario development for climate research.

“The Headache: The Science of a Most Confounding Affliction — and a Search for Relief” (Harper Collins, 2025)
By Tom Zeller Jr., managing editor of Undark, published by the Knight Science Journalism Program at MIT

From blinding migraines to severe headache disorders known as “clusters,” chronic head pain affects 40 percent of the population, many of them suffering in silence. Finally, “The Headache” reveals the science behind a group of disorders that is as much a curse as a cultural punchline, and leads to key insights into the nature of pain itself. Guided by his own decades-long struggle with cluster headaches, Zeller’s journey into headache science is at once intimate and panoramic.

Culture, humanities, and social sciences

“The People Can Fly: American Promise, Black Prodigies, and the Greatest Miracle of All Time” (Little, Brown, and Company, 2026)
By Joshua Bennett, the Distinguished Chair of the Humanities at MIT and professor of literature

In this work, Bennett offers a series of profiles, carefully wrought to see how some prominent figures were able to flourish from childhood forward. He closely reads their works for indications about how they understood the shape of their own lives. In so doing, Bennett underscores the significance of the social settings that prodigious talents grow up in. He also offers reflections on his own career trajectory and encounters with these artists, driving home their influence and meaning.

“Thinking Historically: A Guide to Statecraft and Strategy” (Yale University Press, 2025)
By Francis J. Gavin, research affiliate of the MIT Security Studies Program 

It seems obvious that we should use history to improve policy. If we have a good understanding of the past, it should enable better decisions in the present, especially in the highly consequential worlds of statecraft and strategy. But how do we gain that knowledge? How should history be used? In this book, Gavin explains the many ways historical knowledge can help us understand and navigate the complex, often confusing world around us. 

“The Economic Consequences of the Second Trump Administration: A Preliminary Assessment” (Centre for Economic Policy Research, 2025)
Edited by Gary Gensler, professor of the practice of global economics and management and finance in the MIT Sloan School of Management; Simon Johnson, the Ronald A. Kurtz (1954) Professor of Entrepreneurship and professor of global economics and management at MIT Sloan; Ugo Panizza; and Beatrice Weder di Mauro

How might the economic and geopolitical positions of the Trump administration affect growth, trade, investment, inflation, stability, and the role of the U.S. dollar? This volume offers evidence-based, expert analysis to help decision makers understand the impact of tariffs, breaks in global alliances, government downsizing, deregulation, threats to the rule of law, and more.

“The Colony and the Company: Haiti after the Mississippi Bubble” (Princeton University Press, 2025)
By Malick W. Ghachem, professor of history

Many things account for Haiti’s modern troubles. A good perspective on them comes from going back in time to 1715 or so — and grappling with a far-flung narrative involving the French monarchy, a financial speculator named John Law, and a stock-market crash called the “Mississippi Bubble.” In "The Colony and the Company," Ghachem examines the economic transformations and multi-sided power struggles of that time.

“Retrench, Defend, Compete: Securing America’s Future Against a Rising China” (Cornell University Press, 2025)
By Charles L. Glaser, senior fellow in the MIT Security Studies Program 

Many believe China’s ascent will drive it to war with the United States. Yet this is far from inevitable; geography and nuclear weapons should ensure U.S. security. The real danger, Glaser contends, lies in East Asia’s territorial disputes, especially over Taiwan. To reduce the risk of war, Glaser makes a bold case for ending U.S. security commitments to Taiwan and carefully calibrating its policies on protecting South China Sea maritime features. 

“Trade in War: Economic Cooperation Across Enemy Lines” (Cornell University Press, 2025)
By Mariya Grinberg, associate professor of political science and MIT Security Studies Program affiliate

“Trade in War” is an urgent, insightful study of a puzzling wartime phenomenon: states doing business with their enemies. To explain why states trade with their enemies, Grinberg examines the wartime commercial policies of major powers during the Crimean War, the two World Wars, and several post-1989 wars.

“Constructing Economic Nationalisms in Brazil and India” (Cambridge University Press, 2026)
By Jason Jackson, associate professor in political economy and urban planning in the Department of Urban Studies and Planning

Conventional approaches cite India’s leftist “socialism” and Brazil’s right-wing authoritarianism to explain why India resisted foreign direct investment (FDI) while Brazil welcomed foreign firms. However, this ignores puzzling industry-level variation: India restricted FDI in auto manufacturing but allowed multinationals in oil, while Brazil welcomed foreign auto companies but prohibited FDI in oil. This book argues that FDI policies were shaped by contrasting colonial experiences that generated distinct economic nationalisms and patterns of industrialization in both countries. 

“Traders, Speculators, and Captains of Industry: How Capitalist Legitimacy Shaped Foreign Investment Policy in India” (Harvard University Press, 2025)
By Jason Jackson, associate professor in political economy and urban planning in the Department of Urban Studies and Planning

Is foreign capital an agent of economic growth in developing countries or a vehicle of extraction? Examining how Indian elites wrestled with this question in the late colonial and postcolonial periods, Jackson argues that it reflects a false binary. Instead of simply choosing between domestic and foreign capital, Indian policymakers have long considered the business ethics of individual firms. Indian economic nationalism, in other words, has never been characterized by a straightforward preference for domestic over foreign capital.

“The Handbook of Social Protection: Evidence and New Directions for Low- and Middle-Income Countries” (MIT Press, 2026)
Edited by Benjamin A. Olken, the TEPCO Professor of Economics in the Department of Economics, and Rema Hanna

Over the past several decades, social protection programs that provide financial assistance to the poor and insure against shocks for the vulnerable have become widespread in low- and middle-income countries. These programs can play a critical role in society. This book provides an overview of what we know about the differing aspects of social protection and highlights the open questions for research for the future. 

“Argumentation: The Key Concepts” (Routledge, 2026)
By Edward Schiappa, the John E. Burchard Professor of Humanities in MIT Comparative Media Studies/Writing

In this book, Schiappa delves into the identification and analysis of fallacies, the evaluation of evidence, and the crucial roles of context, audience adaptation, and argumentative style. It explores the ethical dimensions of argument, the impact of cognitive bias, and the influence of cultural and discourse communities.

“American Independence in verse” (Pentameter Press, 2025)
By Brad Skow, the Laurence S. Rockefeller Professor in the Department of Linguistics and Philosophy

“American Independence in verse,” published by Pentameter Press, traces a story of America’s origins through a collection of vignettes featuring some well-known characters, like politician and orator Patrick Henry, alongside some lesser-known but no less important ones, like royalist and former chief justice of North Carolina Martin Howard. Each is rendered in blank verse, a nursery-style rhyme, or free verse.

“Rwanda’s Genocide Heritage: Between Justice and Sovereignty” (Duke University Press, 2025)
By Delia Wendel, associate professor of urban studies and international development in the Department of Urban Studies and Planning

Drawing from oral histories and a visual archive of memory work after the 1994 genocide in Rwanda, Wendel explores the human rights and government priorities that preserved killing sites and victims’ remains for public display. Rwanda’s genocide memorials exemplify a global phenomenon that Wendel terms “trauma heritage,” wherein hidden or unrecognized violence is made visible in public space to demand justice and recognition. Wendel argues that trauma heritage innovates on the form histories take by “writing” them into landscapes, constituting a reparative historiography from the Global South. 

Technology and society 

“Computing in the Age of Decolonization: India’s Lost Technological Revolution” (Princeton University Press, 2026)
By Dwaipayan Banerjee, associate professor of science, technology, and society

In this book, Banerjee examines India’s pursuit of technological self-sufficiency, and the global forces that prevailed against this vision. He describes why the nation is “the world’s leading provider of inexpensive outsourcing and offshoring services, yet enjoys minimal benefits from more profitable advances in research, manufacturing, and development.”

“Auditing AI” (MIT Press, 2026)
By Karrie G. Karahalios, professor of media arts and sciences at the MIT Media Lab; Marc Aidinoff PhD ’22; Nathan Matias SM ’13, PhD ’17; Christian Sandvig; Alondra Nelson; Kristen Vaccaro; Esha Bhandari; Ellery Roberts Biddle; Lena Armstrong; Motahhare Eslami; and Danaé Metaxa

This book serves as a first-of-its-kind roadmap for auditing artificial intelligence systems to prevent decision-making failures in health care, policing, and employment. Using canonical examples of AI gone wrong — from misidentified facial recognition to biased hiring algorithms — this book explains why robust audits are essential and how they drive concrete policy and corporate change.

“Shape Computation: Fifty Years, 1972-2022” (Springer Nature, 2025)
Edited by Sotirios Kotsopoulos SM ’00, PhD ’05, a research affiliate in the Department of Architecture, with a chapter by Terry W. Knight, the William and Emma Rogers Professor of Design and Computation in the Department of Architecture

This book provides a panorama of “shape computation” and “shape grammars,” a computational theory that has, from its inception 50 years ago, been directed toward the “how” of design. Knight’s chapter, “How is that? Computing the Temporality of Drawing,” describes how process and time are key to studying, appreciating, designing, and making things. She notes that in creative production it is not only important to ask, “What is that?” but also “How is that?” — in other words, how did or how can a thing come to be? As a process carried out over time, computation offers a means for rethinking, representing, and elevating the “how” in designing and making activities. 

“The Remote Revolution: Drones and Modern Statecraft” (Cornell University Press, 2025)
By Erik Lin-Greenberg, associate professor in the Department of Political Science

In “The Remote Revolution,” Erik Lin-Greenberg shows that drones are rewriting the rules of international security — but not in ways one would expect. Leveraging diverse types of evidence from original wargames, survey experiments, and cases of U.S. and Israeli drone operations, Lin-Greenberg explores how drone operations lower risks of escalation. 

“The Comedy of Computation: Or, How I Learned to Stop Worrying and Love Obsolescence” (Stanford University Press, 2025)
By Benjamin Mangrum, associate professor of literature

We often deal with our doubts and fears about computing through humor, whether reconciling ourselves to machines or critiquing them. In fact, this dynamic turns up throughout modern culture, in movies, television, fiction, and the theater. Mangrum analyzes this phenomenon in “The Comedy of Computation,” digging into several facets of modern culture and technology.

“Rubrique Technologie / Tech Section” (Printed Matter, 2026)
By Nick Montfort, professor of digital media in MIT Comparative Media Studies/Writing, and Patsy Baudoin

This work is based on a text generator that produces French and English news items that imagine some of the ways technology will impact us in the near future. Most of the generated news involves people getting struck by autonomous vehicles or even aircraft. Others describe labor disputes, hostile takeover attempts, inventions, and the termination of online services. What is imagined in “RT/TS” is not apocalyptic or discontinuous but actually features many of the same problems we face today; the methods of producing the texts are today’s as well.

“Shared Wisdom: Cultural Evolution in the Age of AI” (MIT Press, 2025)
By Alex “Sandy” Pentland, the Toshiba Professor of Media Arts and Sciences and professor of information technology in the MIT Media Lab

How can we build a flourishing society by using human nature to design technology rather than letting technology shape society? Pentland explores how cultural inventions — from civilizations to the Enlightenment — accelerated innovation and collective wisdom. He argues that understanding these key factors in cultural evolution is essential for solving global challenges like climate change and pandemics, and shows how AI and digital media can aid rather than replace human deliberation.

“Priority Technologies: Ensuring US Security and Shared Prosperity” (MIT Press, 2026)
Edited by Elisabeth B. Reynolds, professor of the practice of urban studies and planning, with a foreword by Simon Johnson, the Ronald A. Kurtz (1954) Professor of Entrepreneurship and professor of global economics and management

A new world order is emerging, and within it, U.S. priorities are shifting. For the country to flourish as well as defend and secure its interests, it must build on its decades of experience in developing frontier technologies and globally competitive industries through investments into priority technologies for the 21st century. This volume presents an introduction to some of the key areas where the U.S. must lead in order to ensure both national and economic security: critical minerals, semiconductors, biomanufacturing, quantum computing, drones, and advanced manufacturing.

Education, work, finance, and social impact

“The Meritocracy Paradox: Where Talent Management Strategies Go Wrong and How to Fix Them” (Columbia University Press, 2025)
By Emilio J. Castilla, the NTU Professor of Management and professor of work and organization studies in the MIT Sloan School of Management

Organizations often hail meritocracy as a fair and efficient way to identify, advance, and reward talent. But efforts to create a level playing field can be held back by talent management systems that confer rewards based on individual performance evaluations. In practice, these merit-based systems “may actually reinforce or create advantages for certain groups,” Castilla contends.

“The Art of Monetary Policy: Lessons from Sun Tzu for Central Banks” (MIT Press, 2026)
By Kristin J. Forbes, the Jerome and Dorothy Lemelson Professor of Management and professor of global economics and management in the MIT Sloan School of Management

Central banks are navigating a world of higher debt, tightly interconnected markets, and rising geopolitical tensions. How might they respond effectively? In “The Art of Monetary Policy,” Forbes draws on the writings of Chinese military strategist Sun Tzu to suggest modern principles for central banks, including preparing for the next financial battle, establishing a strong tactical position, combining weapons and methods, and modifying and varying tactics to maintain flexibility.

“Launching from the Lab: Building a Deep-Tech Startup” (MIT Press, 2026)
By Lita Nelsen, former director of the MIT Technology Licensing Office, and Maureen Stancik Boyce, mentor for the MIT Sandbox program

“Launching from the Lab” provides a much-needed framework for new entrepreneurs who are founding companies based on “deep technology” — groundbreaking innovations rising from new discoveries in fundamental research. Nelsen and Stancik Boyce cover the steps to launch and fund such companies, beginning with emergence from the laboratory and acquiring intellectual property through the intensive research of customer needs, building a team, and raising capital.

“There’s Got to Be a Better Way: How to Deliver Results and Get Rid of the Stuff That Gets in the Way of Real Work” (Hachette, 2025)
By Nelson Repenning, professor of management, and Donald Kieffer

The chaos of everyday business forces people into an exhausting, ineffective, seemingly never-ending cycle of work-arounds, firefighting, and Whac-a-Mole. The irritatingly urgent crowds out the lastingly important. In this book, Repenning and Kieffer describe the game-changing discipline of dynamic work design, which improves productivity, reduces costs, and increases efficiency, ensuring that all parts of a company can work in concert.

“Bayesian Entrepreneurship” (MIT Press, 2026)
Edited by Erin L. Scott, senior lecturer of technological innovation, entrepreneurship, and strategic management in the MIT Sloan School of Management; and Scott Stern, the David Sarnoff Professor of Management of Technology and professor of technological innovation, entrepreneurship, and strategic management at MIT Sloan

This edited volume introduces and explores the concept of Bayesian entrepreneurship, a novel framework for understanding entrepreneurial decision-making under uncertainty. It brings together contributions from leading scholars to examine how entrepreneurs form beliefs about opportunities, learn through experimentation, and make strategic decisions.

“Disciplined Entrepreneurship for Climate and Energy Ventures: 24 Steps to Build Solutions for People and the Planet” (Wiley, 2025)
By Ben Soltoff, entrepreneur in residence at MIT Sloan; Bill Aulet, Ethernet Inventors Professor of the Practice; Tod Hynes, senior lecturer of climate and energy ventures; Francis O’Sullivan, senior lecturer in technological innovation, entrepreneurship, and strategic management; and Libby Wayman, senior lecturer of climate and energy ventures

Climate and energy entrepreneurs face challenges that traditional startup playbooks don’t address. Their ventures can require massive capital and take years to reach market, all while striving to achieve a positive impact on people, planet, and profit. This book adapts the MIT-born “Disciplined Entrepreneurship” framework specifically for climate and energy ventures, recognizing that founders in this space need their own approach.

Arts and design, architecture, urban studies and planning

“Tiny Gardens Everywhere: The Past, Present, and Future of the Self-Provisioning City” (W.W. Norton, 2026)
By Kate Brown, the Thomas M. Siebel Distinguished Professor in History of Science

Nurturing health, hope, and community, gardeners in cities and suburbs are reclaiming lost commons, transforming vacant lots into vibrant plots, turning waste into compost, and recreating what was once the most productive agriculture in recorded human history. In a book with global scope, ranging from Estonia to Amsterdam and Washington, Brown contends that urban gardening has many positive spillover effects, from health and environmental benefits to community-building — apart from periods of pushback when others are trying to eliminate it.

“Small-Town Renaissance: Bridging Technology, Heritage, and Planning in Shrinking Italy” (Springer Nature, 2025)
Edited by Brent D. Ryan, vice provost and professor of urban design and public policy in the Department of Urban Studies and Planning; Carmelo Ignaccolo PhD ’24; and Giovanna Fossa

This book explores the transformative power of digitization in rural regions — where technology isn’t just a tool, but a lifeline for local culture, economic resilience, and future development. Born from a unique research collaboration between the MIT and Politecnico di Milano, this book brings together scholarly work on shrinking towns, economic development, and digital innovation. The project tackled some of the most pressing challenges facing rural Italy — from population decline to economic stagnation — through the lens of digital transformation. 

“Blanking: An Annotated Archive of Projects and Thoughts on Architecture” (Park Books / University of Chicago Press, 2026)
By Rosalyn Shieh, assistant professor in the Department of Architecture, and Troy Schaum

Based on the work and vision of their architecture firm Schaum/Shieh, this book shares what is said and what can be heard in a studio. So much of architectural thinking and knowledge is presented, formulated, and traded in spoken words: pinups, meetings, walkthroughs. Those exchanges inform this book, in which ideas and knowledge that are usually only spoken are made accessible to readers.

“Design Before Disaster: Japan’s Culture of Preparedness” (University of Virginia Press, 2026)
By Miho Mazereeuw, associate professor in the departments of Architecture and Urban Studies and Planning

Few countries have faced as many environmental disasters as Japan, which has endured typhoons, cyclones, floods, earthquakes, volcanic eruptions, and tsunamis. Japanese residents have responded to their precarious circumstances by developing a unique culture of disaster preparedness, equipping the island nation to plan for future emergencies and to greatly reduce their impact. Mazereeuw offers a detailed framework to design and prepare for anticipated disasters and describes effective interventions in urban landscape and architecture. 

“Reconstruction as Violence in Assad’s Syria” (American University in Cairo Press, 2025)
Edited by Nasser Rabbat, professor of architecture and director of the Aga Khan Program for Islamic Architecture at MIT, and Deen Sharp, with a foreword by Hashim Sarkis, dean of the MIT School of Architecture and Planning

This book delves into the complex interplay of post-conflict reconstruction in Syria, challenging the traditionally held dichotomy between the end of violence and the commencement of rebuilding. The contributors to this volume — architects, urbanists, geographers, and historians — employ critical concepts such as urbicide, domicide, and “civilian crisis architecture” to argue against the conventional theoretical frameworks that support a neat separation of phases.

Could the precise architectural form of your residence influence how much you participate in politics? 

A new study by MIT scholars finds this to be exactly the case — at least in Accra, Ghana, where many people live in semi-communal structures known as “compound houses,” often sharing kitchens, bathrooms, and common living-room spaces, while having private bedrooms.

The detailed study of homes in Ghana’s capital finds that residents of compound houses are more likely to vote, attend rallies, and take part in political campaigns, compared to people with more private forms of housing. 

“The overarching pattern we find is that if you compare people who live in compound houses to residents of other housing types, like single-family homes or self-contained apartments, there is a pretty big difference in political actions,” says Noah Nathan, an MIT political scientist and co-author of a newly published paper detailing the study’s results. “People seem to vote more, and there are more other types of political behavior, like going to rallies, participating in campaigns, and contacting politicians.”

While those differences could stem from factors other than housing, the highly granular study suggests the architecture itself really matters. The researchers examined the specific floor plans of compound houses and found variations in people’s political information and social connections — key factors that existing studies show predict political activity — that map to differences in where people live within compound houses.

“We show that those kinds of social relationships and exchanges of political information seem to vary systematically with people’s individual locations within the layouts of the buildings they live in,” says Nathan, an associate professor in MIT’s Department of Political Science. “That’s consistent with architectural design leading you to have different levels of political participation.”

The open-access paper, “Vernacular Architecture and Grassroots Urban Politics: How Politics Is Embedded in Residential Design,” appears in the American Political Science Review. Nathan’s co-author is Paige Bollen PhD ’23, an assistant professor of political science at Ohio State University.

Compound effects

Compound houses are a common form of residence in Ghana, much of West Africa, and some other parts of the world. They tend to house lower-income people who construct them out of inexpensive local materials. Trying to understand their effects is part of taking seriously the idea that place, and space, influence how people live. 

“Rather than just thinking of cities as big agglomerations of people, we should evaluate cities through their actual built forms and designs,” Nathan says. “Space affects politics because people interact with each other in space. It’s not just that people are near each other, but the designs force them to interact or talk in ways that affect how information is exchanged and how social networks form, and that can aggregate up into politics in terms of action and cooperation.”

To conduct the study, Nathan and Bollen used three forms of data to draw out the effects of compound houses on politics. Through pre-existing administrative and electoral data, they first show that polling stations in neighborhoods with a high proportion of compound houses have better electoral turnout than neighborhoods with fewer compound houses. And from existing national survey data, the researchers determined that residents of compound houses actively participate in politics more often. 

The researchers then conducted an original research survey of 1,272 residents in 391 compound houses in 30 neighborhoods of Accra, combined with mapping that showed the layout of those compound houses and where the survey participants lived within each one. In this way, they showed the effects of compound houses more precisely: Living in parts of them with especially high exposure to other people actually increases the amount of social network ties people report, as well as the amount of political information they obtain.

Quantitatively, changes in the centrality of people’s locations within compound houses seem to make a bigger difference in political engagement than other fundamental non-housing factors, such as changes in employment or measures of socioeconomic status. 

“We leverage that variation to show that even within compound houses, the people with more exposures to neighbors have different social network ties and different forms of information than neighbors who live in more private locations,” Nathan notes. 

Encouraging participation

As the scholars discuss in the paper, the effects of architecture on civic involvement are hardly immutable, but likely depend very much on the type of political state in question. 

“We think under different conditions, this kind of architecture could have different effects,” Nathan says. “If you live in an authoritarian regime with an active police state, inhabiting an architecture in which you’re constantly on display to your neighbors is probably going to have the exact opposite implications from what we find in the study.”

However, he adds, since Ghana has a generally healthy democracy and is not a repressive state, “In this context, where there are not such high costs to participating in politics, we think these effects are going to break in the direction of more political participation.”

The study itself is an outgrowth of long-running, overlapping research interests on the part of Nathan and Bollen. Nathan is currently developing a book project about urban form, architecture, and politics both in Ghana, where he has conducted research for many years, and in other cities across the African continent. Bollen conducted her PhD research at MIT on public spaces, interactions, and political dynamics in Ghana and South Africa; her advisor was MIT Professor Evan Lieberman.

Sociologists, management experts, architects, and planners have all studied the effects of building design on human behavior, but have often focused on issues such as workplace productivity. Some political scientists, including MIT Associate Professor Bernardo Zacka, have also highlighted the salience of architecture to politics. But few political scientists have undertaken quantitative empirical studies of the subject. If they do, Nathan thinks, the results might surprise some people. 

“There’s a famous idea that cities can be anonymizing,” Nathan says. “I think that’s actually not true. When you go to urban Ghana, people know each other, and there is a great deal of social capital and social connections. And I think part of the reason is that many people live in architectures that are not anonymizing.”

Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it.

But the way these highly fragmented systems are designed and deployed often causes inefficiencies that can lead to wasted computation, energy, and cost. 

To improve efficiency, researchers from MIT and Microsoft developed an intelligent system that streamlines the process of designing agentic workflows and automatically optimizes how those workflows are implemented. 

With this new method, a developer can describe what they want the agentic workflow to do in plain language, without needing to specify all the details of their application in advance. 

The system automatically figures out the best models and tools to use, as well as the ideal hardware configuration and computational resource allocation when the workflow is executed by a cloud provider.

It adjusts those configurations on the fly based on each user’s priorities, such as minimizing costs or maximizing speed.

When tested on several agentic workloads, this new system reduced the number of computational units needed for deployment, significantly cutting energy requirements and costs compared to traditional approaches without hampering performance.

“Agentic workflows are getting very complicated and quickly becoming the backbone of what cloud providers are doing. Energy usage is a huge concern, so we need to be very careful about how efficient these workflows are. It is very easy to over-allocate resources, wasting energy and money. Enabling a cloud provider to intelligently make these workflows more resource-optimal is a win for everyone involved,” says Gohar Chaudhry, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this system.

He is joined on the paper by Adam Belay, an associate professor of EECS and a member of the MIT Computer Science and Artificial Intelligence Laboratory; senior author Ricardo Bianchini, technical fellow and corporate vice president at Microsoft Azure; and others at Microsoft Azure. The paper will be presented at the USENIX Symposium on Operating Systems Design and Implementation.

A configuration conundrum

An agentic workflow is a system composed of several autonomous AI agents that collaboratively use various models and tools, like databases or Python programs, to dynamically complete a multi-step task, such data processing or code generation. 

These workflows can serve as behind-the-scenes processes that power user-facing applications.

Typically, developers must hard-code all technical choices upfront. They need to define which AI agents, models, and tools to use, and the order in which to use them. They also must specify the hardware that runs the workflow and how to balance tradeoffs like speed versus cost. 

This is especially challenging because agentic workflows bring together multiple black-box models and diverse tools, each with their own configuration options, which may be offered by different companies. 

If a new AI model is released that would improve the application’s accuracy or efficiency, the developer would need to start from scratch to implement it.

“Even if you wanted to do all this manually, it is unlikely that you’ll be able to configure the workflow optimally because the space of possible configurations is so large,” Chaudhry says. 

In addition, the cloud data center that deploys the application for customers can’t see inside the workflow to allocate its hardware resources in the most efficient manner at the time of the user’s request. 

With this new system, called Murakkab (an Urdu word that means a composition of things), the researchers sought to optimize the entire agentic workflow process.

Dynamic decision-making

First, Murakkab enables developers to create an agentic workflow by describing their intent for the application in high-level terms, rather than detailing how the many components of that workflow should be combined. 

For instance, a developer might describe a video Q&A application that extracts key frames, generates a transcript, and then answers user queries about the video. 

“There are many ways to do this, and all these different models and tools have implications on how fast the application can finish the task,” he says. 

Murakkab takes the developer’s straightforward specifications and automatically identifies the best existing models and tools to put together into the workflow. 

It also determines which components need to run sequentially and which can be run in parallel to boost performance. 

“The platform makes configuration decisions dynamically over time, so if a new model or GPU accelerator comes out tomorrow, the developer doesn’t need to worry about that,” he says.

When the cloud provider deploys that application for a customer, Murakkab optimizes the workflow by configuring its components to meet the user’s constraints, such as prioritizing accuracy while meeting a latency requirement. 

It adaptively identifies ideal hardware allocations and deployment schedules to maximize efficiency in real time, then generates a workflow that is ready for the cloud provider to execute.

“Our system also gives cloud providers visibility into multiple workloads, so the provider can share computational resources in the most efficient manner while satisfying the constraints of users,” he says.

When tested on diverse agentic workflows for video Q&A and code generation, Murakkab met user requirements while using only about 35 percent of the computation required by other methods. It consumed only about 27 percent as much energy for less than 25 percent of the cost.

The dynamic nature of Murakkab also enables users to balance tradeoffs. In one instance, the system lowered energy consumption of an agentic workflow by more than an order of magnitude with only about a 2 percent drop in accuracy for the customer.

The system was also able to identify an unexpectedly ideal configuration for a model that selects video frames, optimizing performance for a video Q&A task. This type of optimization would be nearly impossible for a developer to do manually, Chaudhry says. 

Next, the researchers plan to expand their system to more complex workflows and larger computing clusters while exploring opportunities to optimize new agentic applications. 

“There is a lot of potential to make these workflows more resource-optimal so they consume far less energy, but we need to be thinking about this at the scale of major cloud platforms,” says Chaudhry.

This research was supported, in part, by the Semiconductor Research Corporation and the U.S. Defense Advanced Research Projects Agency.

When an animal’s environment changes faster than the animal can adapt, its chances of survival can flat-line. The same is true for populations, and even entire species. 

Now, scientists at MIT and the University of Leicester have found that this connection between evolutionary adaptation and the pace of environmental change holds up at the global scale as well — and can determine life’s susceptibility to mass extinction. The researchers developed a theoretical model of this phenomenon, which they present in a paper appearing today in Physical Review Letters.

The team compared the model with available data from past major mass extinctions, including how fast the global environment changed at the time of each event. The model successfully predicted the severity of most mass extinctions in Earth’s history, or the fraction of life that was unable to adapt, and therefore went extinct. 

Interestingly, the researchers found that the range of adaptation rates across animal groups is broadly similar to the range of rates at which the environment can change.

“What we’re beginning to see is a certain level of organization, and ways in which life behaves that are consistent with the ways in which the environment behaves,” says study author Daniel Rothman, professor of geophysics and co-director of the Lorenz Center at MIT. “It may be that life has evolved so that its range of adaptabilities matches the range of stresses that it meets.”

Rothman’s study co-author is Sergei Petrovskii, professor of applied mathematics at the University of Leicester in England.

A catastrophizing connection

The connection between extinction and environmental change is not new. In the late 18th century, the French naturalist Georges Cuvier, who is often referred to as the founding father of paleontology, was the first to propose the concept of “catastrophism.” He had discovered fossil bones near Paris that didn’t match any animal known to exist at the time. Cuvier concluded that the bones were from a group of giant mammals that existed at one time but was no longer around. He proposed, then, that an entire species could disappear, or go extinct, likely due to a widespread catastrophe. 

“That itself was a major idea, that a species could go extinct,” Rothman says. “And he had suggested it was an environmental catastrophe that had caused it.”

The concept of catastrophism later gave way to the view that Earth’s history was shaped mainly by slow, gradual processes. But in the mid-20th century the American geologist Norman Newell revisited the problem. In seeking the cause of extinctions, he proposed what Rothman and Petrovskii call the “rate-mismatch” hypothesis, the notion that extinction occurs when the rate of environmental change is higher than the rate at which a species can evolve to adapt. 

Biologists have since observed Newell’s hypothesis play out in many cases where changes in the environment have driven the extinction of individual species. Rothman and Petrovskii wondered: Could the hypothesis also apply at the global scale?

“We know that individual species go extinct when environmental change outpaces their ability to adapt,” Rothman notes. “But it hasn’t been clear whether this same idea applies at the scale of global extinction events.”

Finding a mismatch

For their new study, the researchers looked to test the rate mismatch hypothesis at the global scale. They wanted to see whether mass extinction events in history can be explained by a mismatch between the rate of global environmental change and the rate at which life around the world can adapt. 

To do so, at least in theory, they would have to compare two sources of data: the rates at which the global environment has changed over time and the rates at which different groups of organisms adapt to environmental change. The first can be found in geological records, which scientists have used extensively to infer how the Earth’s climate changed through history. The second, however, is almost impossible to record.

“We’re talking about the rates at which organisms adapt to major environmental change at effectively geologic timescales, from thousands to millions of years,” Rothman says. “And that doesn’t lend itself to direct observation.”

In place of actual data, the researchers aimed to construct a general mathematical theory to describe the range of adaptation rates across animal groups around the world. In this context, “adaptation” refers to any change within a species, over time periods that are much longer than a generation, that enable the species to persist as its environment changes. 

It is generally understood in evolutionary theory that a species can successfully adapt only when multiple conditions are met. For instance, there needs to be variation in the population, these variations must be heritable, some variations enable an organism to adapt better than others, and the organisms that adapt better should leave more offspring. If all these conditions are met, the entire species should be able to adapt to a given environmental change. However, if any one condition fails, the population will go extinct. 

Rothman and Petrovskii recognized that in this case, a species’ probability of successfully adapting multiplies with every condition that it meets. And it turns out that this pattern can be described mathematically as a very simple, bell-shaped curve. Such a curve essentially describes what fraction of the world’s animals can adapt at given rates, from the slowest to the fastest adapters, and how this fraction changes nonlinearly with the rate of adaptation. This curve generally shows that most animal groups can adapt at intermediate rates, while fewer animal groups adapt at the slowest and fastest rates. 

After they established this general pattern of adaptation rates, the researchers looked to see how this pattern compares to recorded rates of environmental change, and how these two rates match, or don’t match, at times of mass extinction. 

To do so, they considered paleontological and geochemical data from 27 episodes over the last 450 million years where the carbon cycle experienced significant change — a measure that is generally understood to reflect global environmental change. They then compared rates of environmental change with the fraction of animal groups that went extinct during each episode — numbers that were established previously in a well-regarded study by paleobiologist John Alroy. 

In the end, Rothman and Petrovskii observed that indeed, for almost every mass extinction event in the last 450 million years, there was a mismatch in the rates at which the environment changed and at which animals could adapt; mass extinctions occurred when a significant fraction of animals could not adapt fast enough to match the changing environment. Their results confirm that the rate mismatch hypothesis applies at the global scale.

What’s more, this mismatch in rates could predict the severity of extinction events, or the fraction of animal life that went extinct given the rate at which the environment changed. 

In the case of the end-Permian extinction, it’s likely that the rapid acidification of the ocean outpaced organisms’ ability to evolve adequate protections, leading to the extinction of over 80 percent of the world’s marine species. 

The team’s work focuses on applying the new model to past extinction events. But the work could also provide a framework for understanding modern extinction risk. 

“Carbon dioxide levels in the ocean are increasing today at a rate which, when appropriately re-scaled, is similar to rates of carbon-cycle change that are just lower than those associated with major extinction events in the past,” Rothman says. “It suggests that modern environmental change may be approaching rates beyond which adaptation becomes increasingly difficult.” 

This research is supported, in part, by Schmidt Sciences, LLC; the MIT Climate Grand Challenges; the U.S. National Science Foundation; the European Space Agency; and the London Mathematical Society.

In 2022, global production of construction materials accounted for more than 7 percent of total carbon emissions. But how many of those materials were truly necessary to build houses, buildings, and bridges?

A technique called topology optimization can design structures that reduce the amount of material used, in some cases by as much as 90 percent, which would represent a multi-gigaton reduction in building emissions. Unfortunately, topology optimization is mostly used by researchers for applications like 3D printing rather than by engineers designing at the scale of buildings and bridges.

That’s because topology optimization doesn’t create structures that can easily be built on time and budget, which are the things builders really care about.

Now MIT researchers have created a way to make topology optimization designs more buildable. Their framework, described in a new paper in Automation in Construction today, allows users to apply constraints to algorithmically generated structures to limit their complexity. For instance, the approach allows users to limit how many components meet at each point of their design and how small they want their smallest parts. It also builds on previous work by designing structures with multiple materials and taking into account materials’ properties to distribute load and specify part connections.

“There’s an interplay between the materials you’re using, the constructability of designs, and the optimization of the structure,” says senior author Josephine Carstensen, MIT’s Gilbert W. Winslow (1937) Career Development Professor in Civil Engineering. “You need to be able to address all three at the same time. That’s what we tried to do here.”

The researchers used their approach to design steel, wood, and multimaterial truss structures that support loads in buildings and bridges, showing the carbon emissions associated with materials changed significantly when different constraints were applied. They hope their framework will move topology optimization closer to being used in real-world construction.

“In the literature, there’s sometimes been a disconnect between the carbon savings you can achieve on a computer and the realistic carbon savings you can achieve for built structures — especially when it comes to design technologies like topology optimization,” Carstensen says. “The problem lies in the lack of constructability of designs. These designs have been perceived as too difficult to make with conventional methods, so they are never even attempted. That’s what is exciting about our approach: We can add constraints so that you will never be in a situation where the design that comes out is too hard to make.”

Joining Carstensen on the paper is first author and civil and environmental engineering PhD student Zane Schemmer.

More buildable designs

Computer-based topology optimization has been around for decades. It uses computer programs to optimally distribute material in a given space, for instance creating the strongest possible structures at the lowest weight. The resulting designs are often complex, spider web-like structures that would be a challenge for even the most capable engineers to build.

“A big question Josephine and I were asking is why isn’t industry using it?” Schemmer recalls. “What are the obstacles that prevent industry from designing things more efficiently, and how can we fill the gaps between research and real life?”

In recent years, several researchers have developed ways to make topology optimization easier to use. For their study, Schemmer and Carstensen wanted to bring those approaches together and add new capabilities, like creating designs that use multiple materials, which has been another challenge in the field.

“A big aspect of sustainability going forward will be not only using less material, but also implementing materials efficiently based on considerations like where you are in the world, your access to materials, and each of their associated carbon costs,” Schemmer says.

To build their framework, they used a class of equations called mixed integer algorithms that help make binary decisions about things like materials and connections.

“You can’t have a part that’s 72 percent timber and 28 percent steel,” Schemmer says. “Instead, it says, ‘This truss or cable is going to be made out of this,’ and then based on that decision, how do we make sure all of these connections meet their strength standards?”

The system’s decisions also take into account material properties. For instance, steel struts can withstand compressive loads, but steel cables cannot. The model also has more realistic modeling of how parts connect than previous approaches.

“In 3D printing, the way things come together is easy,” Carstensen says. “In construction, that’s not the case. If you’re building with timber there’s a certain rule set, versus steel has a different rule set.”

Users can also decide how complex they want their design to be by specifying the maximum number of connections at each joint and the minimum angle between connected components. The model also creates minimum size limits for parts, further improving its constructability.

“It’s tough to give a contractor these complex, intricate designs because it’s going to be super difficult to build,” Schemmer says. “A lot of times contractors won’t pick up a project like that to begin with.”

The researchers compared structures designed with their approach to structures designed with conventional topology optimization, showing dramatic differences in final designs that transformed how the structures would be built. Using the Lockport “Upside-Down Bridge” near Buffalo, New York, as an example, they applied individual constraints, like a minimum angle on part connections or minimum part sizes, to the bridge’s truss design, to better understand how each constraint impacted final designs.

Finally, they made truss designs that used wood only, steel only, and combined wood and steel, showing how different projects offered tradeoffs with respect to environmental impact and constructability.

“We saw how the system knew that you could design a bridge of pure steel, but that might not be best from a carbon standpoint,” Schemmer says. “Or you could design a bridge out of purely timber, but that might not be the strongest. But these materials can work together, so you use timber for the carbon savings and steel where you need extra strength, and there’s a balance you can find in these structures.”

From research to industry

The researchers say their approach is more computationally intensive than some others, but they were able to use a MacBook Pro to run the programs in their experiment, and they believe it’s practical for most civil engineering firms.

“It’s computationally a little tougher to solve, but there’s a lot of tools coming out nowadays that make these problems a lot more feasible,” Schemmer says. “This approach has been avoided by industry in the past, but now we think it’s a practical way to solve problems dealing with variable constraints.”

If users have more computational resources, the researchers say their approach could work with a long list of materials and far bigger structures than homes, small buildings, and bridges.

Moving forward, Carstensen says the team plans to build scaled-down structures designed by the model to further validate its predictions. They also want to add constraints to their model to make it even more seamless for civil engineers to use when designing the world’s infrastructure.

“As a structural engineer by training, I was never taught how to design for low-carbon,” Schemmer says. “To tackle a problem as big as climate change, addressing the built environment is a great place to start. One of the most tangible things we can do is work at the layer of construction, at the design stage, because that’s a fundamental step that we can control. There’s a lot of decisions we make early on that lead us to use extra material we don’t need.”

The work was funded by the MIT Morningside Academy for Design.

At the recent AI and Society Forum at MIT, experts from across the Institute discussed the potential benefits and dangers of technological innovation on labor, the nature of work, civil discourse, election administration, and other topics.

The event featured individual research presentations and panel discussions, as well as a musical performance exploring the use of generative artificial intelligence in the arts.

The forum was co-organized by the School of Humanities, Arts, and Social Sciences (SHASS) and the Social and Ethical Responsibilities of Computing (SERC). It was presented in collaboration with two of MIT’s strategic initiatives: the MIT Generative AI Impact Consortium (MGAIC) and the MIT Human Insight Collaborative (MITHIC).

Agustín Rayo, the Kenan Sahin Dean of SHASS, and Dan Huttenlocher, dean of the MIT Schwarzman College of Computing, provided opening remarks.

Rayo said bringing scholars from across MIT together was intentional because understanding AI’s impact requires expertise from disciplines throughout the Institute.

“Paying attention to the societal consequences of AI is not a departure from MIT’s mission; it’s a way of ensuring that our technical leadership has maximum impact,” Rayo said.

Huttenlocher added that computing and AI’s rapid growth makes it critical to support interdisciplinary conversations and research.

“Understanding where AI excels and where it falls short is essential not only to unlocking its benefits, but also to avoiding critical errors, overreliance, and unintended consequences,” Huttenlocher said.

Jobs and AI 

Held in the Tull Concert Hall in MIT’s Linde Music Building, the May 12 forum opened with a keynote presentation from economist David Autor, the Daniel (1972) and Gail Rubinfeld Professor in the MIT Department of Economics. Autor challenged the common narrative that AI will simply eliminate jobs by proposing instead that technology's impact depends on how it affects the scarcity and value of human expertise. 

“When I think about how technology interacts with the value of labor, I think about it in terms of how it changes the scarcity of expertise, whether it makes it more valuable or whether it makes it more of a commodity,” he said.

Autor said that what matters is whether automation removes routine supporting tasks or removes expert tasks. He argued that AI will likely create new specialized work, requiring proactive policies around worker training, wage insurance, and broader capital ownership.

A panel discussion followed, moderated by Rob Loughlin, a partner at McKinsey & Company, featuring experts from MIT discussing how work is changing and what it means for society. 

Daniela Rus, the MIT Panasonic Professor of Computer Science and director of the Computer Science and Artificial Intelligence Laboratory (CSAIL), described excitement around ways AI could enhance the workplace.

“I’d like to imagine the robot as your friend and assistant, as someone who watches you and figures out how to help you as someone you can task at a high level,” she said. 

Still, Rus said, human judgment remains critical in decision-making.

“We could really think about co-work with the AI tools, but the role of the human as the decider, as the person with good judgment, as the person deciding the next step, whatever that is, remains super important,” she said.

David Mindell, professor of Aeronautics and Astronautics and the Dibner Professor of the History of Engineering and Manufacturing in the Program in Science, Technology, and Society, says the nature of work has constantly changed over the years, but “what matters is the new work.” 

“We need to be supporting individuals, the economy, professions, to constantly be creating the new work,” he said. “It’s absolutely imperative that we give the tools to the young people and let them do what they find creative and show us what the new work is going to be.”

Panelists also talked about the need to maintain safety standards, while also exploring ways to find efficiencies. Mindell used an example of cargo flights that require six pilots due to the length of the flight.

“We don’t know how to take that six number down to five yet, much less two, one, or zero. There's a lot of money behind solving that problem, but there's also a very rich system that has evolved to make those systems safe,” he said.

Sendhil Mullainathan, the Peter de Florez Professor with dual appointments in the MIT departments of Economics and Electrical Engineering and Computer Science (EECS), described a vision of AI’s utility and growth that offers productivity improvements, but also cautioned, “I think it's very much worth differentiating productivity gains from things that actually drive long-term growth.”

Either way, Mullainathan said, it’s clear we’re entering a time of high variance with regard to AI’s impact on the workforce.

“If you said, ‘exactly how will organizations restructure?’ I don’t know. But is there going to be a lot of restructuring? It’s hard to believe there isn’t going to be a lot of restructuring. And in some sense, if we know that what we’re entering is a period of high variance, that itself is incredibly informative,” he said.

Democracy and AI

The day’s second session focused on AI technology and its impact on democracy. 

Chara Podimata, the Class of 1942 Career Development Assistant Professor and assistant professor of operations research and statistics in the MIT Sloan School of Management, presented her research on auditing large language models for bias in election information.

“Algorithms decide a lot of things about our lives right now,” she said. “With regard to chatbots and election information, if I take two people and they interact with the same chatbot … how will the chatbot respond? How will it personalize the information it gives to these people?”

A longitudinal study of 12 major models during the 2024 U.S. presidential election season found responses varied dramatically based on stated demographics and political leanings. Her research team is now working on a new audit of the 2026 U.S. midterm elections, using a redesigned survey with input from political science experts.

During a panel discussion moderated by Songyee Yoon, founder and managing partner at Principal Venture Partners and member of the MIT Corporation, experts raised concern about the potential for AI to erode democratic norms and processes, but also explored potential positive outcomes.

Bailey Flanigan, the Theodore T. Miller (1922) Career Development Professor in the Department of Political Science, who holds an MIT Schwarzman College of Computing shared position with EECS, said she’s skeptical of how some are applying AI as a tool that can get people to reach decisions or consensus more quickly.

“And there is a reason to think that this is nice because it is more efficient. It's easier. But it loses a lot of these procedural elements of democracy that are the rituals of how we come together and make decisions,” she said. “And I think it’s a mistake to forget about that when we start thinking about automation.”

Charles Stewart III, the Kenan Sahin (1963) Distinguished Professor of Political Science and founding director of the MIT Election Data and Science Lab, said one challenge is that governmental structures do not evolve at the same rate as technology.

Stewart said his biggest concern is the potential for AI to lead to chaos during and after elections.

“If and when things go wrong, they can go really bad, and really wrong. If an election is called into question, that can lead to violence,” Stewart said.

“We’ve already seen in the low-tech eras election results being manipulated. What worries me is what I’m going to observe this coming Election Day, and the Wednesday after, and if AI has helped to create irreversible disruptions to the election system,” he added.

Lily Tsai, the Ford Professor of Political Science and director and founder of the MIT Governance Lab (MIT GOV/LAB), said in many ways, AI runs against the democratic norms and commitments necessary for a healthy democracy.

“It is really important not just in terms of design principles, but the commitments of designers to be familiar with the values and principles that characterize what democracy is based on: agency, political equality, mutual respect, inclusion, and autonomy,” Tsai said.

Tsai also noted her research has shown some people are more comfortable interacting with machines. She described a “Socratic dialogue chatbot” her team designed that asks people to articulate the thinking behind their beliefs and positions.

“And that actually, interestingly, seems to moderate their policy position in the process,” Tsai said. “So there are absolutely examples of ways in which AI can have positive impacts on democracy. But it really is about designing with the right principles and evaluating them rigorously.”

A new chip developed by MIT researchers could help tiny, low-power UAVs avoid obstacles as they zip around tight corners inside an industrial HVAC system to check for gas leaks.

The chip allows small autonomous robots and other battery-limited devices to construct detailed 3D maps of their environments in real-time using only about as much power as a single LED. A robot could use such a map to plan a collision-free path to reach its goal.

Typically, generating such thorough maps requires power-hungry systems and a great deal of memory to build and store 3D representations of the obstacles in a robot’s environment.

The MIT researchers took a different approach by combining an extremely efficient mapping algorithm with specialized hardware designed to accelerate its workload, which minimizes memory and power consumption. 

This system-on-a-chip consumes only about 6 milliwatts of power, a fraction of the power required by other systems. 

This low-power operation could also make the chip well-suited for lightweight augmented reality headsets that can be worn for extended periods, for applications like educational medical simulation or detailed repair and assembly work.

“This paper showcases a key example of how you can leverage co-design of the algorithm and hardware to really push energy efficiency. While there has been a lot of work looking into compact 3D maps, what stands out about this work is that it also ensures that the process to generate those maps is as efficient as possible. Our chip allows you to store very large maps in a very small space, and do it in a very energy efficient manner,” says Vivienne Sze, a professor in the Department of Electrical Engineering and Computer Science (EECS), a member of the Research Laboratory of Electronics (RLE), and senior author of a paper on the chip.

She is joined on the paper by co-lead authors and MIT graduate students Zih-Sing Fu and Peter Zhi Xuan Li as well as Sertac Karaman, a professor of aeronautics and astronautics and the director of LIDS. The work was recently presented at the IEEE Very Large-Scale Integrated Circuits Symposium.

A more compact map

For a robot, generating a 3D map that includes the obstacles in its environment usually demands a lot of power because it must store images captured by its camera, and process all the 3D pixels in each image multiple times.

Instead of representing the environment using 3D pixels, which are cubes called voxels, the MIT researchers utilized a technique that maps the obstacles in space using ellipsoid blobs called Gaussians. 

The size, shape, and thickness of these ellipsoids can be smoothly adapted, so they match the shape of curved objects more efficiently than if one uses rigid, cube-shaped voxels. 

Importantly, the map captures the obstacles and free space around the robot, and together these let the robot plan a safe, collision-free path. Mapping obstacles and free space with voxels typically consumes a lot of memory, which makes traditional methods power-hungry. Because Gaussians can flexibly fit the geometry, a single elongated ellipsoid can represent a region that would take many voxels, so occupied surfaces and free space are captured far more compactly.

For their new system-on-a-chip, called Gleanmer, the researchers employed an algorithm their lab developed called GMMap that efficiently generates a 3D map of the robot’s environment using Gaussians to represent obstacles. 

With traditional approaches, a robot would need to load and process each depth image several times to adjust the size and shape of the ellipsoids. The system would usually construct Gaussians by comparing all the pixels in an image to each other. But the amount of memory and power needed to do this remains too high for many edge devices.

To solve this problem, the MIT researchers invented a technique that can generate highly accurate Gaussians from depth images with only one pass, after which they can discard the images, so the chip never has to store an entire image at once. 

Instead of comparing each pixel to every other pixel in the 3D image, their algorithm assumes that nearby pixels belong in the same Gaussian, so it only needs to compare each pixel to its neighbors.

“At any point in time, we only need to store a few pixels in memory, which significantly reduces the memory footprint our algorithm requires,” Li says.

Leveraging co-design

But as the robot moves through the space, it usually sees the same object from different viewpoints. When it generates Gaussians, some will overlap because they represent the same object. This can make the 3D map too large to store on an edge device.

Fusing overlapping Gaussians makes the map more compact, but doing so typically requires the algorithm to process many raw pixels stored in memory. The researchers developed a novel technique to perform this fusion process directly on overlapping Gaussians, without needing to revisit the original pixels. Since Gaussians are more compact than pixels, this significantly reduces memory and power requirements.

The same principle runs through their algorithm — most computations operate directly on compact Gaussians rather than the original pixels, enabling energy efficiency.

The researchers exploit this principle to design a chip that keeps the Gaussians it is actively working on within small, fast on-chip memory right beside the computational units. This is only possible because the Gaussian map is so compact.

The Gaussians the robot needs to work on next are waiting in the on-chip memory units, so they don’t need to be fetched from more distant, power-hungry, off-chip storage. 

“By having a dedicated memory that just stores the objects you’ve seen in the previous few frames, you can access the data much more efficiently,” Fu explains.

They tested the system-on-a-chip by reconstructing a range of diverse, pre-existing 3D environments. The chip can also reconstruct obstacles and free space directly from live data streamed from an iPhone camera.

Gleanmer generated detailed 3D maps in real-time while consuming about 6 milliwatts of power. It required only about 2.5 percent of the power that the best existing chip for map construction would need. 

By reusing compact Gaussians along the path as it plans, the chip lets a robot chart a safe trajectory using only about 20 percent of the energy it would otherwise need.

“We reduce the memory consumption by making sure the algorithm is efficient. Then we accelerate the workload that is performed by that efficient algorithm, so in the end, our chip is as efficient as possible,” Li says.

The researchers plan to further improve energy efficiency by moving the processing units on the chip closer to the sensors that gather environmental data. They could also explore additional applications, such as the use of Gaussians to represent schematics. This could help AI systems reason about complex blueprints more efficiently.

“Real-time 3D mapping has been the missing piece for small autonomous systems. A drone inspecting a pipeline or a pair of AR glasses navigating a room both need to understand the space around them — instantly, continuously, and at almost no power cost. Gleanmer makes that possible for the first time in a chip you can hold between your fingers,” says Karaman.

This work is supported, in part, by the MIT-MathWorks Fellowship, Amazon, the U.S. National Science Foundation, and Intel. 

Early mornings in the halls of Building 68 feature the sounds of rolling wheels on big metal carts, the rattling of glassware, the whooshing of faucets, and the clanking of autoclaves. 

These aren’t the sounds of researchers at work, but rather those of keeping the labs sterilized and stocked with the sundries of research: pipette tips, test tubes, flasks, petri dishes, and more.

Orchestrating this sunrise cacophony and the staff that undertakes it is Karen O’Leary, lab associate and acting supervisor in the Glassware Sterilization Facility, also known as the “kitchen.” 

Thanks, in part, to O’Leary’s proactivity and hard work, the kitchen staff were recently recognized with an MIT Excellence Award in 2025 for exceptional contributions in service of the community. 

“My goal is to get the scientists everything they need to do their research,” O’Leary says. “I’m good at what I do.” 

O’Leary admits she did not always possess such confidence. In almost 40 years at MIT, O’Leary has grown into this critical role for the department, and the department itself has evolved, moving into a brand-new building and away from previously standard practices like submerging equipment in acid for sterilization. 

From rookie to running the show

On Sept. 7, 1987, Karen O’Leary joined the MIT community as a staff member for the first time. The 18-year-old was fresh from vocational high school, where she studied cosmetology but felt too shy to pursue that as a career. She was also nervous about joining a research institution.

“When I started, I didn’t even know what a beaker was,” she recalls. 

Too embarrassed to admit in her interview that she couldn’t remember her brand-new home phone number, “I just made one up.” Fortunately, this didn’t prevent her from getting the job, where she worked under the mentorship of Thelma Watkins, who would retire in 1996 after 21 years at MIT. Watkins was critical for instilling a good work ethic and boosting O’Leary’s confidence. 

“She taught me to show up every day, and work hard, and laugh,” O’Leary says.

Even now, O’Leary continues to bring joy to that daily diligence, for herself and for her staff.

“Karen is always on top of things,” says longtime friend and fellow Lab Associate AnnMarie Budhai. “She doesn’t refuse work and always goes above and beyond.” 

Facilities and Operations Manager Cesar Duarte says that O’Leary’s long tenure, support, and knowledge have been invaluable as he transitioned into his role in Building 68 starting in 2023.

“Karen is one of those people who makes everything around her run more smoothly and more pleasantly,” Duarte says. 

Better, faster, safer

Although some might consider it drudgery, O’Leary says that washing glassware is her favorite task. 

“I like that when I wash, I can see the job is complete at the end of the day,” she says. 

Although washing glassware is a perennial task, safety and efficiency have come a long way in the past 38 years. More-effective autoclaves and dishwashers have eliminated steps like steaming to dissolve agar solvents before autoclaving, and scrubbing individual test tubes before washing.

O’Leary was working for the department in 2011 when Building 68 piloted a new approach to MIT’s management of regulated medical waste (RMW), such as petri dishes, blood, and needles — the new system, which is cheaper and produces less waste, is now used by all departments at MIT that produce RMW.

“EHS [the Environment, Health and Safety Office] has come really far — I’m glad we got away from acid,” O’Leary notes of the bygone era of submerging glass pipettes for sterilization. “Back then, no one knew of a better way.” 

Other tasks include cleaning velvets, which are used for replicating bacterial colonies on petri dishes, and pouring agar plates. 

“Everyone knows how to do almost every job, so we can take turns doing different tasks,” O’Leary says. “If you get sick, there’s always someone to cover.”

All in the family

For O’Leary, kinship with MIT has spanned generations. O’Leary was raised in Weymouth, Massachusetts, by a father who worked at MIT as a supervisor in the sheet metal shop. Having raised children of her own, now grown, O’Leary came to greatly appreciate the flexibility her job has granted her.

“I’ve had great work-family balance here,” she says. Even though she’s often at work more than an hour before the researchers that the kitchen serves, “The hours are great, and with MIT Health right across the street, it was easy to take everyone to doctors’ appointments.” 

She’s also gained a chosen family at MIT, spending breaks at work taking long walks along the Charles River, “talking about anything and everything” with colleagues like Budhai and Lab Aide Janet Katin. 

“We really grew up together,” she says. 

Working at MIT has provided O’Leary with support and community, and she’d like to pay it forward. In addition to strolling with colleagues, she hits the gym to help maintain the energy required for her highly active work. 

“I don’t like sitting around,” she says.

In addition to maintaining her stamina at work, she hopes that taking care of herself will keep her actively involved if she ever has grandchildren, and enable her to help neighborhood kids when she someday retires.

“I owe a lot to MIT,” she says. “I have been allowed to work hard and get satisfaction and have been appreciated and given space to care for my family.”

O’Leary returns this care to the Department of Biology in spades.

“It’s an understatement to say that Biology is lucky to have her,” says Duarte. “Karen’s overflowing energy, attention to detail, and care for the Biology research community are nothing short of amazing.”

Companies working at the frontier of aerospace, energy, and computing are constantly looking for new materials to improve performance. But in order to understand how those materials will actually behave once they’re inside rockets or on computer chips, companies first have to make the material and then test it. That’s because even the most powerful simulation techniques struggle to model the complex chemical arrangements in most of today’s solid materials. The problem adds costs and time to materials innovation.

Now a team of MIT researchers has created a way to accurately model the behavior of metals, regardless of the complexity of their chemical arrangement. At the center of the approach are machine-learning models that make simulations of materials faster and more accurate. The researchers improved those models by building training datasets that capture the diversity of atomic environments in chemically disordered materials.

In a new paper in Sciences Advances, the researchers showed their approach could be used to accurately predict material properties for a diverse group of metal alloys under a range of conditions. They also showed how the approach could be used to develop new materials, especially in scenarios where experimentation is expensive.

“The focus of the paper is metallic alloys, which is the field I work in, but this could be adapted to other types of materials, like semiconductors,” says senior author Rodrigo Freitas, MIT’s TDK Career Development Professor in Materials Science and Engineering. “This is not specific to any one application — you could use this approach to create new sustainable steels, new materials for aerospace, and more. That’s what makes this exciting.”

Joining Freitas on the paper are first author Killian Sheriff PhD ’26; MIT PhD students Daniel Xiao and Yifan Cao; and University of Sheffield Senior Lecturer Lewis R. Owen.

Modeling metals

Material properties are mostly determined by the internal arrangement of their chemical elements. Even if two materials have the same mix of chemical elements, different chemical arrangements can make the difference between a brittle material and one that deforms without breaking.

Capturing that distinction requires simulating materials atom by atom. To do that, researchers rely on models that describe how atoms interact with each other. Over the last two decades, machine learning has become the most accurate way to build those models. Such models work well when the chemical arrangements inside materials follow highly ordered patterns, but that’s not the case with most solid materials, whose atomic chemical arrangements are disordered and vary from one region to another.

“The real challenge in our field is modelling these chemically disordered phases,” Freitas says. “Chemical disorder means there’s a huge variety of local chemical environments, which is hard for the machine-learning model to learn. This is a problem because every single metal we use in practice is chemically disordered.”

The problem comes down to a lack of representative training data for those atom-by-atom simulations. The current leading approach for creating such data works by brute force, often requiring more than 100,000 hours of computation to create the training data for a single material. Even then, it does not transfer well when researchers change the material’s composition.

In previous work, Freitas’ group had developed a way to measure the chemical complexity of solid materials by analyzing the frequency and spacing of tiny groups of atoms. For this study, the researchers used that capability to build better training datasets. They used a mathematical approach known as information theory to generate training datasets that capture a wider variety of local chemical environments inside disordered materials. The method works by swapping out atoms from samples to reduce repetition and expose the model to chemical environments it might otherwise miss.

“We kept optimizing the training set so it captured as many different local environments as possible,” Freitas says. “If the same kind of environment showed up many times, we replaced redundant examples with ones the model hadn’t seen before. That makes the training set much more informative because each example adds something new.”

When trained on the researchers’ datasets, the models predicted material properties more accurately than models trained using random sampling or another popular sampling method.

“The starting point for all these atom-by-atom simulations is: Are you able to accurately describe the chemical bond between atoms?” Freitas explains. “If not, it can still teach you about materials in general, but it doesn’t tell you what will happen to specific materials in the real world. This approach makes the simulations high fidelity in terms of their chemistry, to better reflect what’s happening to materials.”

The researchers applied their technique to create machine-learning training datasets for a group of chemically diverse metal alloys. Using a set of machine-learning models, they showed the models trained on their datasets are more accurate than much larger models created by companies like Google and Microsoft.

“We got to a point where we were convinced it worked without using these expensive brute-force methods,” Freitas says. “I told Killian, ‘This is a good paper. But if you can show that simulations with these models can now accurately predict useful materials properties, then it becomes a very good paper.’ Killian took that to heart and tested this as widely as he could.”

Sheriff worked with Xiao and Cao to test the approach across different alloys and properties. The team also drew on Owen’s experimental data to compare the simulations against real measurements of atomic ordering in alloys.

From the lab to industry

The method works, in part, by capturing hidden patterns in the sample data. The researchers describe the patterns in the paper as “subtle energetic biases toward certain local chemical configurations.”

Those small energetic differences matter because they determine which phases form in an alloy, how those phases change with temperature and composition, and ultimately which properties the material will have. As one test, Daniel Xiao led simulations showing that the team’s models could predict phase diagrams that closely matched experimental data. Phase diagrams map which phases are stable across different temperatures and chemical compositions, and they are a central tool for designing and processing alloys.

“Phase diagrams are one of the main ways people connect materials modeling to real processing decisions,” Freitas says. “If you are welding, casting, or heat-treating an alloy, you need to know which phases are likely to form under different conditions. Our goal is to make these kinds of predictions accurate enough, and accessible enough, that they become part of how people design materials.”

The researchers are now using the approach to study how changing an alloy’s composition affects mechanical properties and radiation tolerance, with the goal of designing materials that remain strong and damage-tolerant in harsh environments. They are also working to make the method easier to use with the kinds of tools and workflows materials engineers already rely on.

“Industry isn’t going to change the way they do things if what you’re creating doesn’t fit into their existing operating procedures,” Freitas says. “The goal is to make these predictions useful in the places where materials decisions are actually made.”

The research was supported by the U.S. Air Force Office of Scientific Research.

On June 9, The Boston Globe released its 2026 “Tech Power Players” list, recognizing 50 influential local leaders in technology and business across Massachusetts. The list includes eight MIT affiliates including President Sally Kornbluth, Prof. Daniela Rus (director of CSAIL), Prof. Regina Barzilay, Prof. Yet-Ming Chiang, Prof. Max Tegmark, Ana Bakshi (executive director of the Martin Trust Center for MIT Entrepreneurship), Katie Rae CEO and Managing Partner of Engine Ventures), and Senior Lecturer Brian Halligan, along with a number of MIT alumni.

In addition to recognizing individual leaders, the Power Players coverage highlights MIT’s research labs, its culture of innovation and entrepreneurship, industry connections, new AI initiatives, and the Institute’s deep commitment to maintaining Massachusetts’ technological leadership.

“Massachusetts can absolutely lead in this next wave,” says President Kornbluth, noting that the future is bright with burgeoning opportunities to advance technologies in fields from manufacturing, life and health sciences to quantum technologies and energy in service of Americans across the country.

Advancing AI and entrepreneurship 

When it comes to AI, MIT is “working to drive artificial intelligence forward in sectors where the region is strongest, from biotechnology and robotics to defense and clean energy. It’s also trying to broaden entrepreneurship through a ‘dorm-to-startup’ push, creating a pipeline of support services — from hack-a-thons to venture funding — to help students to start companies between classes,” writes Robert Weisman for The Globe. 

Looking ahead, The Globe highlights how MIT aims to remain a central driver of AI advancement within higher ed. 

“President Sally Kornbluth is reinvigorating the school’s support of the local innovation ecosystem,” writes Aaron Pressman, noting how MIT is “unveiling new online classes dedicated to AI — with free entry-level classes for anyone — and encouraging more entrepreneurship on campus.”

MIT’s free, online AI courses could help local tech leaders in their challenge “to ensure people, not only corporations, benefit from the technology,” writes Pressman.

And when it comes to applying AI technologies to real-world problems, MIT aims to ensure the greater Boston area remains a leader.

“Some schools in Massachusetts, including MIT, are carving out a specialty in applied AI — sometimes called ‘AI+X’ — deploying the technology to help businesses, hospitals, and research institutions to supercharge productivity, innovation, and scientific breakthroughs,” explains Weisman.

Aman Narang ‘04, CEO of Toast, adds: “The superpower has always been the university system. The best thing Boston can do is keep these people around.”

MIT startups are a key driver of the region’s entrepreneurial ecosystem. To ensure the greater Boston area remains a hub for innovators and to respond to growing student interest, MIT is looking to build upon its existing entrepreneurship resources for students, including the more than 150 courses and 85 centers and programs dedicated to fostering an entrepreneurial community. Additionally, President Sally Kornbluth and Provost Anantha Chandrakasan recently formed the Committee on Accelerating Translation and Entrepreneurship (CATE) to explore anew how the Institute can best support, remove barriers to, and accelerate the movement of ideas from MIT’s research and innovative discoveries into new ventures. 

Further, reflecting on the optimism surrounding the Greater Boston tech scene, The Globe describes how applications for The Martin Trust Center for MIT Entrepreneurship’s startup accelerator program have doubled from last year, and nearly one-fifth of MIT undergraduates — about 800 students — attended a recent startup career fair.

Innovating change beyond MIT

The simple worm could drive the future of AI. This might sound like a squishy premise, but that’s the idea behind MIT startup Liquid AI, which is developing AI models inspired by the brain structure of a simple worm and could significantly reduce AI energy consumption. Liquid AI’s models, “which can uncover financial fraud and pilot autonomous drones, require far less electricity to operate than large language models, saving energy and water, which is used to cool data centers,” Pressman explains.

The Globe highlights how Liquid AI recently signed a deal with Mercedes-Benz to incorporate its technology into the onboard systems of cars sold in North America.

To power new AI technologies – and ensure Americans across the country can have reliable and affordable energy sources – researchers at MIT and a number of alumni are also turning their attention to the future of energy. 

In Prof. Yet-Ming Chiang’s lab, researchers are developing batteries that can store more electricity over longer periods, creating “more opportunities for wind, solar, and other clean energy sources.”

Weisman highlights how “Chiang’s lab and other MIT research centers are also working on innovations in microchips, critical minerals, fusion technology, and defense tech. All are examples of ‘tough tech’ projects combining science and engineering, which Chiang says ‘are in the sweet spot of the Boston ecosystem.’“

Soon, 80 MIT students will work as summer interns and employees at GE Vernova, thanks to the MIT-GE Vernova Climate and Energy Alliance, a collaboration aimed at advancing research and education that will accelerate the global energy transition.

GE Vernova CEO Scott Strazik wanted his organization to “plug into the city’s innovation culture,” particularly the MIT campus and community. The company announced it would dedicate $50 million over five years to fund internships and research projects in which students and faculty work alongside GE Vernova engineers and technicians.

The most promising area for the Greater Boston tech scene

The Globe concludes by asking each Power Player what the most promising thing about the Greater Boston tech scene is right now.

For Rus, the answer is: “talent. Boston has the best AI researchers in the world, and they're producing genuinely new ideas, not incremental ones,” she explains. 

When it comes to realizing the potential of fusion energy, Bob Mumgaard SM ’15, co-founder and CEO of Commonwealth Fusion Systems, explains that he couldn’t have built the company anywhere but Massachusetts thanks to the region’s expertise in engineering, designing, and manufacturing hardware and equipment and access to university researchers.

“The ecosystem has the building blocks,” says Mumgaard. “Massachusetts is the strongest in the nation in innovation in energy.”

President Kornbluth points to quantum.

“There isn’t a more important technological field right now than quantum science and technology, and the Boston area has the greatest concentration of quantum talent anywhere in the world,” Kornbluth emphasizes.

In the small coastal town of Prince Rupert, British Columbia, the port is the backbone of the community.

Growing up there, with a father who works as a longshoreman, Chelsea Mitchell witnessed the port’s importance firsthand. From an early age, she understood that the port was essential to the transportation of goods in and out of not only Prince Rupert but all of British Columbia’s North Coast. Disruptions to port operations could have ripple effects reaching from dockworkers’ families to the regional economy and beyond. 

“The port is central to my hometown’s economy,” Mitchell says. “Having family in the industry gave me visibility into the complexity and the volatility of the shipping industry.”

Today, that industry and the forces that shape it are the subject of Michell’s research as a fourth-year PhD student in MIT’s Department of Economics. She studies how ports and shipping companies compete, how goods move through congested terminals, and how disruptions affect global supply chains.

“When I was younger, I never would have imagined I would get to conduct research at MIT,” Mitchell says. “Prince Rupert is largely a blue-collar town, so I had minimal insight into the world of academic research growing up. But in high school I realized I thrived in an academic environment, especially studying math, and hoped one day I could pursue a PhD.”

She left British Columbia to attend the University of Toronto, where she studied math and economics. There, faculty mentors introduced her to economic research and encouraged her to apply to doctoral programs, eventually leading her to the Institute.

“I was lucky to have mentors in college who encouraged me to apply to MIT. The level of support and quality of advising here has consistently amazed me,” Mitchell says.

Her research focus became clearer in 2023, when longshore workers along Canada’s West Coast walked off the job during a labor dispute centered, in part, on automation and its effect on port employment. The strike lasted roughly two weeks and shut down 35 terminals across the province. That experience left a lasting impression on Mitchell.

“These labor disruptions made me acutely aware that ports were a choke point in our supply chains,” Mitchell says. “They seemed understudied relative to how important they are.”

Because of her family’s ties to the industry, Mitchell was able to spend time speaking not only with her father’s co-workers who were involved in the strike but also with people working throughout the shipping industry. 

One of her first major projects examined labor negotiations and competition among American ports. She found that even just the possibility of work disruptions in ports could alter shipping patterns, prompting companies to reroute cargo away from West Coast ports and toward East Coast facilities despite added logistical cost.

Her current work focuses on another major shift in the industry: the growing number of shipping companies that own container terminals.

Traditionally, carriers relied on independent terminal operators to load and unload cargo. Increasingly, however, major shipping lines have begun acquiring terminals themselves. Using detailed vessel-tracking and port-call data, Mitchell studies what happens after those acquisitions occur.

Her findings suggest that ships operated by the acquiring carrier often receive faster service, particularly during periods of congestion when terminal capacity is limited. Competing carriers, meanwhile, face longer wait times and are more likely to divert cargo to other terminals.

“Ports are notoriously capacity constrained, but all carriers need access to them,” Mitchell says. “A central question is what advantages these acquisitions create and whether they affect competition.”

More broadly, Mitchell hopes her work highlights the importance of an industry that has often gone unnoticed by consumers. Approximately 80 percent of global trade moves by sea, making ports essential infrastructure for the modern economy.

“People have become increasingly aware of the shipping industry, but we can’t ship goods without functioning ports,” she says. “We want ports to be reliable and efficient so that supply chains function and goods can remain affordable.”

Mitchell credits her advisors, Nancy Rose and Tobias Salz, with helping her navigate her research, especially through difficult obstacles. More broadly, she says the people she has met at MIT have been the most rewarding part of her experience thus far.

Outside of economics, Mitchell enjoys exercising, skiing, reading, and spending time with friends. She finds that having a work-life balance is essential to her success as a researcher.

“Research is extremely challenging,” Mitchell says. “You invest a lot of time trying to answer questions that you don’t necessarily know are answerable given the data you have. It’s important to have rewarding aspects of your life outside of research that can help keep you motivated.”

Still, whether she is analyzing data in Cambridge, Massachusetts, or returning home to the rugged coastline of northern British Columbia, Mitchell takes a people-first approach to her research.

“I see numbers. I see data. But it’s challenging to tell a story with that data when you don’t have insights from the people who are actually doing the work,” Mitchell says. “Talking to people in the industry has been fundamental to understanding what’s really happening.”

MIT has again been named the world’s top university by the QS World University Rankings, which were announced today. This is the 15th year in a row MIT has received this distinction.

The full 2027 edition of the rankings — published by Quacquarelli Symonds, an organization specializing in education and study abroad — can be found at TopUniversities.com. The QS rankings are based on factors including academic reputation, employer reputation, citations per faculty, student-to-faculty ratio, proportion of international faculty, and proportion of international students. 

MIT was also ranked the world’s top university in 12 of the subject areas ranked by QS, as announced in March of this year. 

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

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

Susan Solomon, the Lee and Geraldine Professor of Environmental Studies at MIT, has been named the 2026 Tang Prize Laureate in Sustainable Development for “groundbreaking advances and leadership in atmospheric and climate sciences that shaped global policy for Sustainable Development,” according to the Tang Prize Foundation.

The Tang Prize is a biennial international award granted by judges convened by Academia Sinica, Taiwan’s top academic research institution, and recognizes four fields of research: sustainable development, biopharmaceutical science, sinology, and rule of law.

“The Tang Prize is one of the most prestigious awards in environmental science, and it’s flooring to anyone to learn that they received it,” says Solomon, who holds joint appointments in the MIT departments of Chemistry and Earth, Atmospheric and Planetary Sciences (EAPS). “It’s a tremendous, tremendous honor, and I’ll try to live up to it.”

Solomon began her career at the National Oceanic and Atmospheric Administration. In 1985, scientists discovered an unexpected “hole” in the ozone layer of the atmosphere above Antarctica. Ozone, a gas made of three oxygen atoms, helps filter out ultraviolet radiation from the sun that would otherwise damage living organisms, with impacts such as increasing rates of skin cancer and cataracts. The following year Solomon, then 30, published a paper proposing a novel chemical mechanism that might explain the mysterious hole. In the same year, she led a team of 16 scientists to take direct measurements of the degradation of the ozone layer, as the only woman in the expedition. Their findings were the first measurements to show that chlorofluorocarbons (CFCs), compounds used in common items such as aerosols and cooling systems, were indeed destroying ozone in the stratosphere. 

“Maybe it’s just being young and naive, or maybe it’s being open to new ideas, but at that stage in my life I was open to the idea that chemistry might be completely different from what we had thought. I came up with some ideas of how to explain it that turned out to be right, remarkably,” she says.

The following year, a United Nations conference signed the Montreal Protocol, with all nations agreeing to phase out the use of CFCs and resulting in one of the most successful triumphs of international climate policy to date.

“The ozone story is a fantastic one, because it teaches us that we can actually develop international agreements and get all different kinds of countries, developed and developing, to agree to them and to solve problems together,” she says.

From 2002 to 2008, she co-led the production of the Intergovernmental Panel on Climate Change Fourth Assessment Report, synthesizing climate science knowledge and assessing effects and mitigation approaches to human-caused climate change. It was later recognized with a Nobel Peace Prize.

Solomon then went on to study the impacts of human-made carbon dioxide (CO2) emissions on the Earth’s climate. Her groundbreaking research showed that human emissions of CO2 were causing impacts on the climate that would be irreversible for 1,000 years, even after emissions stopped. In 2012 she joined the faculty of EAPS, where she has continued her work on studying the ozone layer. Recently, she has found the first quantitative proof that the ozone layer is on track to recover by around 2035.

“Most of the awards I’ve gotten previously have been very focused on the science that I did, but this one embraces the fact that my work has benefit for the planet’s sustainability,” she says. “People recognize that my work did something valuable. That is an incredible, humbling, and remarkable feeling.”

“Susan is a model of an engaged scientist,” says David McGee, the William R. Kenan, Jr. Professor of Earth and Planetary Sciences at MIT and EAPS department head. “From uncovering the mechanisms by which human activities affect the ozone layer to using that understanding to guide political action to, most recently, showing that our actions have produced measurable ozone recovery, her work and leadership have deeply impacted the field and the health of our society. Her mentoring and teaching have similarly impacted students and researchers across EAPS and MIT. This award is a wonderful celebration of her remarkable achievements.”

“Susan is a pioneer of atmospheric chemistry,” says Class of 1942 Professor of Chemistry and Department Head Matthew D. Shoulders. “Her groundbreaking research at the intersection of chemistry and environmental science is critically important, and it is wonderful to see her dedication, creativity, and scientific leadership recognized in this way.”

“I have been absolutely blessed by the students and colleagues that I’ve had over the years,” Solomon says, including collaborators Qiang Fu, Rolando Garcia, Douglas Kinnison, Ben Santer, and David Thompson, as well as MIT research scientists Kane Stone and Diane Ivy and former students, including Megan Lickley and Peidong Wang.

Founded in 2012 by the late Samuel Yin, the Tang Prize Foundation is a nongovernmental, nonprofit educational foundation. Nomination and selection of laureates is conducted by the Academia Sinica. Each award cycle, the academy convenes four autonomous selection committees, each consisting of an assembly of international experts, until a consensus on the recipients is reached. Recipients are chosen on the basis of the originality of their work along with their contributions to society, irrespective of nationality, ethnicity, gender, and political affiliation. Recipients in each Tang Prize category receive a total of approximately $1.6 million and a grant of approximately $320,000.

Solomon is the second MIT faculty member to receive the award after Feng Zhang, who won the award in Biopharmaceutical Science in 2016 for his role in developing the CRISPR-Cas9 gene-editing system.

Since 2021, the MIT Environmental Solutions Journalism Fellowship has supported local and regional journalists in reporting high-impact news stories that connect climate change with local priorities. 

Now, the MIT Climate Project has published a report on the reach and impact of these fellowships, highlighting how the Institute’s scientific resources can help spark and deepen conversations about climate solutions in every corner of the country.

“Our goal is to offer trusted, grounded knowledge about climate change to everyone who wants to learn, so communities can make informed decisions for themselves about how to respond,” says Aaron Krol, who leads the Climate Change Engagement Program within the Climate Project. “Often, the best way to do that is just to lend support and scientific guidance to the people, like the reporters at local papers and radio stations, who know their audiences’ needs and perspectives best.”

Since the fellowship was founded, 20 journalists have completed the program, publishing 104 stories with a collective audience of nearly 3 million readers and listeners. Among the goals of the fellowship is to ensure that ambitious, long-form or serial climate reporting is not restricted to the large national outlets that can afford to maintain a climate desk. Americans consistently say they trust their local newsrooms more than national ones, and feel local news is an important institution in their cities and towns — making these news sources especially powerful media for introducing new ideas and perspectives on climate change and its solutions. 

MIT journalism fellows have covered the potential for offshore wind energy in Louisiana, flood preparedness in West Virginia, and the energy transition in Utah’s coal country, among many other topics with clear stakes for readers and their communities.

“Local journalists want to engage on climate issues,” says Krol. “Every year, we’re amazed by the quality of the applications we receive. There are so many reporters out there who know this is important, who have been holding onto ideas for stories, and just need that extra support to step outside their usual beats or devote the time and resources to these issues.”

The 20 outlets that have participated in the fellowship showcase the full variety of local news media in the United States today. Some are long-standing institutions in their cities and states, while others are recent startups trying out new, nonprofit models for local journalism in the 21st century. Some publish in print, some are online-only, and some report on the radio. Some have readerships in the hundreds of thousands, and others serve impactful niche audiences.

The most recent cohort of fellows, from 2025, exemplifies this range. At the Chicago Tribune, Karina Atkins reached hundreds of thousands of readers with her series on state and federal policies that have hampered Illinois farmers from diversifying their crops in preparation for a warming climate. Meanwhile, at Lancaster Farming, Carolyn Beans gave dairy farmers in Pennsylvania an in-depth look at the market for climate-smart milk.

“We don’t ask how big your audience is,” Krol says. “We ask who you’re going to reach, and how you’re going to connect climate change to their lives and livelihoods.”

MIT provides the fellows with editorial, scientific, design, and financial support. Fellows get a crash course in climate science from MIT experts, and work hands-on with interactive climate models to get new perspectives on policy and technology solutions. They also get access to a science editor who can supplement the work of the host newsroom with a specialized background in reporting and writing science-focused stories.

“The stories themselves are important, but I’m proudest of the difference our program has made for the careers of the journalists who have come through it,” says Krol. “We’ve had newsrooms dedicate more resources to following up on their climate stories, fellows pivot to energy and environment beats, outlets start using digital tools and data visualizations in new ways. We even had a fellow start her own newsroom to pursue more environmental and solutions reporting for Minnesota. Once these journalists get a chance to dig in on climate, they carry the knowledge and skills with them.”

Read the 2026 Impact Report to learn more about the MIT Environmental Solutions Journalism Fellows, and the impacts they made on communities across the country. All 100-plus stories published through the fellowship can be found on the MIT Climate Portal.

By harnessing the unique properties of quantum mechanics, scientists and engineers worldwide seek to enable systems with extraordinary capabilities. Many of them are working on the highly anticipated development of quantum computers capable of completing complex calculations at unprecedented speeds. These computers could meet the growing computational demands of both scientific research and data-intensive industries like finance, cybersecurity, and medicine.  

Necessary for quantum system development is an environment in which the fragile nature of quantum bits (qubits) is stabilized and the thermal noise (fluctuations in current/voltage) inherent in superconducting electronics is dampened. That environment requires cryogenic temperatures, those ranging from 5 to 10 millikelvins, colder than the extreme temperatures encountered in space. Dilution refrigerators create this needed cryogenic condition.

Dilution refrigerators used for quantum R&D need a wiring system that can operate in cryogenic temperatures, maintain a power-efficient direct current, and support high-speed data transmission. Researchers at MIT Lincoln Laboratory prototyped flexible, ribbon-like, low-frequency (LF) cables that not only meet these demands, but also are compatible with commercial circuit-board manufacturing processes. Maybell Quantum, a Colorado-based company supplying hardware for developing quantum systems, licensed the design for these cables and is adapting them for use in their dilution refrigerators.

"We’re planning to integrate Maybell LF CryoTrace, the ribbon wiring system transferred from MIT Lincoln Laboratory, across all thermal stages of our dilution refrigerators. Initially, the cables will be used for LF services, such as thermometry, heaters, and sensors, with feasibility studies planned for additional functions," says Lasse Nielsen, strategy and operations lead at Maybell Quantum. "After qualification testing, LF CryoTrace is planned for the next iteration of our internal wiring across the Maybell product family."

Motivation for invention

To support government initiatives in quantum computing, the Lincoln Laboratory research team investigated alternatives to conventional coaxial cables for use in hardware like dilution refrigerators. Coaxial cables can generate heavy heat loads for cryogenic hardware to address. And, as the number of qubits in quantum computers will increase, so will the number of coaxial cables in the infrastructure, making it difficult to fit stiff, bulky cable arrays into hardware supporting superconducting qubits.    

The team chose a stripline cable configuration with conductive layers positioned between flexible polymer layers that shield against electromagnetic interference (also known as crosstalk). Striplines offer consistency across different frequencies and minimal signal loss. The new cables were designed to accommodate large numbers of simultaneous signal transmissions; support direct-current operation without warming the cryogenic environment; and, importantly, provide easier integration into hardware than achievable with brittle coaxial cables.

"The main innovation is that the laboratory's cables can be fabricated by a traditional printed-circuit-board manufacturer. They're cheaper to fabricate and easier to install than traditional coaxial cables," says John Cummings, a principal investigator in the flexible cables project of the Lincoln Laboratory Quantum-Enabled Computation Group.

Citing ease of installation and durability as two factors making these cables attractive, Maybell Quantum says the ribbon format is mechanically robust, reducing handling-related breakages common with thin coaxials and improving repeatability in production. The supple flex cables allow assembly tasks that took days to complete to be done in a few hours.

"Over time, we think ribbonized, quantum-specific internal wiring can reshape manufacturing norms: faster and more consistent builds, easier field service, and more modular upgrades," Nielsen says.

Future outlook

Maybell Quantum is looking toward supporting quantum computing's transition from a laboratory-based capability to an industrial, commercially viable one. The huge gap between the current highly specialized quantum-laboratory environment and the robust infrastructure required for future industrial quantum computing lies in the hardware promoting the development of functional chips.

Maybell's mission is to develop reliable tools that commercial developers of quantum computers can use with ease and without the high costs and expert training associated with the equipment in today's quantum labs. The flex cables and Maybell's continued R&D into their capabilities and integration into various tools will foster a future infrastructure that could enable industry to scale manufacture of quantum computers to a level at which these powerful machines could cost-effectively find use in myriad enterprises.

"If you want to scale to hundreds of chips, you need interconnects that can handle more signals more reliably. That’s why the Lincoln Laboratory cables are so exciting for us — they enable true scalability," says Kyle Thompson, founder and chief technology officer of Maybell Quantum. "We believe this technology will materially improve our systems and strengthen the broader U.S. quantum ecosystem by moving federally funded innovation into American manufacturing."

From the icy expanse of the South Pole, John Della Costa, a researcher on the Background Imaging of Cosmic Extragalactic Polarization (BICEP) project, watches STS.042/8.225 (Einstein, Oppenheimer, Feynman: Physics in the 20th Century), a free online class from MIT Open Learning’s OpenCourseWare, as part of a weekly “Fysics Fridays” series he started with his team.

MIT Professor David Kaiser, who teaches the course, often receives thoughtful notes from remote learners, but says an email from Della Costa stood out.

“Hearing that John and his team are spending a part of their time with this course was just the best message to receive,” says Kaiser.

The BICEP collaboration uses a series of radio telescopes at the South Pole to study the cosmic microwave background — the oldest light, emitted about 380,000 years after the start of the universe. The team is looking for signs of primordial gravitational waves, which would help to support MIT Professor Alan Guth’s theory of cosmic inflation that explains the rapid early expansion of the universe.

“Inflation is really important in making sense of our observations of our universe,” says Della Costa. “We have yet to discover the evidence for inflation that definitively proves that it did happen, and BICEP’s main role here at the South Pole is to discover gravitational waves from the very early universe.”

Kaiser co-directs a research group on early-universe cosmology with Guth. He says he has colleagues who have worked as Antarctica winter-overs, and can appreciate the immense challenge of this work.

“It’s very exciting to see this important research flourishing,” says Kaiser. “It takes enormous effort and dedication.” 

Bringing Open Learning to the South Pole

Della Costa first discovered MIT OpenCourseWare, part of MIT Open Learning, as a graduate student at San Diego State University. At the time, the Covid-19 pandemic had altered his schedule and created more downtime to pursue additional independent learning. He was taking a nuclear physics course as part of his graduate program in astrophysics, and wanted to learn much more about the topic. A little bit of online research led to his discovery of class 22.01 (Introduction to Nuclear Engineering and Ionizing Radiation), taught by Professor Michael Short.

“I found the course so interesting, and I’ve been exploring OpenCourseWare ever since then,” says Della Costa.

Preparing to spend an entire year at the South Pole (from November 2025 to December 2026), he realized he would need a productive way to occupy his downtime and stay entertained while isolated from much of the world.

“The station is completely isolated. After a certain point, no planes can fly in because it’s too cold,” says Della Costa. “The station closed on February 14, and it will reopen at the end of October or early November, depending on the weather.”

Because internet access is so limited at the South Pole, he downloaded several courses ahead of time, including: STS.042/8.225, 8.02 (Physics II: Electricity and Magnetism), 8.03 (Physics III: Vibrations and Waves), and Guth’s course, 8.286 (The Early Universe).

Like Della Costa’s discovery of OpenCourseWare, STS.042/8.225 was rooted in the disruptive days of the Covid-19 pandemic. Kaiser had taught the course in its traditional, in-person format many times, until fall 2020, when the courses needed to be taught entirely remotely. He made slides and taught the course via Zoom — for synchronous and asynchronous learning — to approximately 100 students located throughout the world. The materials were initially posted on the course site. The online version was later refined and expanded, launching on OpenCourseWare in August 2022. Unlike many physics offerings, this course includes background readings by physicists, as well as historians, philosophers, and sociologists.

“In this course, we get to talk about some really amazing ideas from modern physics,” says Kaiser. “We start in the middle of the 19th century, still in an era of what we would now call classical physics, and we rapidly go through things like relativity, quantum theory, nuclear physics, and particle physics. We end up with some of my favorite material about cosmology and the Big Bang — the kinds of things that John and his team are actively working on right now from their perch at the South Pole.”

Building community and learning together

Beyond finding ways to stay occupied during downtime from his research, Della Costa realized the importance of engaging the 45-person community at the South Pole. He describes it as a tight-knit group that needs to work together and look out for one another, especially given the extreme isolation, cold, and darkness, which can take a serious toll on mental health during the winter months.

“It’s very important to have community activities here,” says Della Costa, who thought of the idea to launch the “Fysics Fridays” series a couple of months ago. 

The group gathers to watch lectures and documentaries about physics every Friday. The series kicked off with a documentary about atomic bombs, drawing strong interest from the very beginning. 

Della Costa realized that STS.042/8.225 would be an ideal offering for Fysics Fridays.

“I thought this would be a perfect lecture series for us to watch, because it’s fairly introductory,” says Della Costa. “Not everyone here is a physicist, actually. It’s widely accessible, but still meaty, and worth people’s time to watch.”

Team members have been very interested in watching the course, and they’ve also started doing experiments before watching the lectures. Della Costa says that they’ve done the double-slit experiment and plan to also make a cloud chamber to see cosmic rays going through it.

Now that Della Costa and Kaiser are in contact, Kaiser has made plans to provide a special Zoom colloquium for the community at the South Pole.

“This use of the course is especially inspiring,” says Kaiser. “It really speaks to the excellence and far reach of OpenCourseWare and Open Learning.”

An auto factory worker can remember the storage bin where she left a partly assembled component the night before, and quickly return to that spot to pick it up. But robots that may work side-by-side with her would struggle to develop and access this same type of “spatiotemporal” memory.

Now, MIT researchers have developed a long-term memory framework that allows robots to rapidly form and recall a detailed mental model of complicated, large-scale environments.

In the future, this advance could allow the factory worker to send a robotic assistant to fetch the item, simply by asking it to “go and grab the component we started assembling last night.”

This new method combines advanced map representations with rich descriptions of the environment that the robot gathers as it travels over a long period of time. The robot can quickly access this memory to answer complex queries about its environment in plain language.

This memory framework, which answers questions more accurately than state-of-the-art methods, runs fast enough for a mobile robot to use in real-time.

In addition to its potential uses in robotics, this method could have applications in augmented reality systems that aid maintenance workers in anomaly detection or assist commuters in wayfinding.

“If we want robots to work side-by-side with humans and interact better with humans, they must speak the same language. The robot must be able to reason about time and space the same way humans do. That is essentially what our method is doing. It is turning a traditional map into a language-based map that is easier for the robot to think about and access using language,” says Luca Carlone, an associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), principal investigator in the Laboratory for Information and Decision Systems (LIDS), and director of the MIT SPARK Laboratory.

He is joined on the paper by lead author Nicolas Gorlo, an MIT graduate student; and Lukas Schmid, a former research scientist at MIT and now professor at the University of Technology Nuremberg in Germany. The research was recently presented at the Conference on Computer Vision and Pattern Recognition (CVPR).

Spatiotemporal memory

Memory allows an artificial intelligence system, like a chatbot, to answer complex questions and reason about previous interactions with its user.

“We want to design a new type of memory, a spatiotemporal memory, that enables an AI-powered robot to remember real interactions and sensor observations. Like ChatGPT, but grounded in the real world and capable of answering any question about the environment, like ‘Where did I leave my wallet?’” Carlone says.

To develop such a memory framework, the MIT researchers bridged two lines of work: computer vision and robotic mapping.

Multimodal computer vision models can understand and richly describe the objects in a scene, but they often only process a single annotation at a time. On the other hand, robotic mapping frameworks create 3D maps of an environment, like an entire apartment or university campus, but usually lack detailed descriptions of objects or are computationally expensive.

The method the MIT researchers created, called Describe Anything, Anywhere, Anytime, at Any Moment (DAAAM), takes the best of both approaches.

Using DAAAM, as a robot traverses its environment, it attaches rich descriptions to objects it sees. For instance, the robot may note that a particular building on the MIT campus is called the Stata Center and is designed with a certain type of architecture, or that a bike rack holds five bicycles and the red one has a flat tire. 

It stores this detailed information in a 3D map-based representation that is arranged spatially, so objects will be grouped into separate regions. In this way, the robot can remember that the red bicycle with the flat tire is in the bike rack outside the Stata Center.

But existing techniques that capture such rich descriptions typically take a few seconds to annotate a few objects. This is too slow for real-time performance, since a robot might see hundreds of objects during a few minutes of exploration.

“The faster the robot can form this spatial memory, the more efficient it will be performing actions in the environment,” Carlone adds.

Streamlining the process

To speed things up, DAAAM aggregates nearby objects as it travels and uses an optimization method to select key frames to annotate. These are images with the clearest view of multiple objects, allowing the system to thoroughly describe several items in parallel, speeding up computation tenfold.

As the robot explores the space, it attaches each batch of annotations to multiple objects in a particular location on the 3D map.

“We annotate every object only once, so our framework can run in very large-scale environments in real time. And by clustering objects into regions, it can answer a wide range of queries about objects and locations in the environment,” Gorlo explains.

Once the system builds this spatial memory, it must retrieve information from an enormous database of objects and descriptions in an efficient manner. 

To enable this, the researchers used an LLM that calls on various tools, which can quickly retrieve specific information in a way that reduces hallucinations. This allows DAAAM to answer a user query accurately in only a few seconds. 

For instance, if one asks a robot about a certain sculpture it saw near an MIT campus building, DAAAM can use a semantic search tool to retrieve information based on the word “sculpture” or a different tool to retrieve information based on the location of the building.

When tested and compared with other methods, DAAAM was between 21 percent and 53 percent more accurate, depending on the question type. 

In the future, the researchers want to expand DAAAM so the system can capture significant events that happened in the environment. They are also working to incorporate confidence levels into the system’s responses.

“Ultimately, we want to have robots that can help with any sort of tasks. With this framework, we are trying to create the foundations to enable a generalist agent that can do anything you ask,” Gorlo says.

This research was funded, in part, by the U.S. Army Research Laboratory and the Office of Naval Research. Carlone is currently on sabbatical as an Amazon Scholar; this article describes work performed at MIT and is not associated with Amazon.

In May, the Initiative for New Manufacturing (INM) marked its first anniversary with MIT Manufacturing Week, four days of events that attracted more than 800 registrants including students, faculty, industry leaders, investors, entrepreneurs, and government officials to explore topics ranging from how companies are using AI on factory floors to the role of startups in introducing innovation to new workforce solutions to address the worker shortage.

“INM launched a year ago with the premise that strengthening the industrial base needed a coordinated response, and MIT has a responsibility to lead it,” says Paula T. Hammond, dean of MIT’s School of Engineering and co-chair of INM’s Steering Committee. “The response and participation level has been huge. MIT Manufacturing Week proved that the appetite for change — from students to chief executives — is real and urgent.”

The week opened with a cybersecurity workshop co-led by INM and Google Cloud for the initiative’s industry members. It continued with the MIT MIMO (Machine Intelligence for Manufacturing Operations) symposium focused on deploying artificial intelligence on factory floors, alongside discussions on workforce development, emerging technologies, startups, and industrial transformation. The week closed with a regional research showcase and competition that drew more than 140 graduate students and postdocs from across New England.

Over the past year, INM has also continued its distinguished speaker series featuring manufacturing leaders including Keith Flynn, senior vice president of manufacturing at Anduril; Roland Busch, president and CEO of Siemens; and Venky Alagirisamy, COO of Nike.

Inspiring a new generation of manufacturing startups

A central goal of INM is to help more students see manufacturing as a frontier for scientific discovery, technological innovation, entrepreneurship, and societal impact.

To support that effort, INM is launching and leading programs to help move early-stage ideas and new technologies from the lab to real-world development, and to catalyze new manufacturing companies. 

This year, INM partnered with NSF I-Corps New England, which helps researchers turn their startup ideas into companies, to host its first manufacturing research showcase. More than 140 teams from 17 universities across New England applied to participate. Forty finalist teams received mentorship on their ideas and advanced to the final competition, where eight teams shared $50,000 in prize funding.

The top prize in the category “most transformative innovation” went to MIT PhD student Jake Read for “The End of G Code,” a project focused on modular machine control architectures designed to accelerate the development of new manufacturing equipment and processes. Vatsal Patel from MIT and Joshua Grace from Yale University won the top prize in the research excellence category, for “VisFT,” scalable six-axis force-torque sensors.

Project themes presented by participating teams included AI tools for manufacturing, semiconductor manufacturing and process control, robotics and autonomous assembly, digital twins and simulation, new materials, additive manufacturing, next-generation shipbuilding, and biomanufacturing. 

“Entrepreneurship is a transformative pathway to take research to market, and to drive faster innovation and scale-up,” says John Hart, INM faculty co-director and head of MIT’s Department of Mechanical Engineering. “At INM’s inaugural research showcase, we had tremendous interest from universities across New England, along with enthusiastic participation from industry, investors, and experienced founders across the ecosystem. We are excited to build on this success and work toward a nationwide program and platform for entrepreneurship and translation in manufacturing.” 

The Cheng Wu Foundation supported the showcase. 

Growing industry membership

During MIT Manufacturing Week, First Solar became INM’s eighth industry member, joining Amgen, Autodesk, GE Vernova, Flex, PTC, Sanofi and Siemens. 

The growth of INM’s consortium reflects a broader recognition that the challenges facing modern manufacturing — from supply chain resilience to workforce development and industrial competitiveness — are too complex for any single sector or company to address alone. 

This reflects renewed interest in manufacturing at a moment when advances in artificial intelligence, robotics, energy systems, and advanced materials are transforming industrial production. INM provides a platform to convene and provide solutions.

INM’s industry consortium model brings industry, researchers, and educators together around shared manufacturing challenges, with a focus on emerging technologies, workforce transformation, and commercialization pathways. Members participate in workshops and working groups on topics including cybersecurity and digital twins, implementing automated systems, AI agents in regulatory environments, and AI and continuous innovation. INM helps them connect with students, meet with startups, and learn from one another.

“Our members see MIT as a partner that can help them both address today’s challenges and think far into the future,” says Rick Locke, dean of the MIT Sloan School of Management and co-chair of INM’s steering committee. “This kind of multi-industry engagement is unusual and powerful.”

A year of rapid progress

When MIT launched INM a year ago, the goal was to create stronger connections between research, industry, workforce development, and entrepreneurship — helping accelerate how new manufacturing technologies move from the laboratory into real-world development.

Since then, the initiative has expanded quickly across research, industry, workforce training, and student engagement. INM issued a call for proposals focused on artificial intelligence and automation, receiving an incredible response from faculty and researchers, and funding eight seed research projects. In June, the initiative plans to publish eight white papers as part of a broader study examining the future of manufacturing. 

During MIT’s Independent Activities Period (IAP) in January 2026, INM collaborated with NSF I-Corps to guide 13 early-stage teams through customer discovery as part of the I-Corps Spark program.

Workforce development has also been a major focus. This fall, MIT launched the Technologist Advanced Manufacturing Program (TechAMP), led by Principal Research Scientist John Liu, to create a new generation of shop floor leaders and drivers of productivity — becoming“‘technologists” — at six sites across New England, including three community colleges. 

“INM has the potential to transform the national manufacturing workforce,” says Liu. “It will require deep engagement between how people learn and lead, and how firms adopt new technologies and transform. We’re just getting started.” 

INM is now exploring a national rollout of TechAMP, along with expansion into areas including biomanufacturing and semiconductor manufacturing.

On campus, INM supported student engagements including an AI and automation lunch series that Professor Faez Ahmed and colleagues organized, and visited factories through its Factory Observatory program that Ben Armstrong and the MIT Industrial Performance Center led. This spring, students also founded MIT’s first manufacturing club, holding its launch event during MIT Manufacturing Week. “We’re thrilled students are taking the lead,” says Sloan associate professor and INM faculty co-director Karen Zheng. “It was really exciting to see a full room of 80-plus students across campus coming together for the kickoff event during the busiest final period of a semester. This speaks to the students’ enthusiasm.” 

An eye toward the long term

While maintaining a deep focus on strengthening domestic manufacturing, INM aims to have a global reach. For example, the initiative is collaborating with NAMTECH, a new education institute in Ahmedabad, India, where students are now taking an adaptation of MIT’s well-known “yo-yo course,” or 2.008 (Design and Manufacturing II), focused on the fundamentals of manufacturing processes.

Next year, INM plans to bring more manufacturing leaders to campus, offer additional programming for emerging entrepreneurs, graduate the first cohort of TechAMP students, bring TechAMP to new states, grow the consortium to include new industries, and deepen research into manufacturing productivity. 

“INM aims to be a catalyst for transforming manufacturing across the nation to drive innovation, economic growth, and new types of jobs,” says Chris Love, faculty co-director of INM. “MIT’s work on the PIE (Production in the Innovation Economy) study in 2013 highlighted the value of proximity between production and innovation. INM seeks to rekindle this relationship in manufacturing across the country.”