Daniel Kleppner, the Lester Wolfe Professor Emeritus of Physics at MIT whose work in experimental atomic physics made an immense mark on the field, died on June 16 at the age of 92, in Palo Alto, California.

Kleppner’s varied research examined the interactions of atoms with static electric and magnetic fields and radiation. His work included creating precision measurements with hydrogen masers, including the co-invention of the hydrogen maser atomic clock; his research into the physics of Rydberg atoms and cavity quantum electrodynamics; and his pioneering work in Bose-Einstein condensation (BEC).

Kleppner, who retired in 2003 after 37 years at MIT, was a highly literate and articulate scientist whose exacting research and communication skills helped set the direction of modern atomic, molecular, and optical (AMO) physics. From 1987 to 2000, he was associate director of the MIT Research Laboratory of Electronics (RLE), and served as interim director in 2001. He also co-founded the MIT-Harvard Center for Ultracold Atoms (CUA) in 2000, where he was co-director until 2006.

While he was never awarded a Nobel Prize, Kleppner's impact on the field of atomic physics and quantum optics, and his generous mentorship, enabled the Nobel achievements of many others. His patient and exacting pursuit of discovery led to basic research insights that led to major achievements. His extensive research into the tiny atom provided the fundamental knowledge necessary for the huge: the eventual development of groundbreaking technologies such as the global positioning system (GPS), magnetic resonance imaging (MRI), and quantum computing.

“He was a leader in the department, and a leader in the American Physical Society,” says Wolfgang Ketterle, the John D. MacArthur Professor of Physics at MIT and a 2001 Nobel laureate. “He was a statesman of science. He was this eloquent person, this master of words who could express things in memorable ways, and at the same time he has this sense of humility.”

“Dan Kleppner was a giant in the area of AMO physics, and in science more broadly,” says John Doyle PhD ’91, Harvard Quantum Initiative co-director and Kleppner advisee who helped Kleppner create the Bose-Einstein condensate from atomic hydrogen. “Perhaps his most impactful legacy is leading a culture of respect and supportive community actions that all scientists in the area of AMO physics enjoy today. Not only did his science lay the path for current research directions, his kindness, erudition, and commitment to community — and community service — are now ever-expanding waves that guide AMO physics. He was a mentor and friend to me."

Kleppner’s daughter Sofie Kleppner notes: “People who worked on early lasers never imagined we would be scanning groceries at the checkout counter. When they developed the hydrogen maser, they were a bunch of nerdy people who really wanted to understand Einstein’s theory of relativity. This was the basis for GPS, this is how our flights run on time. Our dad was convinced that basic research today could lead to all sorts of valuable things down the road.”

Early life and career

Born in Manhattan on Dec. 16, 1932, Kleppner was the son of Vienna native and advertising agency founder Otto Kleppner, who wrote the best-selling book “Advertising Procedure.” His mother, Beatrice (Taub) Kleppner, grew up in New Jersey and was a graduate of Barnard College. She helped with Otto’s manuscripts. Daniel Kleppner was the second of three siblings; his brother, the late Adam Kleppner, was a professor of mathematics at the University of Maryland, and his sister, Susan Folkman, was a research psychologist at the University of California at Berkeley.

“As a teenager, I just liked building things,” Kleppner once said. “And that turned out to be very useful when I went on to become an experimental physicist. I had a crystal radio, so I could listen to the radio over earphones. And the thought that the signals were just coming out of the atmosphere, I remember thinking: totally remarkable. And actually, I still do. In fact, the idea of the electromagnetic field, although it’s very well understood in physics, always seems like a miracle to me.”

In high school, he was inspired by his physics teacher, Arthur Hussey, who allowed Kleppner to work all hours in the labs. “There was one time when the whole school was having a pep rally, and I wasn’t that interested in cheering football, so I stayed up and worked in the lab, and the high school principal noticed that I was in there and called me in and gave me a dressing down for lack of school spirit.”

He didn’t care. Hussey talked with Kleppner about quantum mechanics, and “that sort of put a bee in my bonnet on that,” and taught him a little calculus. “In those years, physics was extremely fashionable. These were the post-war years, and physicists were considered heroes for having brought the war to conclusion with the atom bomb, and … the development of radar.”

He knew by then that he was “destined to spend a life in physics,” he said in a video interview for InfiniteMIT. “It was an easy era to become delighted by physics, and I was.”

Studying physics at Williams College, he was drawn to Albert Einstein’s theory of general relativity. He built a programmable machine that he called a forerunner of cybernetics. Williams also instilled in him a lifelong love of literature, and he almost became an English major. However, he didn’t appreciate what he called the school fraternities’ “playboy” and “anti-intellectual” atmosphere, and worked to graduate quickly within three years, in 1953.

He deferred his acceptance to Harvard University with a Fulbright Fellowship to Cambridge University, where he met the young physicist Kenneth Smith, whose research was with atomic beam resonance. Smith introduced him to the book “Nuclear Moments,” by Harvard professor Norman Ramsey, and presented a proposal by Ramsey’s advisor I.I. Rabi, who invented a technique that could make an atomic clock so precise “that you could see the effect of gravity on time that Einstein predicted,” said Kleppner.

“I found that utterly astonishing,” Kleppner noted. “The thought that gravity affects time: I had a hard time just visualizing that.”

When Kleppner wandered Harvard’s halls in 1955, he was excited to see a door with Ramsey’s name on it. He was interested in Ramsey’s research on molecular beam magnetic resonance, atomic clocks, and precision measurements. “Fortunately, I came along at a time when he had an opening in his research group,” Kleppner recalled.

A new atomic clock

As Kleppner’s advisor, Ramsey encouraged him to create a new type of atomic clock, believing that cesium and ammonia masers, a technology of amplified microwaves, were not precise enough to measure the effect of gravity on time.

Kleppner’s thesis was on using the concepts behind an ammonia maser to advance toward a hydrogen maser, which uses the natural microwave frequency of hydrogen atoms and amplifies it through stimulated emission of radiation. Kleppner discovered that coherent cesium atoms can bounce from properly prepared surfaces without losing their coherence.

After his 1959 PhD, Kleppner stayed on at Harvard, becoming an assistant professor in 1962.

Kleppner’s research on hydrogen led to a method to keep hydrogen atoms locked in a glass container for study over a longer period of time. The result, featuring hydrogen atoms bouncing within a microwave cavity, is used to stabilize the frequency of a clock to a precision better than one microsecond in a year.

In 1960, he and Ramsey successfully created a new atomic clock whose significant stability could confirm the minute effects of gravity on time, as predicted by Einstein’s theory of general relativity.

The current generation of optical clocks “are good enough to see the gravitational red shift for a few centimeters in height, so that’s quite extraordinary, and it’s had an extraordinary result,” said Kleppner. “We got to rethink just what we mean by time.”

While the hydrogen maser did verify Einstein’s conjecture about time and gravity, it took more than a decade before being widely used, at first by radio astronomers. Today, atomic clocks such as the hydrogen maser are used in applications requiring high short-term stability, such as the synchronization of ground-based timing systems that track global positioning satellites, for timekeeping and communication by naval observatories to maintain a precise and stable time reference known as UTC (USNO); very long-baseline microwave interferometry (VLBI) that enables astronomers to achieve very high resolution and study distant radio sources, including black holes; and, indirectly, in magnetic resonance imaging.

“When we first set out to make these atomic clocks, our goals were about the least practical you can think of,” Kleppner said in an interview with the MIT Physics Department. “From being a rather abstract idea that you’d like to somehow witness, it becomes a very urgent thing for the conduct of human affairs.”

Ramsey went on to win the Nobel Prize in Physics in 1989 for his work on the separated oscillatory fields method and its application in the hydrogen maser and atomic clocks.

MIT, ultracold gases, and BEC advancements

Kleppner figured he wouldn’t get tenure at Harvard, “because no matter how generous and good-spirited Norman was, he casts a long shadow, and it was good for me to be at just the right distance. When I came to MIT, I had a pallet of experiments that I wanted to pursue, and some ideas about teaching that I wanted to pursue, and the transition was very simple.”

Kleppner joined the Institute in 1966, and his Harvard PhD student (and current MIT professor post-tenure) David Pritchard followed him, to work on scattering experiments: Kleppner worked with pulsed lasers, and Pritchard with continuous-wave (CW) lasers.

“He was young, he was verbal, and he seemed to have new ideas about what to do,” says Pritchard. “We foresaw how important lasers would become. For a long time, it was just Dan and myself. That was actually the era in which lasers took over. Dan and I started off, we both got into lasers, and he did Rydberg atoms, and I did collisions and spectroscopy of weakly bound molecules and two-photon spectroscopy.”

Kleppner led the tiny MIT Atomic Physics Group to eventually become the US News and World Report’s No. 1 nationally ranked atomic physics group in 2012. “Dan was the leader on this,” recalled Pritchard. “To start from non-tenure and build it into the number-one ranked department in your subfield, that’s a lifetime achievement.”

The group became what Pritchard called “the supergroup” of laser developers that included Charles Townes, who won the Nobel for his work; Ali Javan, who established a major laser research center at MIT; and Dolly Shibles. Pritchard joined the faculty in 1970, and Ketterle joined in 1990 as his postdoc. “We were pioneers, and the result was of course that our total group had a bigger impact.”

“He’s not just the father figure of the field, he is my scientific father,” says Pritchard. “When I’m writing something and it’s not going very well, I would sort of think to myself, ‘What would Dan say? What would he advise you?”

With MIT low-temperature physicist Tom Greytak ’63, PhD ’67, Kleppner developed two revolutionary techniques — magnetic trapping and evaporative cooling. When the scientific community combined these techniques with laser cooling, atomic physics went into a major new direction.

In 1995, a group of researchers, led by Kleppner's former students Eric Cornell PhD ’90 and Carl Weiman ’73, made a BEC using rubidium atoms, and Ketterle succeeded with sodium atoms. For this achievement, they received the 2001 Nobel Prize in Physics. Kleppner called BEC “the most exciting advance in atomic physics for decades.” 

At a conference on BEC in 1996, Ketterle recalls Kleppner describing his own contributions: “'I feel like Moses, who showed his people the Holy Land, but he never reached it himself.' This was exactly what Dan did. He showed us the Holy Land of Bose-Einstein condensation. He showed us what is possible … He was the godfather of Bose-Einstein condensation.”

But he did reach the Holy Land. In 1998, when only a few groups had been able to create BECs, Kleppner and Greytak realized a hydrogen BEC. When he presented their work at the summer school in Varenna soon afterward, he received a long-lasting standing ovation — after 20 years of hard work, he had reached his goal.

“It is an irony that when Dan started this work, hydrogen was the only choice to reach the low temperatures for BEC,” says Ketterle. But in the end, it turned out that hydrogen has special properties that made it much harder to reach BEC than with other atoms. 

Rydberg atoms

In 1976, Kleppner pioneered the field of Rydberg atoms, a highly excited atom that shares the simple properties that characterize hydrogen. Kleppner showed that these states could be excited by a tunable laser and easily detected with field ionization. He then mapped out their response in high electric and magnetic fields, which he used to provide new physical insights into the connections between quantum mechanics and classical chaos.

In 1989, his research into atomic energy levels, under conditions where the corresponding classical motion is chaotic, mapped out the positions of thousands of quantum levels as a function of laser frequency and applied field using high-resolution laser spectroscopy. His observations gave new physical insight into the implications of classical chaos on quantum systems.

“I see Dan as being the inventor of Rydberg atoms,” says Dan’s former student William Phillips PhD ’76, physicist at the Institute of Standards and Technology (NIST). “Of course, Rydberg atoms is something that nature gives you, but Dan was the one who really understood this was something that you could use to do really new and wonderful things.”

Such atoms have proved to be useful for studying the transition between quantum mechanics and classical chaos. Kleppner’s 1976 paper on Rydberg atoms’ strong interactions, long lifetimes, and sensitivity to external fields has led to current scientific research and multimillion-dollar startups interested in developing the promising Rydberg quantum computer; highly accurate measurements of electric and magnetic fields; and in quantum optics experiments.

“Largely due to Dan’s seminal roadmap, Rydberg atoms have become atomic physics’ E. coli for investigating the interaction of radiation with matter,” wrote Ketterle in his nomination for Kleppner’s 2017 APS Medal for Exceptional Achievement in Research. “They are being used by others in quests for experimental systems to realize Schrödinger’s cat, as well as for making a quantum computer.”

In 1981, Kleppner suggested in a theoretical paper the possibility of suppressing spontaneous emission with a cavity: excited atoms cannot decay when the cavity lacks the oscillatory modes to receive their emissions. This was followed by his demonstration of this effect, and launched the field of cavity quantum electrodynamics (cQED), the study of how light confined within a reflective cavity interacts with atoms or other particles. This field has led to the creation of new lasers and photonic devices.

“This work fundamentally changed the way physicists regard the process of spontaneous emission by showing that it is not a fixed property of a quantum state, but can be modified and controlled,” said Ketterle. “Current applications of these principles, which Dan terms ‘wrecking the vacuum,’ include thresholdless lasers and the construction of photonic bandgap materials in which light propagation is forbidden at certain frequencies.”

MIT-Harvard Center for Ultracold Atoms

In 2000, Kleppner secured National Science Foundation funding to co-found the Center for Ultracold Atoms (CUA), an MIT-Harvard collaboration that linked RLE with the Harvard Department of Physics to explore the physics of ultracold atoms and quantum gases. Kleppner served as its first director until 2006, and was a member of a group that included MIT professors Ketterle, Pritchard, Vladan Vuletic, Martin W. Zwierlein, Paola Cappellaro PhD ’06, and Isaac Chuang ’90.

“Many centers disappear after 10 to 20 years; sometimes their mission is fulfilled,” says Ketterle, the CUA director from 2006 to 2023. “But given the excitement and the rapid evolution in atomic physics, the CUA is a super-active center brimming with excitement, and we just recently got renewed. That’s partially due to the efforts of Dan. He created the tradition of atomic physics at MIT. We are one of the best atomic physics groups in the world. And we are really a family.”

Boost-phase intercept report

Kleppner co-authored a highly influential 2003 report that examined the technical feasibility of boost-phase intercept, a concept central to President George H.W. Bush’s proposed controversial Strategic Defense Initiative (SDI), nicknamed "Star Wars,” which purportedly would render nuclear weapons obsolete. The focus of the APS Study on Boost-Phase Intercept for National Missile Defense, published as a special supplement to Reviews of Modern Physics, was on the physics and engineering challenges of intercepting a missile during its boost phase.

“This was a subject on which I had no technical background at all,” Kleppner recalled, so he expressed gratitude for the skills of co-chair Fred Lamb of the University of Illinois. “But the APS [American Physical Society] felt that it was important to have information for the public … and no one knew anything about it. It was the point in my life where I could do that. And I feel that you have an obligation when the need arises and you can do it, to do that.”

The result? “Technically, it really would not succeed, except in very limited circumstances,” Kleppner said. Added Pritchard, “It vastly changed the path of the nation.”

“He was the perfect person to chair the committee,” says Ketterle. “He excelled in being neutral and unbiased, and to create a no-nonsense report. I think the APS was very proud of this report. It shows how physicists analyze something which was at that moment of immense political and societal importance. This report helped to understand what laser weapons cannot do and what they can do. The fact that (SDI) eventually, slowly, disappeared, the report may have contributed to that.”

Dedicated educator

Kleppner trained generations of physicists, including as advisor to 23 PhD students who have gone on to attain positions in major universities and achieve major scientific awards.

He was awarded the Oersted Medal of the American Association of Physics Teachers in 1997, and earned the Institute’s prestigious 1995-1996 James R. Killian, Jr. Faculty Achievement Award for his service to MIT and society on behalf of atomic physics. “He has given generously of his time and effort to the formation of national science policy, and he has served the Institute with distinction as teacher, administrator and counselor,” the Killian committee wrote.

Kleppner and Ramsey wrote the widely used text “Quick Calculus” in 1972 — the third edition of the book was updated in 2022 edition with MIT Department of Physics’ Peter Dourmashkin. With Robert J. Kolenkow, Kleppner also wrote “An Introduction to Mechanics” in 1973, and its second edition in 2013. Physics department head Deepto Chakrabarty ’88 called it “a masterpiece:” “It has formed the foundation of our freshman 8.012 course for potential physics majors for over 50 years and has provided a deep, elegant, and mathematically sophisticated introduction to classical mechanics of physics majors across the U.S. It was my own introduction to serious physics as an MIT freshman in 1984.”

Recently, while Kleppner was being wheeled into surgery, one of the medical personnel noticed that his patient was the author of that book and blurted out, “Oh my God, I still am wondering about one of those problems that I found so difficult,” recalls his wife, Bea, laughing.

Kleppner called his method of teaching “an engagement with the students and with the subject.” He said that his role model for teaching was his wife, who taught psychology at Beaver Country Day High School. “Fortunately, at MIT, the students are so great. There’s nothing tough about teaching here, except trying to stay ahead of the students.”

He leaves a legacy of grateful physicists impacted by his generous teaching style.

“I’ve always felt that I’ve just been incredibly lucky to be part of Dan’s group,” says Phillips, who was at Princeton when his research into magnetic resonance caught Kleppner’s attention, and invited him to MIT. “Dan extended this idea to putting this hydrogen maser in a much higher magnetic field. Not that many people are trained by somebody like Dan Kleppner in the art of precision measurement.”

Kleppner also gifted Phillips an apparatus he built for his thesis, which shaved years off the laser cooling experiments that led to Phillips’ Nobel.

Ketterle credited Kleppner’s mentorship for his career at MIT. “He was an older, experienced person who believed in me. He had more trust in me than I had initially myself. I felt whenever I was at a crossroads, I could go to Dan and ask him for advice. When I gave him a paper to edit … there was red ink all over it, but he was absolutely right on almost everything.’”

In 2003, Kleppner was dismayed at the statistic that over 60 percent of middle and high school teachers teaching physics have no background in the subject. He started the CUA’s Teaching Opportunities in Physical Science summer program with his then-postdoc Ted Ducas to train physics majors to prepare and teach physics material to middle and high school students. In its 14-year run, they worked with 112 students.

According to Ducas, one survey “indicates over 60 percent of our undergraduates have gone into, or plan to go into, pre-college teaching — a higher percentage than expected, because physics majors have so many other career opportunities often paying significantly more. The potential positive impact of that number of highly qualified and motivated teachers is dramatic.”

Kleppner also partnered with Japanese mathematician Heisuke Hironaka on the mentoring program Japanese Association for Mathematical Sciences (JAMS), which connected American college science students with their Japanese counterparts. “His interest in ensuring that future generations also see the value of international communities was reflected in JAMS,” says Sofie Kleppner.

Recognitions and public service

Kleppner was promoted to professor in 1974 and headed the physics department’s Division of Atomic, Plasma and Condensed Matter Physics from 1976 to 1979. He was named the Lester Wolfe Professor of Physics in 1985.

Active in the interface between physics and public policy, he served on more than 30 committees. For the APS, he was on the Panel on Public Affairs (POPA), chaired the Physics Planning Committee and the Division of Atomic, Molecular and Optical Physics, and contributed to a study on the growth and mentorship of young physics professors. He chaired a report for the National Academy of Sciences on atomic physics that he presented on various congressional committees, served on the National Research Council's Physics Survey Committee, and was chair of the International Union of Pure and Applied Physics’ Commission on Atomic and Molecular Physics. At MIT, he was also an ombuds of the Physics Department.

Kleppner was a fellow of the American Academy of Arts and Sciences, American Association for the Advancement of Science, OSA (now Optica), French Academy of Sciences, and the American Philosophical Society; a member of the National Academy of Sciences; and a Phi Beta Kappa lecturer.

His interest in literature at Williams bloomed into a secondary career as a writer, including decades of writing witty and insightful, yet accessible, pieces for Physics Today, including his “Reference Frame” columns on physics history and policy.

Kleppner was a recipient of many awards, including the prestigious Wolf Prize in 2005 “for groundbreaking work in atomic physics of hydrogenic systems, including research on the hydrogen maser, Rydberg atoms, and Bose-Einstein condensation.” Other accolades include a 2014 Benjamin Franklin Medal and a 2006 National Medal of Science, presented by U.S. President George W. Bush. He also received the Frederic Ives Medal (2007), the William F. Meggers Award (1991), the Lilienfeld Prize (1991), and the Davisson-Germer Prize (1986).

His articles, congressional testimony, and advocating on behalf of physicists around the world at one point inspired his Physics Planning Committee colleagues to present him with a Little League trophy of a golden baseball player, with the inscription “Dan Kleppner — Who Went to Bat for Atomic Physics.”

Kleppner said that he was inspired by his mentor, Ramsey, to get involved in the scientific community. “It’s a privilege to be a scientist in this country,” said Kleppner. “And I think that one has some obligation to pay for the privilege, when you can.”

He wrote, “Any scenario for a decent future of our nation and the world must include a reasonable component of science that is devoted to the search for new knowledge. We cannot afford to abandon this vision under a barrage of criticism, no matter how eloquent or powerful the critics.”

Family and retired life

Kleppner met his future wife, Beatrice Spencer, in 1954 on the USS United States, when both were England-bound and in their second year of studying at Cambridge. They began as friends, and eventually married in 1958, in Ipswich, Massachusetts. They raised their three children, Sofie, Paul, and Andrew, at their home in Belmont, Massachusetts, and their vacation home in Vermont.

Kleppner’s family described him as an optimist who didn’t believe in lying, worrying, or unethical behavior. He and Bea generously invited into their home anyone in need. “When we were growing up, we had the international community in our house,” recalls Sofie. “He was just a tremendously generous person. At my father’s 80th birthday celebration at MIT, there were three hours of five-minute reminiscences. It was really moving to hear the number of people who felt that just having the open door at my parents’ house meant the difference to them as they went through difficult times.”

In his retirement, Kleppner continued with his woodworking projects, including building beds, lamps, cabinets, a beautiful spiral staircase, a cradle curved like the hull of a boat, and bookcases featuring super ellipses, a closed curve that blends elements of an ellipse and a rectangle.

“I enjoy designing,” he said in one video. “It’s the same instinct for making things work in experimental physics. It’s lovely to make a piece of apparatus that starts functioning, and even if the experiment doesn’t do what you want it to do. There’s always a lot of jubilation when the apparatus is first turned on and first works.”

His last article for Physics Today was in 2020. In his later years, he kept in touch with his colleagues, swapping book ideas with Ketterle’s wife, Michele Plott, and, since the Covid-19 pandemic, maintained regular Zoom meetings with a group of his former students, hosted by Mike Kash; and another, what they called “The Famous Physicists,” that included Phillips and  their Brazilian colleague Vanderlei Bagnato.

“In recent years, I would still go to Dan for advice about difficult questions,” says Phillips, “sometimes about physics, sometimes just about life and public policy, because maybe I always felt that if there was anything you wanted done in which physics or science was part of the question that Dan would be the best person to do it.”

His family says that Kleppner suddenly fell ill at a Father’s Day dinner. According to his wife, his last words before being rushed to the hospital were a toast to his grandson, who recently graduated high school: “To Darwin and all youth who have new and exciting ideas.”

Says Bea, “​​He always said that you have to be optimistic to be a scientist, because you have to be patient. Things don’t work out and they’re fiddly, and there are lots of things that go wrong. His last words were ones that make you feel there’s hope for the future.”

The National Academy of Sciences (NAS) has elected 120 members and 30 international members, including five MIT faculty members and 13 MIT alumni. Professors Rodney Brooks, Parag Pathak, Scott Sheffield, Benjamin Weiss, and Yukiko Yamashita were elected in recognition of their “distinguished and continuing achievements in original research.” Membership to the National Academy of Sciences is one of the highest honors a scientist can receive in their career.

Elected MIT alumni include: David Altshuler ’86, Rafael Camerini-Otero ’66, Kathleen Collins PhD ’92, George Daley PhD ’89, Scott Doney PhD ’91, John Doyle PhD ’91, Jonathan Ellman ’84, Shanhui Fan PhD ’97, Julia Greer ’97, Greg Lemke ’78, Stanley Perlman PhD ’72, David Reichman PhD ’97, and Risa Wechsler ’96. 

Those elected this year bring the total number of active members to 2,662, with 556 international members. The NAS is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — with the National Academy of Engineering and the National Academy of Medicine — provides science, engineering, and health policy advice to the federal government and other organizations.

Rodney Brooks

Rodney A. Brooks is the Panasonic Professor of Robotics Emeritus at MIT and the chief technical officer and co-founder of Robust AI. Previously, he was founder, chair, and CTO of Rethink Robotics and founder and CTO of iRobot Corp. He is also the former director of the MIT Artificial Intelligence Laboratory and the MIT Computer Science and Artificial Intelligence Laboratory. Brooks received degrees in pure mathematics from the Flinders University of South Australia and a PhD in computer science from Stanford University in 1981. He held research positions at Carnegie Mellon University and MIT, and a faculty position at Stanford before joining the faculty of MIT in 1984.

Brooks’ research is concerned with both the engineering of intelligent robots to operate in unstructured environments, and with understanding human intelligence through building humanoid robots. He has published papers and books in model-based computer vision, path planning, uncertainty analysis, robot assembly, active vision, autonomous robots, micro-robots, micro-actuators, planetary exploration, representation, artificial life, humanoid robots, and compiler design.

Brooks is a member of the National Academy of Engineering, a founding fellow of the Association for the Advancement of Artificial Intelligence, a fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the Association for Computing Machinery, a foreign fellow of The Australian Academy of Technological Sciences and Engineering, and a corresponding member of the Australian Academy of Science. He won the Computers and Thought Award at the 1991 International Joint Conference on Artificial Intelligence, and the IEEE Founders Medal in 2023.

Parag Pathak

Parag Pathak is the Class of 1922 Professor of Economics and a founder and director of MIT’s Blueprint Labs. He joined the MIT faculty in 2008 after completing his PhD in business economics and his master’s and bachelor’s degrees in applied mathematics, all at Harvard University.

Pathak is best known for his work on market design and education. His research has informed student placement and school choice mechanisms across the United States, including in Boston, New York City, Chicago, and Washington, and his recent work applies ideas from market design to the rationing of vital medical resources. Pathak has also authored leading studies on school quality, charter schools, and affirmative action. In urban economics, he has measured the effects of foreclosures on house prices and how the housing market reacted to the end of rent control in Cambridge, Massachusetts.

Pathak’s research on market design was recognized with the 2018 John Bates Clark Medal, given by the American Economic Association to the economist under 40 whose work is judged to have made the most significant contribution to the field. He is a fellow of the American Academy of Arts and Sciences, the Econometric Society, and the Society for the Advancement of Economic Theory. Pathak is also the founding co-director of the market design working group at the National Bureau of Economic Research, and a co-founder of Avela Education.

Scott Sheffield

Scott Sheffield, Leighton Family Professor of Mathematics, joined the MIT faculty in 2008 after a faculty appointment at the Courant Institute at New York University. He received a PhD in mathematics from Stanford University in 2003 under the supervision of Amir Dembo, and completed BA and MA degrees in mathematics from Harvard University in 1998.

Sheffield is a probability theorist, working on geometrical questions that arise in such areas as statistical physics, game theory, and metric spaces, as well as long-standing problems in percolation theory and the theory of random surfaces.

In 2017, Sheffield received the Clay Research Award with Jason Miller, “in recognition of their groundbreaking and conceptually novel work on the geometry of Gaussian free field and its application to the solution of open problems in the theory of two-dimensional random structures.” In 2023, he received the Leonard Eisenbud Prize with Jason Miller “for works on random two-dimensional geometries, and in particular on Liouville Quantum Gravity.” Later in 2023, Sheffield received the Frontiers of Science Award with Jason Miller for the paper “Liouville quantum gravity and the Brownian map I: the QLE(8/3,0) metric.” Sheffield is a fellow of the American Academy of Arts and Science.

Benjamin Weiss

Benjamin Weiss is the Robert R. Schrock Professor of Earth and Planetary Sciences. He studied physics at Amherst College as an undergraduate and went on to study planetary science and geology at Caltech, where he earned a master’s degree in 2001 and PhD in 2003. Weiss’ doctoral dissertation on Martian meteorite ALH 84001 revealed records of the ancient Martian climate and magnetic field, and provided evidence some meteorites could transfer materials from Mars to Earth without heat-sterilization. Weiss became a member of the Department of Earth, Atmospheric and Planetary Sciences faculty in 2004 and is currently chair of the Program in Planetary Science.

A specialist in magnetometry, Weiss seeks to understand the formation and evolution of the Earth, terrestrial planets, and small solar system bodies through laboratory analysis, spacecraft observations, and fieldwork. He is known for key insights into the history of our solar system, including discoveries about the early nebular magnetic field, the moon’s long-lived core dynamo, and asteroids that generated core dynamos in the past. In addition to leadership roles on current, active NASA missions — as deputy principal investigator for Psyche, and co-investigator for Mars Perseverance and Europa Clipper — Weiss has also been part of science teams for the SpaceIL Beresheet, JAXA Hayabusa 2, and ESA Rosetta spacecraft.

As principal investigator of the MIT Planetary Magnetism Laboratory, Weiss works to develop high-sensitivity, high-resolution techniques in magnetic microscopy to image the magnetic fields embedded in rock samples collected from meteorites, the lunar surface, and sites around the Earth. Studying these magnetic signatures can help answer questions about the conditions of the early solar system, past climates on Earth and Mars, and factors that promote habitability.

Yukiko Yamashita

Yukiko Yamashita is a professor of biology at MIT, a core member of the Whitehead Institute for Biomedical Research, and an investigator at the Howard Hughes Medical Institute (HHMI). Yamashita earned her BS in biology in 1994 and her PhD in biophysics in 1999 from Kyoto University. From 2001 to 2006, she did postdoctoral research at Stanford University. She was appointed to the University of Michigan faculty in 2007 and was named an HHMI Investigator in 2014. She became a member of the Whitehead Institute and a professor of biology at MIT in 2020.

Yukiko Yamashita studies two fundamental aspects of multicellular organisms: how cell fates are diversified via asymmetric cell division, and how genetic information is transmitted through generations via the germline.

Two remarkable feats of multicellular organisms are generation of many distinct cell types via asymmetric cell division and transmission of the germline genome to the next generation, essentially in eternity. Studying these processes using the Drosophila male germline as a model system has led us to venture into new areas of study, such as functions of satellite DNA, “genomic junk,” and how they might be involved in speciation.

Yamashita is a member of the American Academy of Arts and Sciences, a fellow of the American Society for Cell Biology, and the winner of the Tsuneko and Reiji Okazaki Award in 2016. She was named a MacArthur Fellow in 2011.

Researchers at MIT and other institutions have identified compounds that can fight off viral infection by activating a defense pathway inside host cells. These compounds, they believe, could be used as antiviral drugs that work against not just one but any kind of virus.

The researchers identified these compounds, which activate a host cell defense system known as the integrated stress response pathway, in a screen of nearly 400,000 molecules. In tests in human cells, the researchers showed that the compounds help cells fend off infection from RSV, herpes virus, and Zika virus. They also proved effective in combating herpes infection in a mouse model.

The research team now plans to test the compounds against additional viruses, in hopes of developing them for eventual clinical trials.

“We’re very excited about this work, which allows us to harness the stress response of the host cells to arrive at a means to identify and develop broad-spectrum antivirals,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering.

Collins and Maxwell Wilson, an associate professor of molecular biology at the University of California, Santa Barbara and chief scientific officer of Integrated Biosciences, are the senior authors of the new study, which appears in Cell. Felix Wong, a former MIT postdoc and chief executive officer of Integrated Biosciences, is the lead author of the paper. In addition to MIT, UCSB, and Integrated Biosciences, the research team also includes scientists from Illumina Ventures and Princeton University.

Boosting cell defense

In human cells, the integrated stress response pathway is turned on in response to viral infection as well as other types of stress such as starvation. During viral infection, the pathway is triggered by double-stranded RNA, a molecule produced during the replication cycle of viruses. When that RNA is detected, the cell shuts down protein synthesis, which blocks the virus from producing the proteins it needs to replicate.

Compounds that boost this pathway, the researchers believe, could be good candidates for new antiviral drugs that could combat any type of virus.

“Typically, how antivirals are developed is that you develop one antiviral for one specific virus,” Wong says. “In this case, we hypothesized that being able to modulate the host cell stress response might give us a new class of broad-spectrum antivirals — compounds that directly act on the host cells to alter something fundamental about how all viruses replicate.”

To help them identify compounds that would enhance the activity of this pathway during viral infection, the researchers invented a novel optogenetic screen. Optogenetics is a bioengineering technique that allows researchers to insert light-sensitive proteins into the genome of a cell. In this case, the researchers engineered modifications to a protein called PKR, which turns on the stress pathway, so that they could turn it on with light.

Using this technique, the researchers screened a library of nearly 400,000 commercially available and proprietary chemical compounds. Each of these compounds was applied to human cells as the cells were also exposed to blue light, which simulated viral infection by activating PKR.

By measuring the cells’ survival rates, the researchers could determine which compounds boosted activation of the pathway and amplified the cells’ ability to shut down viral reproduction. This screen yielded about 3,500 compounds with potential antiviral activity, which were evaluated further.

“If the pathway were turned on in response to viral infection, what our compounds do is they turn it on full blast,” Wong says. “Even in the presence of a small amount of virus, if the pathway is triggered, then the antiviral response is also maximized.”

Fighting infection

The researchers then selected eight of the most promising compounds and screened them for their ability to kill viruses while avoiding harmful effects in human cells. Based on these tests, the researchers chose three top candidates, which they called IBX-200, IBX-202, and IBX-204.

In cells that were infected with either Zika virus, herpes virus, or RSV, treatment with these compounds significantly reduced the amount of virus in the cells. The researchers then tested one of the compounds, IBX-200, in mice infected with herpes virus, and found that it was able to reduce the viral load and improve symptoms.

Experiments showed that these compounds appear to turn on an enzyme that is involved in detecting stress. This activates the stress response pathway and primes the cells to become more responsive to viral infection. When applied to cells that are not already infected, the compounds have no effect.

The researchers now plan to evaluate their lead candidates against a broader range of viruses. They also aim to identify additional compounds that activate the integrated stress response, as well as other cellular stress pathways with the potential to clear viral or bacterial infections.

The research was funded by the Defense Threat Reduction Agency, the National Science Foundation, the U.S. Army Research Office, and Integrated Biosciences.

When ChatGPT or Gemini give what seems to be an expert response to your burning questions, you may not realize how much information it relies on to give that reply. Like other popular generative artificial intelligence (AI) models, these chatbots rely on backbone systems called foundation models that train on billions, or even trillions, of data points.

In a similar vein, engineers are hoping to build foundation models that train a range of robots on new skills like picking up, moving, and putting down objects in places like homes and factories. The problem is that it’s difficult to collect and transfer instructional data across robotic systems. You could teach your system by teleoperating the hardware step-by-step using technology like virtual reality (VR), but that can be time-consuming. Training on videos from the internet is less instructive, since the clips don’t provide a step-by-step, specialized task walk-through for particular robots.

A simulation-driven approach called “PhysicsGen” from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Robotics and AI Institute customizes robot training data to help robots find the most efficient movements for a task. The system can multiply a few dozen VR demonstrations into nearly 3,000 simulations per machine. These high-quality instructions are then mapped to the precise configurations of mechanical companions like robotic arms and hands. 

PhysicsGen creates data that generalize to specific robots and condition via a three-step process. First, a VR headset tracks how humans manipulate objects like blocks using their hands. These interactions are mapped in a 3D physics simulator at the same time, visualizing the key points of our hands as small spheres that mirror our gestures. For example, if you flipped a toy over, you’d see 3D shapes representing different parts of your hands rotating a virtual version of that object.

The pipeline then remaps these points to a 3D model of the setup of a specific machine (like a robotic arm), moving them to the precise “joints” where a system twists and turns. Finally, PhysicsGen uses trajectory optimization — essentially simulating the most efficient motions to complete a task — so the robot knows the best ways to do things like repositioning a box.

Each simulation is a detailed training data point that walks a robot through potential ways to handle objects. When implemented into a policy (or the action plan that the robot follows), the machine has a variety of ways to approach a task, and can try out different motions if one doesn’t work.

“We’re creating robot-specific data without needing humans to re-record specialized demonstrations for each machine,” says Lujie Yang, an MIT PhD student in electrical engineering and computer science and CSAIL affiliate who is the lead author of a new paper introducing the project. “We’re scaling up the data in an autonomous and efficient way, making task instructions useful to a wider range of machines.”

Generating so many instructional trajectories for robots could eventually help engineers build a massive dataset to guide machines like robotic arms and dexterous hands. For example, the pipeline might help two robotic arms collaborate on picking up warehouse items and placing them in the right boxes for deliveries. The system may also guide two robots to work together in a household on tasks like putting away cups.

PhysicsGen’s potential also extends to converting data designed for older robots or different environments into useful instructions for new machines. “Despite being collected for a specific type of robot, we can revive these prior datasets to make them more generally useful,” adds Yang.

Addition by multiplication

PhysicsGen turned just 24 human demonstrations into thousands of simulated ones, helping both digital and real-world robots reorient objects.

Yang and her colleagues first tested their pipeline in a virtual experiment where a floating robotic hand needed to rotate a block into a target position. The digital robot executed the task at a rate of 81 percent accuracy by training on PhysicGen’s massive dataset, a 60 percent improvement from a baseline that only learned from human demonstrations.

The researchers also found that PhysicsGen could improve how virtual robotic arms collaborate to manipulate objects. Their system created extra training data that helped two pairs of robots successfully accomplish tasks as much as 30 percent more often than a purely human-taught baseline.

In an experiment with a pair of real-world robotic arms, the researchers observed similar improvements as the machines teamed up to flip a large box into its designated position. When the robots deviated from the intended trajectory or mishandled the object, they were able to recover mid-task by referencing alternative trajectories from their library of instructional data.

Senior author Russ Tedrake, who is the Toyota Professor of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering at MIT, adds that this imitation-guided data generation technique combines the strengths of human demonstration with the power of robot motion planning algorithms.

“Even a single demonstration from a human can make the motion planning problem much easier,” says Tedrake, who is also a senior vice president of large behavior models at the Toyota Research Institute and CSAIL principal investigator. “In the future, perhaps the foundation models will be able to provide this information, and this type of data generation technique will provide a type of post-training recipe for that model.”

The future of PhysicsGen

Soon, PhysicsGen may be extended to a new frontier: diversifying the tasks a machine can execute.

“We’d like to use PhysicsGen to teach a robot to pour water when it’s only been trained to put away dishes, for example,” says Yang. “Our pipeline doesn’t just generate dynamically feasible motions for familiar tasks; it also has the potential of creating a diverse library of physical interactions that we believe can serve as building blocks for accomplishing entirely new tasks a human hasn’t demonstrated.”

Creating lots of widely applicable training data may eventually help build a foundation model for robots, though MIT researchers caution that this is a somewhat distant goal. The CSAIL-led team is investigating how PhysicsGen can harness vast, unstructured resources — like internet videos — as seeds for simulation. The goal: transform everyday visual content into rich, robot-ready data that could teach machines to perform tasks no one explicitly showed them.

Yang and her colleagues also aim to make PhysicsGen even more useful for robots with diverse shapes and configurations in the future. To make that happen, they plan to leverage datasets with demonstrations of real robots, capturing how robotic joints move instead of human ones.

The researchers also plan to incorporate reinforcement learning, where an AI system learns by trial and error, to make PhysicsGen expand its dataset beyond human-provided examples. They may augment their pipeline with advanced perception techniques to help a robot perceive and interpret their environment visually, allowing the machine to analyze and adapt to the complexities of the physical world.

For now, PhysicsGen shows how AI can help us teach different robots to manipulate objects within the same category, particularly rigid ones. The pipeline may soon help robots find the best ways to handle soft items (like fruits) and deformable ones (like clay), but those interactions aren’t easy to simulate yet.

Yang and Tedrake wrote the paper with two CSAIL colleagues: co-lead author and MIT PhD student Hyung Ju “Terry” Suh SM ’22 and MIT PhD student Bernhard Paus Græsdal. Robotics and AI Institute researchers Tong Zhao ’22, MEng ’23, Tarik Kelestemur, Jiuguang Wang, and Tao Pang PhD ’23 are also authors. Their work was supported by the Robotics and AI Institute and Amazon.

The researchers recently presented their work at the Robotics: Science and Systems conference.

In order to produce effective targeted therapies for cancer, scientists need to isolate the genetic and phenotypic characteristics of cancer cells, both within and across different tumors, because those differences impact how tumors respond to treatment.

Part of this work requires a deep understanding of the RNA or protein molecules each cancer cell expresses, where it is located in the tumor, and what it looks like under a microscope.

Traditionally, scientists have looked at one or more of these aspects separately, but now a new deep learning AI tool, CellLENS (Cell Local Environment and Neighborhood Scan), fuses all three domains together, using a combination of convolutional neural networks and graph neural networks to build a comprehensive digital profile for every single cell. This allows the system to group cells with similar biology — effectively separating even those that appear very similar in isolation, but behave differently depending on their surroundings.

The study, published recently in Nature Immunology, details the results of a collaboration between researchers from MIT, Harvard Medical School, Yale University, Stanford University, and University of Pennsylvania — an effort led by Bokai Zhu, an MIT postdoc and member of the Broad Institute of MIT and Harvard and the Ragon Institute of MGH, MIT, and Harvard.

Zhu explains the impact of this new tool: “Initially we would say, oh, I found a cell. This is called a T cell. Using the same dataset, by applying CellLENS, now I can say this is a T cell, and it is currently attacking a specific tumor boundary in a patient.

“I can use existing information to better define what a cell is, what is the subpopulation of that cell, what that cell is doing, and what is the potential functional readout of that cell. This method may be used to identify a new biomarker, which provides specific and detailed information about diseased cells, allowing for more targeted therapy development.”

This is a critical advance because current methodologies often miss critical molecular or contextual information — for example, immunotherapies may target cells that only exist at the boundary of a tumor, limiting efficacy. By using deep learning, the researchers can detect many different layers of information with CellLENS, including morphology and where the cell is spatially in a tissue.

When applied to samples from healthy tissue and several types of cancer, including lymphoma and liver cancer, CellLENS uncovered rare immune cell subtypes and revealed how their activity and location relate to disease processes — such as tumor infiltration or immune suppression.

These discoveries could help scientists better understand how the immune system interacts with tumors and pave the way for more precise cancer diagnostics and immunotherapies.

“I’m extremely excited by the potential of new AI tools, like CellLENS, to help us more holistically understand aberrant cellular behaviors within tissues,” says co-author Alex K. Shalek, the director of the Institute for Medical Engineering and Science (IMES), the J. W. Kieckhefer Professor in IMES and Chemistry, and an extramural member of the Koch Institute for Integrative Cancer Research at MIT, as well as an Institute member of the Broad Institute and a member of the Ragon Institute. “We can now measure a tremendous amount of information about individual cells and their tissue contexts with cutting-edge, multi-omic assays. Effectively leveraging that data to nominate new therapeutic leads is a critical step in developing improved interventions. When coupled with the right input data and careful downsteam validations, such tools promise to accelerate our ability to positively impact human health and wellness.”

For many years, health experts have been concerned about “food deserts,” places where residents lack good nutritional options. Now, an MIT-led study of three major global cities uses a new, granular method to examine the issue, and concludes that having fewer and less nutritional eating options nearby correlates with obesity and other health outcomes.

Rather than just mapping geographic areas, the researchers examined the dietary value of millions of food items on roughly 30,000 restaurant menus and derived a more precise assessment of the connection between neighborhoods and nutrition.

“We show that what is sold in a restaurant has a direct correlation to people’s health,” says MIT researcher Fabio Duarte, co-author of a newly published paper outlining the study’s results. “The food landscape matters.”

The open-access paper, “Data-driven nutritional assessment of urban food landscapes: insights from Boston, London, Dubai,” was published this week in Nature: Scientific Reports.

The co-authors are Michael Tufano, a PhD student at Wageningen University, in the Netherlands; Duarte, associate director of MIT’s Senseable City Lab, which uses data to study cities as dynamic systems; Martina Mazzarello, a postdoc at the Senseable City Lab; Javad Eshtiyagh, a research fellow at the Senseable City Lab; Carlo Ratti, professor of the practice and director of the Senseable City Lab; and Guido Camps, a senior researcher at Wageningen University.

Scanning the menu

To conduct the study, the researchers examined menus from Boston, Dubai, and London, in the summer of 2023, compiling a database of millions of items available through popular food-delivery platforms. The team then evaluated the food items as rated by the USDA’s FoodData Central database, an information bank with 375,000 kinds of food products listed. The study deployed two main metrics, the Meal Balance Index, and the Nutrient-Rich Foods Index.

The researchers examined about 222,000 menu items from over 2,000 restaurants in Boston, about 1.6 million menu items from roughly 9,000 restaurants in Dubai, and about 3.1 million menu items from about 18,000 restaurants in London. In Boston, about 71 percent of the items were in the USDA database; in Dubai and London, that figure was 42 percent and 56 percent, respectively.

The team then rated the nutritional value of the items appearing on menus, and correlated the food data with health-outcome data from Boston and London. In London, they found a clear correlation between neighborhood menu offerings and obesity, or the lack thereof; with a slightly less firm correlation in Boston. Areas with food options that include a lot of dietary fibers, sometimes along with fruits and vegetables, tend to have better health data.

In Dubai, the researchers did not have the same types of health data available but did observe a strong correlation between rental prices and the nutritional value of neighborhood-level food, suggesting that wealthier residents have better nourishment options.

“At the item level, when we have less nutritional food, we see more cases of obsesity,” Tufano says. “It’s true that not only do we have more fast food in poor neighborhoods, but the nutritional value is not the same.”

Re-mapping the food landscape

By conducting the study in this fashion, the scholars added a layer of analysis to past studies of food deserts. While past work has broken ground by identifying neighborhoods and areas lacking good food access, this research makes a more comprehensive assessment of what people consume. The research moves toward evaluating the complex mix of food available in any given area, which can be true even of areas with more limited options.

“We were not satisfied with this idea that if you only have fast food, it’s a food desert, but if you have a Whole Foods, it’s not,” Duarte says. “It’s not necessarily like that.”

For the Senseable City Lab researchers, the study is a new technique further enabling them to understand city dynamics and the effects of the urban environment on health. Past lab studies have often focused on issues such as urban mobility, while extending to matters such as mobility and air pollution, among other topics.

Being able to study food and health at the neighborhood level, though, is still another example of the ways that data-rich spheres of life can be studied in close detail.

“When we started working on cities and data, the data resolution was so low,” Ratti says. “Today the amount of data is so immense we see this great opportunity to look at cities and see the influence of the urban environment as a big determinant of health. We see this as one of the new frontiers of our lab. It’s amazing how we can now look at this very precisely in cities.”

From the very beginning, MIT Professor Mark Bear’s philosophy for the textbook “Neuroscience: Exploring the Brain” was to provide an accessible and exciting introduction to the field while still giving undergraduates a rigorous scientific foundation. In the 30 years since its first print printing in 1995, the treasured 975-page tome has gone on to become the leading introductory neuroscience textbook, reaching hundreds of thousands of students at hundreds of universities around the world.

“We strive to present the hard science without making the science hard,” says Bear, the Picower Professor in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences at MIT. The fifth edition of the textbook is out today from the publisher Jones & Bartlett Learning.

Bear says the book is conceived, written, and illustrated to instill students with the state of knowledge in the field without assuming prior sophistication in science. When he first started writing it in the late 1980s — in an effort soon joined by his co-authors and former Brown University colleagues Barry Connors and Michael Paradiso — there simply were no undergraduate neuroscience textbooks. Up until then, first as a graduate teaching assistant and then as a young professor, Bear taught Brown’s pioneering introductory neuroscience class with a spiral-bound stack of photocopied studies and other scrounged readings.

Don’t overwhelm

Because universities were only beginning to launch neuroscience classes and majors at the time, Bear recalls that it was hard to find a publisher. The demand was just too uncertain. With an unsure market, Bear says, the original publisher, Williams & Wilkins, wanted to keep costs down by printing only in black and white. But Bear and his co-authors insisted on color. Consistent with their philosophy for the book, they wanted students, even before they began reading, to be able to learn from attractive, high-quality illustrations.

“Rather than those that speak a thousand words, we wanted to create illustrations that each make a single point.” Bear says. “We don’t want to overwhelm students with a bunch of detail. If people want to know what’s in our book, just look at the pictures.”

Indeed, if the book had struck students as impenetrable and dull, Bear says, he and his co-authors would have squandered the advantage they had in presenting their subject: the inherently fascinating and exciting brain.

“Most good scientists are extremely enthusiastic about the science. It exciting. It’s fun. It turns them on,” Bear says. “We try to communicate the joy. We’re so lucky because the object of our affection is the brain.”

To help bring that joy and excitement across, another signature of the book throughout its 30-year-history has been the way it presents the process of discovery alongside the discoveries themselves, Bear says. While it’s instructive to provide students with the experimental evidence that supports the concepts they are learning, it would bog down the text to delineate the details of every experiment. Instead, Bear, Connors, and Paradiso have chosen to highlight the process of discovery via one-page guest essays by prominent neuroscientists who share their discovery stories personally. Each edition has featured about 25 such “Path of Discovery” essays, so more than 100 scientists have participated, including several Nobel Prize winners, such as the Picower Institute’s founding director, Susumu Tonegawa.

The new edition includes Path of Discovery essays by current Picower Institute Director Li-Huei Tsai and Picower Institute colleague Emery N. Brown. Tsai recounts her discovery that sensory stimulation of 40Hz rhythms in the brain can trigger a health-promoting response among many different cell types. Brown writes about how various biological cycles and rhythms in the brain and body, such as the circadian rhythms and brain waves, help organize our daily lives.

Immense impact

Jones & Bartlett reports that more than 470 colleges and universities in 48 U.S. states and the District of Columbia have used the fourth edition of the book. Various editions have also been translated into seven other languages, including Chinese, French, Portuguese, and Spanish. There are hundreds of reviews on Amazon.com with an average around 4.6 stars. One reviewer wrote about the fourth edition: “I never knew it was possible to love a textbook before!”

The reviews sometimes go beyond mere internet postings. Once, after Bear received an award in Brazil, he found himself swarmed at the podium by scores of students eager for him to sign their copies of the book. And earlier this year, when Bear needed surgery, the anesthesiologist was excited to meet him.

“The anesthesiologist was like, ‘Are you the Mark Bear who wrote the textbook?,’ and she was so excited, because she said, ‘This book changed my life,’” Bear recalls. “After I recovered, she showed up in the ICU for me to sign it. All of us authors have had this experience that there are people whose lives we’ve touched.”

While Bear is proud that so many students have benefited from the book, he also notes that teaching and textbook writing have benefited him as a scientist. They have helped him present his research more clearly, he says, and have given him a broad perspective on what’s truly important in the field.

“Experience teaching will influence the impact of your own science by making you more able to effectively communicate it.” Bear says. “And the teacher has a difficult job of surveying a field and saying, ‘I’ve got to capture the important advances and set aside the less-important stuff.’ It gives you a perspective that helps you to discriminate between more-important and less-important problems in your own research.”

Over the course of 30 years via their carefully crafted book, Bear, Connors, and Paradiso have lent that perspective to generations of students. And the next generation will start with today’s publishing of the new edition. 

The MIT Institute for Data, Systems, and Society (IDSS) announced the creation of a new endowed chair made possible by the generosity of IDSS professor post-tenure and “MIT lifer” Richard “Dick” Larson. Effective July 1, the fund provides a full professorship for senior IDSS faculty: the Distinguished Professorship in Data, Systems, and Society.

“As a faculty member, MIT has not only accepted but embraced my several mid-career changes of direction,” says Larson. “I have called five different academic departments my home, starting with Electrical Engineering (that is what it was called in the 1960s) and now finalized with the interdepartmental, interdisciplinary IDSS — Institute for Data, Systems and Society. Those beautiful three words  — data, systems, society — they represent my energy and commitment over the second half of my career. My gifted chair is an effort to keep alive those three words, with others following me doing research, teaching and mentoring centered around data, systems, society.”

Larson’s career has focused his operations research and systems expertise on a wide variety of problems, in both public and private sectors. His contributions span the fields of urban service systems (especially emergency response systems), disaster planning, pandemics, queueing, logistics, technology-enabled education, smart-energy houses, and workforce planning. His latest book, “Model Thinking for Everyday Life,” draws on decades of experience as a champion of STEM education at MIT and beyond, such as his leadership of MIT BLOSSOMS.

“Dick Larson has been making an impact at MIT for over half a century,” says IDSS Director Fotini Christia, the Ford International Professor in Political Science. “This gift extends his already considerable legacy and ensures his impact will continue to be felt for many years to come.”

Christia is pleased that IDSS and brain and cognitive science professor Alexander “Sasha” Rakhlin is the inaugural holder of the new professorship. The selection recognizes Rakhlin’s distinguished scholarly record, dedicated service to IDSS, excellence in teaching, and contributions to research in statistics and computation.

“Sasha’s analysis of neural network complexity, and his work developing tools for online prediction, are perfect examples of research which builds bridges across disciplines, and also connects different departments and units at MIT,” says Michale Fee, the Glen V. and Phyllis F. Dorflinger Professor of Neuroscience, and head of the Department of Brain and Cognitive Sciences. “It’s wonderful to see Sasha’s contributions recognized in this way, and I’m grateful to Dick Larson for supporting this vision.”

Rakhlin’s research is in machine learning, with an emphasis on statistics and computation. He is interested in formalizing the process of learning, in analyzing learning models, and in deriving and implementing emerging learning methods. A significant thrust of his research is in developing theoretical and algorithmic tools for online prediction, a learning framework where data arrives in a sequential fashion.

“I am honored to be the inaugural holder of the Distinguished Professorship in Data, Systems, and Society,” says Rakhlin. “Professor Larson’s commitment to education and service to MIT both serve as models to follow.”

A new security screener that people can simply walk past may soon be coming to an airport near you. Last year, U.S. airports nationwide began adopting HEXWAVE — a commercialized walkthrough security screening system based on microwave imaging technology developed at MIT Lincoln Laboratory — to satisfy a new Transportation Security Administration (TSA) mandate for enhanced employee screening to detect metallic and nonmetallic threats. The TSA is now in the process of evaluating HEXWAVE as a potential replacement of metal detectors to screen PreCheck passengers.

Typically, when you arrive at an airport security checkpoint line, you place your carry-on items on the conveyer belt, remove your shoes and any metallic items, and enter a body scanner. As you hold still for a few seconds with your feet spread apart and your arms extended over your head, the scanner creates a generic, featureless 3D body outline revealing any metallic or nonmetallic concealed weapons or other prohibited items.

Requiring individuals to stop, remove clothing and belongings, and pose for scans impedes traffic flow in airports and other highly populated venues, such as stadiums, shopping malls, mass transit stations, and schools. To enable more efficient screening of unstructured crowds and ensure public safety, the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) sponsored Lincoln Laboratory to prototype a high-resolution imaging system capable of scanning people and their belongings as they walk by. This R&D effort was conducted as part of S&T's Surface Transportation Explosive Threat Detection Program, which aims to provide the surface-transportation end user-community (e.g., mass transit) with a layered and integrated capability to detect threat items at the speed of the traveling public.

The laboratory's prototype microwave imager, which consists of a set of antennas installed on flat panels, operates under the same fundamental principle as existing body scanners: low-energy radio waves (less powerful than those transmitted by a cellphone) are transmitted from antennas toward a person's body and reflect off skin and any hidden objects; the reflected waves return to the antennas and are processed by a computer to create an image, which security personnel then review to identify any potential concealed threats.

The novelty of the laboratory's invention lies in its ability to discreetly handle a constant stream of subjects in motion, measuring each subject very quickly (within tens of milliseconds) and reconstructing 3D microwave images of each subject at a video rate. To meet these challenging requirements, the laboratory team developed a cost-effective antenna array and efficient image-reconstruction algorithms. Compared to existing systems, the laboratory's 3D microwave imager runs 100 times faster using the same computing hardware. In 2017, the team demonstrated the prototype's ability to detect various simulated threat items at varying distances on a rail platform at the Massachusetts Bay Transit Authority (MBTA) Emergency Training Center in Boston.

"The goal of our work is to provide security staff with more effective tools to protect public spaces. To that end, microwave imaging technology can quickly and unobtrusively provide visibility of items carried into a venue," says William Moulder, who led the technology's development at Lincoln Laboratory.

In 2018, the security company Liberty Defense licensed the imaging technology and entered into a cooperative research and development agreement (CRADA) with Lincoln Laboratory. Transitioning technology to industry for commercialization is part of the laboratory's role as a federally funded research and development center, and CRADAs provide a mechanism for such transition to happen. Through the CRADA, Liberty Defense maintained Lincoln Laboratory's core image-reconstruction intellectual property and made the technology enhancements required for commercialization, including an entirely new hardware architecture, radio frequency (RF) antenna modules, and a transceiver system that meets Federal Communications Commission waveform and RF performance requirements for indoor and outdoor operation. The co-organizational team facilitating the transition of the technology was recognized by the Federal Laboratory Consortium for Technology Transfer with a 2019 Excellence in Technology Transfer Award for the Northeast region.

By 2021, Liberty Defense had prototyped a walk-through security screening system, HEXWAVE. That same year, through the TSA's On-Person Screening Capability Program, Liberty Defense received a contract award to demonstrate HEXWAVE's enhanced threat-detection and high-throughput capabilities for screening aviation workers. Following successful testing of HEXWAVE at sports complexes, entertainment arenas, and shopping centers, both nationally and internationally, Liberty Defense began offering the product for sale.

"HEXWAVE is a great example of how federally funded R&D can be successfully transitioned to industry to meet real-world security needs," says Asha Rajagopal, the laboratory's chief technology transfer officer. "By working with Liberty Defense, we helped accelerate the delivery of a critical capability into the hands of those protecting public spaces."

In 2023, TSA began testing HEXWAVE as a potential replacement of metal detectors used to screen passengers in TSA PreCheck lanes. Airports across the United States started deploying HEXWAVE in 2024 to meet the TSA's employee screening mandate by the April 2026 deadline. Liberty Defense notes various other markets for HEXWAVE; the first units for commercial applications were delivered to Los Alamos National Laboratory in 2023, and the technology has since been deployed at other national labs, correctional facilities, government buildings, and courthouses.

"Liberty was extremely fortunate to license the technology from MIT Lincoln Laboratory," says Bill Frain, CEO of Liberty Defense. "From the outset, they've been a true partner — bringing not only deep innovation and technical expertise, but also a clear vision for commercial deployment. Together, we've successfully brought next-generation technology to market to help protect people in public spaces."

In addition to the typical rigors of MIT classes, Terrascope Subject 2.00C/1.016/EC.746 (Design for Complex Environmental Issues) poses some unusual hurdles for students to navigate: collaborating across time zones, bridging different cultural and institutional experiences, and trying to do hands-on work over Zoom. That’s because the class includes students from not only MIT, but also Diné College in Tsaile, Arizona, within the Navajo Nation, and the University of Puerto Rico-Ponce (UPRP).

Despite being thousands of miles apart, students work in teams to tackle a real-world problem for a client, based on the Terrascope theme for the year. “Understanding how to collaborate over long distances with people who are not like themselves will be an important item in many of these students’ toolbelts going forward, in some cases just as much as — or more than — any particular design technique,” says Ari Epstein, Terrascope associate director and senior lecturer. Over the past several years, Epstein has taught the class along with Joel Grimm of MIT Beaver Works and Libby Hsu of MIT D-Lab, as well instructors from the two collaborating institutions. Undergraduate teaching fellows from all three schools are also key members of the instructional staff.

Since the partnership began three years ago (initially with Diné College, with the addition of UPRP two years ago), the class themes have included food security and sustainable agriculture in Navajo Nation; access to reliable electrical power in Puerto Rico; and this year, increasing museum visitors’ engagement with artworks depicting mining and landscape alteration in Nevada.

Each team — which includes students from all three colleges — meets with clients online early in the term to understand their needs; then, through an iterative process, teams work on designing prototypes. During MIT’s spring break, teams travel to meet with the clients onsite to get feedback and continue to refine their prototypes. At the end of the term, students present their final products to the clients, an expert panel, and their communities at a hybrid showcase event held simultaneously on all three campuses.

Free-range design engineering

“I really loved the class,” says Graciela Leon, a second-year mechanical engineering major who took the subject in 2024. “It was not at all what I was expecting,” she adds. While the learning objectives on the syllabus are fairly traditional — using an iterative engineering design process, developing teamwork skills, and deepening communication skills, to name a few — the approach is not. “Terrascope is just kind of like throwing you into a real-world problem … it feels a lot more like you are being trusted with this actual challenge,” Leon says.

The 2024 challenge was to find a way to help the clients, Puerto Rican senior citizens, turn on gasoline-powered generators when the electrical power grid fails; some of them struggle with the pull cords necessary to start the generators. The students were tasked with designing solutions to make starting the generators easier.

Terrascope instructors teach fundamental skills such as iterative design spirals and scrum workflow frameworks, but they also give students ample freedom to follow their ideas. Leon admits she was a bit frustrated at first, because she wasn’t sure what she was supposed to be doing. “I wanted to be building things and thought, ‘Wow, I have to do all these other things, I have to write some kind of client profile and understand my client’s needs.’ I was just like, ‘Hand me a drill! I want to design something!’”

When he took the class last year, Uziel Rodriguez-Andujar was also thrown off initially by the independence teams had. Now a second-year UPRP student in mechanical engineering, he’s accustomed to lecture-based classes. “What I found so interesting is the way [they] teach the class, which is, ‘You make your own project, and we need you to find a solution to this. How it will look, and when you have it — that’s up to you,’” he says.

Clearing hurdles

Teaching the course on three different campuses introduces a number of challenges for students and instructors to overcome — among them, operating in three different time zones, overcoming language barriers, navigating different cultural and institutional norms, communicating effectively, and designing and building prototypes over Zoom.

“The culture span is huge,” explains Epstein. “There are different ways of speaking, different ways of listening, and each organization has different resources.”

First-year MIT student EJ Rodriguez found that one of the biggest obstacles was trying to convey ideas to teammates clearly. He took the class this year, when the theme revolved around the environmental impacts of lithium mining. The client, the Nevada Museum of Art, wanted to find ways to engage visitors with its artwork collection related to mining-related landscape changes.

Rodriguez and his team designed a pendulum with a light affixed to it that illuminates a painting by a Native American artist. When the pendulum swings, it changes how the visitor experiences the artwork. The team built parts for the pendulum on different campuses, and they reached a point where they realized their pieces were incompatible. “We had different visions of what we wanted for the project, and different vocabulary we were using to describe our ideas. Sometimes there would be a misunderstanding … It required a lot of honesty from each campus to be like, ‘OK, I thought we were doing exactly this,’ and obviously in a really respectful way.”

It’s not uncommon for students at Diné College and UPRP to experience an initial hurdle that their MIT peers do not. Epstein notes, “There’s a tendency for some folks outside MIT to see MIT students as these brilliant people that they don’t belong in the same room with.” But the other students soon realize not only that they can hold their own intellectually, but also that their backgrounds and experiences are incredibly valuable. “Their life experiences actually put them way ahead of many MIT students in some ways, when you think about design and fabrication, like repairing farm equipment or rebuilding transmissions,” he adds.

That’s how Cauy Bia felt when he took the class in 2024. Currently a first-year graduate student in biology at Diné College, Bia questioned whether he’d be on par with the MIT students. “I’ve grown up on a farm, and we do a lot of building, a lot of calculations, a lot of hands-on stuff. But going into this, I was sweating it so hard [wondering], ‘Am I smart enough to work with these students?’ And then, at the end of the day, that was never an issue,” he says.

The value of reflection

Every two weeks, Terrascope students write personal reflections about their experiences in the class, which helps them appreciate their academic and personal development. “I really felt that I had undergone a process that made me grow as an engineer,” says Leon. “I understood the importance of people and engineering more, including teamwork, working with clients, and de-centering the project away from what I wanted to build and design.”

When Bia began the semester, he says, he was more of a “make-or-break-type person” and tended to see things in black and white. “But working with all three campuses, it kind of opened up my thought process so I can assess more ideas, more voices and opinions. And I can get broader perspectives and get bigger ideas from that point,” he says. It was also a powerful experience culturally for him, particularly “drawing parallels between Navajo history, Navajo culture, and seeing the similarities between that and Puerto Rican culture, seeing how close we are as two nations.”

Rodriguez-Andujar gained an appreciation for the “constant struggle between simplicity and complexity” in engineering. “You have all these engineers trying to over-engineer everything,” he says. “And after you get your client feedback [halfway through the semester], it turns out, ‘Oh, that doesn’t work for me. I’m sorry — you have to scale it down like a hundred times and make it a lot simpler.’”

For instructors, the students’ reflections are invaluable as they strive to make improvements every year. In many ways, you might say the class is an iterative design spiral, too. “The past three years have themselves been prototypes,” Epstein says, “and all of the instructional staff are looking forward to continuing these exciting partnerships.”

MIT researchers have developed a new bionic knee that can help people with above-the-knee amputations walk faster, climb stairs, and avoid obstacles more easily than they could with a traditional prosthesis.

Unlike prostheses in which the residual limb sits within a socket, the new system is directly integrated with the user’s muscle and bone tissue. This enables greater stability and gives the user much more control over the movement of the prosthesis.

Participants in a small clinical study also reported that the limb felt more like a part of their own body, compared to people who had more traditional above-the-knee amputations.

“A prosthesis that's tissue-integrated — anchored to the bone and directly controlled by the nervous system — is not merely a lifeless, separate device, but rather a system that is carefully integrated into human physiology, offering a greater level of prosthetic embodiment. It’s not simply a tool that the human employs, but rather an integral part of self,” says Hugh Herr, a professor of media arts and sciences, co-director of the K. Lisa Yang Center for Bionics at MIT, an associate member of MIT’s McGovern Institute for Brain Research, and the senior author of the new study.

Tony Shu PhD ’24 is the lead author of the paper, which appears today in Science.

Better control

Over the past several years, Herr’s lab has been working on new prostheses that can extract neural information from muscles left behind after an amputation and use that information to help guide a prosthetic limb.

During a traditional amputation, pairs of muscles that take turns stretching and contracting are usually severed, disrupting the normal agonist-antagonist relationship of the muscles. This disruption makes it very difficult for the nervous system to sense the position of a muscle and how fast it’s contracting.

Using the new surgical approach developed by Herr and his colleagues, known as agonist-antagonist myoneuronal interface (AMI), muscle pairs are reconnected during surgery so that they still dynamically communicate with each other within the residual limb. This sensory feedback helps the wearer of the prosthesis to decide how to move the limb, and also generates electrical signals that can be used to control the prosthetic limb.

In a 2024 study, the researchers showed that people with amputations below the knee who received the AMI surgery were able to walk faster and navigate around obstacles much more naturally than people with traditional below-the-knee amputations.

In the new study, the researchers extended the approach to better serve people with amputations above the knee. They wanted to create a system that could not only read out signals from the muscles using AMI but also be integrated into the bone, offering more stability and better sensory feedback.

To achieve that, the researchers developed a procedure to insert a titanium rod into the residual femur bone at the amputation site. This implant allows for better mechanical control and load bearing than a traditional prosthesis. Additionally, the implant contains 16 wires that collect information from electrodes located on the AMI muscles inside the body, which enables more accurate transduction of the signals coming from the muscles.

This bone-integrated system, known as e-OPRA, transmits AMI signals to a new robotic controller developed specifically for this study. The controller uses this information to calculate the torque necessary to move the prosthesis the way that the user wants it to move.

“All parts work together to better get information into and out of the body and better interface mechanically with the device,” Shu says. “We’re directly loading the skeleton, which is the part of the body that’s supposed to be loaded, as opposed to using sockets, which is uncomfortable and can lead to frequent skin infections.”

In this study, two subjects received the combined AMI and e-OPRA system, known as an osseointegrated mechanoneural prosthesis (OMP). These users were compared with eight who had the AMI surgery but not the e-OPRA implant, and seven users who had neither AMI nor e-OPRA. All subjects took a turn at using an experimental powered knee prosthesis developed by the lab.

The researchers measured the participants’ ability to perform several types of tasks, including bending the knee to a specified angle, climbing stairs, and stepping over obstacles. In most of these tasks, users with the OMP system performed better than the subjects who had the AMI surgery but not the e-OPRA implant, and much better than users of traditional prostheses.

“This paper represents the fulfillment of a vision that the scientific community has had for a long time — the implementation and demonstration of a fully physiologically integrated, volitionally controlled robotic leg,” says Michael Goldfarb, a professor of mechanical engineering and director of the Center for Intelligent Mechatronics at Vanderbilt University, who was not involved in the research. “This is really difficult work, and the authors deserve tremendous credit for their efforts in realizing such a challenging goal.”

A sense of embodiment

In addition to testing gait and other movements, the researchers also asked questions designed to evaluate participants’ sense of embodiment — that is, to what extent their prosthetic limb felt like a part of their own body.

Questions included whether the patients felt as if they had two legs, if they felt as if the prosthesis was part of their body, and if they felt in control of the prosthesis. Each question was designed to evaluate the participants’ feelings of agency, ownership of device, and body representation.

The researchers found that as the study went on, the two participants with the OMP showed much greater increases in their feelings of agency and ownership than the other subjects.

“Another reason this paper is significant is that it looks into these embodiment questions and it shows large improvements in that sensation of embodiment,” Herr says. “No matter how sophisticated you make the AI systems of a robotic prosthesis, it’s still going to feel like a tool to the user, like an external device. But with this tissue-integrated approach, when you ask the human user what is their body, the more it’s integrated, the more they’re going to say the prosthesis is actually part of self.”

The AMI procedure is now done routinely on patients with below-the-knee amputations at Brigham and Women’s Hospital, and Herr expects it will soon become the standard for above-the-knee amputations as well. The combined OMP system will need larger clinical trials to receive FDA approval for commercial use, which Herr expects may take about five years.

The research was funded by the Yang Tan Collective and DARPA.

As spaceflight becomes more affordable and accessible, the story of human life in space is just beginning. Aurelia Institute wants to make sure that future benefits all of humanity — whether in space or here on Earth.

Founded by Ariel Ekblaw SM ’17, PhD ’20; Danielle DeLatte ’11; and former MIT research scientist Sana Sharma, the nonprofit institute serves as a research lab for space technology and architecture, a center for education and outreach, and a policy hub dedicated to inspiring more people to work in the space industry.

At the heart of the Aurelia Institute’s mission is a commitment to making space accessible to all people. A big part of that work involves annual microgravity flights that Ekblaw says are equal part research missions, workforce training, and inspiration for the next generation of space enthusiasts.

“We’ve done that every year,” Ekblaw says of the flights. “We now have multiple cohorts of students that connect across years. It brings together people from very different backgrounds. We’ve had artists, designers, architects, ethicists, teachers, and others fly with us. In our R&D, we are interested in space infrastructure for the public good. That’s why we’re directing our technology portfolios toward near-term, massive infrastructure projects in low-Earth orbit that benefit life on Earth.”

From the annual flights to the Institute’s self-assembling space architecture technology known as TESSERAE, much of Aurelia’s work is an extension of projects Ekblaw started as a graduate student at MIT.

“My life trajectory changed when I came to MIT,” says Ekblaw, who is still a visiting researcher at MIT. “I am incredibly grateful for the education I got in the Media Lab and the Department of Aeronautics and Astronautics. MIT is what gave me the skill, the technology, and the community to be able to spin out Aurelia and do something important in the space industry at scale.”

“MIT changes lives”

Ekblaw has always been passionate about space. As an undergraduate at Yale University, she took part in a NASA microgravity flight as part of a research project. In the first year of her PhD program at MIT, she led the launch of the Space Exploration Initiative, a cross-Institute effort to drive innovation at the frontiers of space exploration. The ongoing initiative started as a research group but soon raised enough money to conduct microgravity flights and, more recently, conduct missions to the International Space Station and the moon.

“The Media Lab was like magic in the years I was there,” Ekblaw says. “It had this sense of what we used to call ‘anti-disciplinary permission-lessness.’ You could get funding to explore really different and provocative ideas. Our mission was to democratize access to space.”

In 2016, while taking a class taught by Neri Oxman, then a professor in the Media Lab, Ekblaw got the idea for the TESSERAE Project, in which tiles autonomously self-assemble into spherical space structures.

“I was thinking about the future of human flight, and the class was a seeding moment for me,” Ekblaw says. “I realized self-assembly works OK on Earth, it works particularly well at small scales like in biology, but it generally struggles with the force of gravity once you get to larger objects. But microgravity in space was a perfect application for self-assembly.”

That semester, Ekblaw was also taking Professor Neil Gershenfeld’s class MAS.863 (How to Make (Almost) Anything), where she began building prototypes. Over the ensuing years of her PhD, subsequent versions of the TESSERAE system were tested on microgravity flights run by the Space Exploration Initiative, in a suborbital mission with the space company Blue Origin, and as part of a 30-day mission aboard the International Space Station.

“MIT changes lives,” Ekblaw says. “It completely changed my life by giving me access to real spaceflight opportunities. The capstone data for my PhD was from an International Space Station mission.”

After earning her PhD in 2020, Ekblaw decided to ask two researchers from the MIT community and the Space Exploration Initiative, Danielle DeLatte and Sana Sharma, to partner with her to further develop research projects, along with conducting space education and policy efforts. That collaboration turned into Aurelia.

“I wanted to scale the work I was doing with the Space Exploration Initiative, where we bring in students, introduce them to zero-g flights, and then some graduate to sub-orbital, and eventually flights to the International Space Station,” Ekblaw says. “What would it look like to bring that out of MIT and bring that opportunity to other students and mid-career people from all walks of life?”

Every year, Aurelia charters a microgravity flight, bringing about 25 people along to conduct 10 to 15 experiments. To date, nearly 200 people have participated in the flights across the Space Exploration Initiative and Aurelia, and more than 70 percent of those fliers have continued to pursue activities in the space industry post-flight.

Aurelia also offers open-source classes on designing research projects for microgravity environments and contributes to several education and community-building activities across academia, industry, and the arts.

In addition to those education efforts, Aurelia has continued testing and improving the TESSERAE system. In 2022, TESSERAE was brought on the first private mission to the International Space Station, where astronauts conducted tests around the system’s autonomous self-assembly, disassembly, and stability. Aurelia will return to the International Space Station in early 2026 for further testing as part of a recent grant from NASA.

The work led Aurelia to recently spin off the TESSERAE project into a separate, for-profit company. Ekblaw expects there to be more spinoffs out of Aurelia in coming years.

Designing for space, and Earth

The self-assembly work is only one project in Aurelia’s portfolio. Others are focused on designing human-scale pavilions and other habitats, including a space garden and a massive, 20-foot dome depicting the interior of space architectures in the future. This space habitat pavilion was recently deployed as part of a six-month exhibit at the Seattle Museum of Flight.

“The architectural work is asking, ‘How are we going to outfit these systems and actually make the habitats part of a life worth living?’” Ekblaw explains.

With all of its work, Aurelia’s team looks at space as a testbed to bring new technologies and ideas back to our own planet.

“When you design something for the rigors of space, you often hit on really robust technologies for Earth,” she says.

Generative artificial intelligence is transforming the ways humans write, read, speak, think, empathize, and act within and across languages and cultures. In health care, gaps in communication between patients and practitioners can worsen patient outcomes and prevent improvements in practice and care. The Language/AI Incubator, made possible through funding from the MIT Human Insight Collaborative (MITHIC), offers a potential response to these challenges. 

The project envisions a research community rooted in the humanities that will foster interdisciplinary collaboration across MIT to deepen understanding of generative AI’s impact on cross-linguistic and cross-cultural communication. The project’s focus on health care and communication seeks to build bridges across socioeconomic, cultural, and linguistic strata.

The incubator is co-led by Leo Celi, a physician and the research director and senior research scientist with the Institute for Medical Engineering and Science (IMES), and Per Urlaub, professor of the practice in German and second language studies and director of MIT’s Global Languages program. 

“The basis of health care delivery is the knowledge of health and disease,” Celi says. “We’re seeing poor outcomes despite massive investments because our knowledge system is broken.”

A chance collaboration

Urlaub and Celi met during a MITHIC launch event. Conversations during the event reception revealed a shared interest in exploring improvements in medical communication and practice with AI.

“We’re trying to incorporate data science into health-care delivery,” Celi says. “We’ve been recruiting social scientists [at IMES] to help advance our work, because the science we create isn’t neutral.”

Language is a non-neutral mediator in health care delivery, the team believes, and can be a boon or barrier to effective treatment. “Later, after we met, I joined one of his working groups whose focus was metaphors for pain: the language we use to describe it and its measurement,” Urlaub continues. “One of the questions we considered was how effective communication can occur between doctors and patients.”

Technology, they argue, impacts casual communication, and its impact depends on both users and creators. As AI and large language models (LLMs) gain power and prominence, their use is broadening to include fields like health care and wellness. 

Rodrigo Gameiro, a physician and researcher with MIT’s Laboratory for Computational Physiology, is another program participant. He notes that work at the laboratory centers responsible AI development and implementation. Designing systems that leverage AI effectively, particularly when considering challenges related to communicating across linguistic and cultural divides that can occur in health care, demands a nuanced approach. 

“When we build AI systems that interact with human language, we’re not just teaching machines how to process words; we’re teaching them to navigate the complex web of meaning embedded in language,” Gameiro says.

Language’s complexities can impact treatment and patient care. “Pain can only be communicated through metaphor,” Urlaub continues, “but metaphors don’t always match, linguistically and culturally.” Smiley faces and one-to-10 scales — pain measurement tools English-speaking medical professionals may use to assess their patients — may not travel well across racial, ethnic, cultural, and language boundaries.

“Science has to have a heart” 

LLMs can potentially help scientists improve health care, although there are some systemic and pedagogical challenges to consider. Science can focus on outcomes to the exclusion of the people it’s meant to help, Celi argues. “Science has to have a heart,” he says. “Measuring students’ effectiveness by counting the number of papers they publish or patents they produce misses the point.”

The point, Urlaub says, is to investigate carefully while simultaneously acknowledging what we don’t know, citing what philosophers call Epistemic Humility. Knowledge, the investigators argue, is provisional, and always incomplete. Deeply held beliefs may require revision in light of new evidence. 

“No one’s mental view of the world is complete,” Celi says. “You need to create an environment in which people are comfortable acknowledging their biases.”

“How do we share concerns between language educators and others interested in AI?” Urlaub asks. “How do we identify and investigate the relationship between medical professionals and language educators interested in AI’s potential to aid in the elimination of gaps in communication between doctors and patients?” 

Language, in Gameiro’s estimation, is more than just a tool for communication. “It reflects culture, identity, and power dynamics,” he says. In situations where a patient might not be comfortable describing pain or discomfort because of the physician’s position as an authority, or because their culture demands yielding to those perceived as authority figures, misunderstandings can be dangerous. 

Changing the conversation

AI’s facility with language can help medical professionals navigate these areas more carefully, providing digital frameworks offering valuable cultural and linguistic contexts in which patient and practitioner can rely on data-driven, research-supported tools to improve dialogue. Institutions need to reconsider how they educate medical professionals and invite the communities they serve into the conversation, the team says. 

‘We need to ask ourselves what we truly want,” Celi says. “Why are we measuring what we’re measuring?” The biases we bring with us to these interactions — doctors, patients, their families, and their communities — remain barriers to improved care, Urlaub and Gameiro say.

“We want to connect people who think differently, and make AI work for everyone,” Gameiro continues. “Technology without purpose is just exclusion at scale.”

“Collaborations like these can allow for deep processing and better ideas,” Urlaub says.

Creating spaces where ideas about AI and health care can potentially become actions is a key element of the project. The Language/AI Incubator hosted its first colloquium at MIT in May, which was led by Mena Ramos, a physician and the co-founder and CEO of the Global Ultrasound Institute. 

The colloquium also featured presentations from Celi, as well as Alfred Spector, a visiting scholar in MIT’s Department of Electrical Engineering and Computer Science, and Douglas Jones, a senior staff member in the MIT Lincoln Laboratory’s Human Language Technology Group. A second Language/AI Incubator colloquium is planned for August.

Greater integration between the social and hard sciences can potentially increase the likelihood of developing viable solutions and reducing biases. Allowing for shifts in the ways patients and doctors view the relationship, while offering each shared ownership of the interaction, can help improve outcomes. Facilitating these conversations with AI may speed the integration of these perspectives. 

“Community advocates have a voice and should be included in these conversations,” Celi says. “AI and statistical modeling can’t collect all the data needed to treat all the people who need it.”

Community needs and improved educational opportunities and practices should be coupled with cross-disciplinary approaches to knowledge acquisition and transfer. The ways people see things are limited by their perceptions and other factors. “Whose language are we modeling?” Gameiro asks about building LLMs. “Which varieties of speech are being included or excluded?” Since meaning and intent can shift across those contexts, it’s important to remember these when designing AI tools. 

“AI is our chance to rewrite the rules”

While there’s lots of potential in the collaboration, there are serious challenges to overcome, including establishing and scaling the technological means to improve patient-provider communication with AI, extending opportunities for collaboration to marginalized and underserved communities, and reconsidering and revamping patient care. 

But the team isn’t daunted.

Celi believes there are opportunities to address the widening gap between people and practitioners while addressing gaps in health care. “Our intent is to reattach the string that’s been cut between society and science,” he says. “We can empower scientists and the public to investigate the world together while also acknowledging the limitations engendered in overcoming their biases.”

Gameiro is a passionate advocate for AI’s ability to change everything we know about medicine. “I’m a medical doctor, and I don’t think I’m being hyperbolic when I say I believe AI is our chance to rewrite the rules of what medicine can do and who we can reach,” he says.

“Education changes humans from objects to subjects,” Urlaub argues, describing the difference between disinterested observers and active and engaged participants in the new care model he hopes to build. “We need to better understand technology’s impact on the lines between these states of being.”

Celi, Gameiro, and Urlaub each advocate for MITHIC-like spaces across health care, places where innovation and collaboration are allowed to occur without the kinds of arbitrary benchmarks institutions have previously used to mark success.

“AI will transform all these sectors,” Urlaub believes. “MITHIC is a generous framework that allows us to embrace uncertainty with flexibility.”

“We want to employ our power to build community among disparate audiences while admitting we don’t have all the answers,” Celi says. “If we fail, it’s because we failed to dream big enough about how a reimagined world could look.”

Marine scientists have long marveled at how animals like fish and seals swim so efficiently despite having different shapes. Their bodies are optimized for efficient, hydrodynamic aquatic navigation so they can exert minimal energy when traveling long distances.

Autonomous vehicles can drift through the ocean in a similar way, collecting data about vast underwater environments. However, the shapes of these gliding machines are less diverse than what we find in marine life — go-to designs often resemble tubes or torpedoes, since they’re fairly hydrodynamic as well. Plus, testing new builds requires lots of real-world trial-and-error.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the University of Wisconsin at Madison propose that AI could help us explore uncharted glider designs more conveniently. Their method uses machine learning to test different 3D designs in a physics simulator, then molds them into more hydrodynamic shapes. The resulting model can be fabricated via a 3D printer using significantly less energy than hand-made ones.

The MIT scientists say that this design pipeline could create new, more efficient machines that help oceanographers measure water temperature and salt levels, gather more detailed insights about currents, and monitor the impacts of climate change. The team demonstrated this potential by producing two gliders roughly the size of a boogie board: a two-winged machine resembling an airplane, and a unique, four-winged object resembling a flat fish with four fins.

Peter Yichen Chen, MIT CSAIL postdoc and co-lead researcher on the project, notes that these designs are just a few of the novel shapes his team’s approach can generate. “We’ve developed a semi-automated process that can help us test unconventional designs that would be very taxing for humans to design,” he says. “This level of shape diversity hasn’t been explored previously, so most of these designs haven’t been tested in the real world.”

But how did AI come up with these ideas in the first place? First, the researchers found 3D models of over 20 conventional sea exploration shapes, such as submarines, whales, manta rays, and sharks. Then, they enclosed these models in “deformation cages” that map out different articulation points that the researchers pulled around to create new shapes.

The CSAIL-led team built a dataset of conventional and deformed shapes before simulating how they would perform at different “angles-of-attack” — the direction a vessel will tilt as it glides through the water. For example, a swimmer may want to dive at a -30 degree angle to retrieve an item from a pool.

These diverse shapes and angles of attack were then used as inputs for a neural network that essentially anticipates how efficiently a glider shape will perform at particular angles and optimizes it as needed.

Giving gliding robots a lift

The team’s neural network simulates how a particular glider would react to underwater physics, aiming to capture how it moves forward and the force that drags against it. The goal: find the best lift-to-drag ratio, representing how much the glider is being held up compared to how much it’s being held back. The higher the ratio, the more efficiently the vehicle travels; the lower it is, the more the glider will slow down during its voyage.

Lift-to-drag ratios are key for flying planes: At takeoff, you want to maximize lift to ensure it can glide well against wind currents, and when landing, you need sufficient force to drag it to a full stop.

Niklas Hagemann, an MIT graduate student in architecture and CSAIL affiliate, notes that this ratio is just as useful if you want a similar gliding motion in the ocean.

“Our pipeline modifies glider shapes to find the best lift-to-drag ratio, optimizing its performance underwater,” says Hagemann, who is also a co-lead author on a paper that was presented at the International Conference on Robotics and Automation in June. “You can then export the top-performing designs so they can be 3D-printed.”

Going for a quick glide

While their AI pipeline seemed realistic, the researchers needed to ensure its predictions about glider performance were accurate by experimenting in more lifelike environments.

They first fabricated their two-wing design as a scaled-down vehicle resembling a paper airplane. This glider was taken to MIT’s Wright Brothers Wind Tunnel, an indoor space with fans that simulate wind flow. Placed at different angles, the glider’s predicted lift-to-drag ratio was only about 5 percent higher on average than the ones recorded in the wind experiments — a small difference between simulation and reality.

A digital evaluation involving a visual, more complex physics simulator also supported the notion that the AI pipeline made fairly accurate predictions about how the gliders would move. It visualized how these machines would descend in 3D.

To truly evaluate these gliders in the real world, though, the team needed to see how their devices would fare underwater. They printed two designs that performed the best at specific points-of-attack for this test: a jet-like device at 9 degrees and the four-wing vehicle at 30 degrees.

Both shapes were fabricated in a 3D printer as hollow shells with small holes that flood when fully submerged. This lightweight design makes the vehicle easier to handle outside of the water and requires less material to be fabricated. The researchers placed a tube-like device inside these shell coverings, which housed a range of hardware, including a pump to change the glider’s buoyancy, a mass shifter (a device that controls the machine’s angle-of-attack), and electronic components.

Each design outperformed a handmade torpedo-shaped glider by moving more efficiently across a pool. With higher lift-to-drag ratios than their counterpart, both AI-driven machines exerted less energy, similar to the effortless ways marine animals navigate the oceans.

As much as the project is an encouraging step forward for glider design, the researchers are looking to narrow the gap between simulation and real-world performance. They are also hoping to develop machines that can react to sudden changes in currents, making the gliders more adaptable to seas and oceans.

Chen adds that the team is looking to explore new types of shapes, particularly thinner glider designs. They intend to make their framework faster, perhaps bolstering it with new features that enable more customization, maneuverability, or even the creation of miniature vehicles.

Chen and Hagemann co-led research on this project with OpenAI researcher Pingchuan Ma SM ’23, PhD ’25. They authored the paper with Wei Wang, a University of Wisconsin at Madison assistant professor and recent CSAIL postdoc; John Romanishin ’12, SM ’18, PhD ’23; and two MIT professors and CSAIL members: lab director Daniela Rus and senior author Wojciech Matusik. Their work was supported, in part, by a Defense Advanced Research Projects Agency (DARPA) grant and the MIT-GIST Program.

Common sense tells us to run from molten lava flowing from active volcanoes. But MIT professors J. Jih, Cristina Parreño Alonso, and Skylar Tibbits — faculty in the Department of Architecture at the School of Architecture and Planning — have their bags packed to head to southwest Iceland in anticipation of an imminent volcanic eruption. The Nordic island nation is currently experiencing a period of intense seismic activity; seven volcanic eruptions have taken place in its southern peninsula in under a year.

Earlier this year, the faculty built and placed a series of lightweight, easily deployable steel structures close to the volcano, where a few of the recent eruptions have taken place; several more structures are on trucks waiting to be delivered to sites where fissures open and lava oozes out. Cameras are in place to record what happens when the lava meets and hits these structures to help understand the lava flows.

This new research explores what type of shapes and materials can be used to interact with lava and successfully divert it from heading in the direction of habitats or critical infrastructure that lie in its path. Their work is supported by a Professor Amar. G. Bose Research Grant.

“We’re trying to imagine new ways of conceptualizing infrastructure when it relates to lava and volcanic eruptions,” says Jih, an associate professor of the practice. “Lovely for us as designers, physical prototyping is the only way you can test some of these ideas out.” 

Currently, the Icelandic Department of Civic Protection and Emergency Management and an engineering group, EFLA, are diverting the lava with massive berms (approximately 44 to 54 yards in length and 9 yards in height) made from earth and stone.

Berms protecting the town of Grindavik, a power plant, and the popular Blue Lagoon geothermal spa have met with mixed results. In November 2024, a volcano erupted for the seventh time in less than a year, forcing the evacuation of town residents and the Blue Lagoon’s guests and employees. The latter’s parking lot was consumed by lava.

Sigurdur Thorsteinsson, chief brand, design, and innovation officer of the Blue Lagoon, as well as a designer and a partner in Design Group Italia, was on site for this eruption and several others.

“Some magma went into the city of Grindavik and three or four houses were destroyed,” says Thorsteinsson. “One of our employees watched her house go under magma on television, which was an emotional moment.”

While staff at the Blue Lagoon have become very efficient at evacuating guests, says Thorsteinsson, each eruption forces the tourist destination to close and townspeople to evacuate, disrupting lives and livelihoods.

“You cannot really stop the magma,” says Thorsteinsson, who is working with the MIT faculty on this research project. “It’s too powerful.”

Tibbits, associate professor of design research and founder and co-director of the Self-Assembly Lab, agrees. His research explores how to guide or work with the forces of nature.

Last year, Tibbits and Jih were in Iceland on another research project when erupting volcanoes interrupted their work. The two started thinking about how the lava could be redirected.

“The question is: Can we find more strategic interventions in the field that could work with the lava, rather than fight it?” says Tibbits.

To investigate what kinds of materials would withstand this type of interaction, they invited Parreño Alonso, a senior lecturer in the Department of Architecture, to join them.

“Cristina, being the department authority on magma, was an obvious and important partner for us,” says Jih with a smile.

Parreño Alonso has been working with volcanic rock for years and taught a series of design studios exploring volcanic rock as an architectural material. She also has proposed designing structures to engage directly with lava flows and recently has been examining volcanic rock in a molten state and melting basalt in MIT’s foundry with Michael Tarkanian, a senior lecturer in MIT’s Department of Materials Science and Engineering, and Metals Lab director. For this project, she is exploring the potential of molten rock as a substitute for concrete, a widely used material because of its pliability.

“It’s exciting how this idea of working with volcanoes was taking shape in parallel, from different angles, within the same department,” says Parreño Alonso. “I love how these parallel interests have led to such a beautiful collaboration.”

She also sees other opportunities by collaborating with these forces of nature.

“We are interested in the potential of generating something out of the interaction with the lava,” she says. “Could it be a landscape that becomes a park? There are many possibilities.”

The steel structures were first tested at MIT’s Metals Lab with Tarkanian and then built onsite in Iceland. The team wanted to make the structures lightweight so they could be quickly set up in the field, but strong enough so they wouldn’t be easily destroyed. Various designs were created; this iteration of the design has V-shaped structures that can guide the lava to flow around them, or they can be reconfigured as ramps or tunnels.

“There is a road that has been hit by many of the recent eruptions and must keep being rebuilt,” says Tibbits. “We created two ramps that could in the future serve as tunnels, allowing the lava to flow over the road and create a type of lava cave where the cars could drive under the cooled lava.”

Tibbits says they see the structures in the field now as an initial intervention. After documenting and studying how they interact with the lava, the architects will develop new iterations of what they believe will eventually become critical infrastructure for locations around the world with active volcanoes.

“If we can show and prove what kinds of shapes and structures and what kinds of materials can divert magma flows, I think it’s incredibly valuable research,” says Thorsteinsson.

Thorsteinsson lives in Italy half of the year and says the volcanoes there — Mount Etna in Sicily and Mount Vesuvius in the Gulf of Naples — pose a greater danger than those in Iceland because of the densely populated neighborhoods nearby. Volcanoes in Hawaii and Japan are in similarly populated areas.

“Whatever information you can learn about diverting magma flows to other directions and what kinds of structures are needed — it would be priceless,” he says.

For people with Type 1 diabetes, developing hypoglycemia, or low blood sugar, is an ever-present threat. When glucose levels become extremely low, it creates a life-threatening situation for which the standard treatment of care is injecting a hormone called glucagon.

As an emergency backup, for cases where patients may not realize that their blood sugar is dropping to dangerous levels, MIT engineers have designed an implantable reservoir that can remain under the skin and be triggered to release glucagon when blood sugar levels get too low.

This approach could also help in cases where hypoglycemia occurs during sleep, or for diabetic children who are unable to administer injections on their own.

“This is a small, emergency-event device that can be placed under the skin, where it is ready to act if the patient’s blood sugar drops too low,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering, a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science (IMES), and the senior author of the study. “Our goal was to build a device that is always ready to protect patients from low blood sugar. We think this can also help relieve the fear of hypoglycemia that many patients, and their parents, suffer from.”

The researchers showed that this device could also be used to deliver emergency doses of epinephrine, a drug that is used to treat heart attacks and can also prevent severe allergic reactions, including anaphylactic shock.

Siddharth Krishnan, a former MIT research scientist who is now an assistant professor of electrical engineering at Stanford University, is the lead author of the study, which appears today in Nature Biomedical Engineering.

Emergency response

Most patients with type 1 diabetes use daily insulin injections to help their body absorb sugar and prevent their blood sugar levels from getting too high. However, if their blood sugar levels get too low, they develop hypoglycemia, which can lead to confusion and seizures, and may be fatal if it goes untreated.

To combat hypoglycemia, some patients carry preloaded syringes of glucagon, a hormone that stimulates the liver to release glucose into the bloodstream. However, it isn’t always easy for people, especially children, to know when they are becoming hypoglycemic.

“Some patients can sense when they’re getting low blood sugar, and go eat something or give themselves glucagon,” Anderson says. “But some are unaware that they’re hypoglycemic, and they can just slip into confusion and coma. This is also a problem when patients sleep, as they are reliant on glucose sensor alarms to wake them when sugar drops dangerously low.”

To make it easier to counteract hypoglycemia, the MIT team set out to design an emergency device that could be triggered either by the person using it, or automatically by a sensor.

The device, which is about the size of a quarter, contains a small drug reservoir made of a 3D-printed polymer. The reservoir is sealed with a special material known as a shape-memory alloy, which can be programmed to change its shape when heated. In this case, the researcher used a nickel-titanium alloy that is programmed to curl from a flat slab into a U-shape when heated to 40 degrees Celsius.

Like many other protein or peptide drugs, glucagon tends to break down quickly, so the liquid form can’t be stored long-term in the body. Instead, the MIT team created a powdered version of the drug, which remains stable for much longer and stays in the reservoir until released.

Each device can carry either one or four doses of glucagon, and it also includes an antenna tuned to respond to a specific frequency in the radiofrequency range. That allows it to be remotely triggered to turn on a small electrical current, which is used to heat the shape-memory alloy. When the temperature reaches the 40-degree threshold, the slab bends into a U shape, releasing the contents of the reservoir.

Because the device can receive wireless signals, it could also be designed so that drug release is triggered by a glucose monitor when the wearer’s blood sugar drops below a certain level.

“One of the key features of this type of digital drug delivery system is that you can have it talk to sensors,” Krishnan says. “In this case, the continuous glucose-monitoring technology that a lot of patients use is something that would be easy for these types of devices to interface with.”

Reversing hypoglycemia

After implanting the device in diabetic mice, the researchers used it to trigger glucagon release as the animals’ blood sugar levels were dropping. Within less than 10 minutes of activating the drug release, blood sugar levels began to level off, allowing them to remain within the normal range and avert hypoglycemia.

The researchers also tested the device with a powdered version of epinephrine. They found that within 10 minutes of drug release, epinephrine levels in the bloodstream became elevated and heart rate increased.

In this study, the researchers kept the devices implanted for up to four weeks, but they now plan to see if they can extend that time up to at least a year.

“The idea is you would have enough doses that can provide this therapeutic rescue event over a significant period of time. We don’t know exactly what that is — maybe a year, maybe a few years, and we’re currently working on establishing what the optimal lifetime is. But then after that, it would need to be replaced,” Krishnan says.

Typically, when a medical device is implanted in the body, scar tissue develops around the device, which can interfere with its function. However, in this study, the researchers showed that even after fibrotic tissue formed around the implant, they were able to successfully trigger the drug release.

The researchers are now planning for additional animal studies and hope to begin testing the device in clinical trials within the next three years.

“It’s really exciting to see our team accomplish this, which I hope will someday help diabetic patients and could more broadly provide a new paradigm for delivering any emergency medicine,” says Robert Langer, the David H. Koch Institute Professor at MIT and an author of the paper.

Other authors of the paper include Laura O’Keeffe, Arnab Rudra, Derin Gumustop, Nima Khatib, Claudia Liu, Jiawei Yang, Athena Wang, Matthew Bochenek, Yen-Chun Lu, Suman Bose, and Kaelan Reed.

The research was funded by the Leona M. and Harry B. Helmsley Charitable Trust, the National Institutes of Health, a JDRF postdoctoral fellowship, and the National Institute of Biomedical Imaging and Bioengineering.

The first time Steve Jobs held a public demo of the Apple Macintosh, in early 1984, scripted jokes were part of the rollout. First, Jobs pulled the machine out of a bag. Then, using speech technology from Samsung, the Macintosh made a quip about rival IBM’s mainframes: “Never trust a computer you can’t lift.”

There’s a reason Jobs was doing that. For the first few decades that computing became part of cultural life, starting in the 1950s, computers seemed unfriendly, grim, and liable to work against human interests. Take the 1968 film “2001: A Space Odyssey,” in which the onboard computer, HAL, turns against the expedition’s astronauts. It’s a famous cultural touchstone. Jobs, in selling the idea of a personal computer, was using humor to ease concerns about the machines.

“Against the sense of computing as cold and numbers-driven, the fact that this computer was using voice technology to deliver jokes made it seem less forbidding, less evil,” says MIT scholar Benjamin Mangrum.

In fact, this dynamic turns up throughout modern culture, in movies, television, fiction, and the theater. We often deal with our doubts and fears about computing through humor, whether reconciling ourselves to machines or critiquing them. Now, Mangrum analyzes this phenomenon in a new book, “The Comedy of Computation: Or, How I Learned to Stop Worrying and Love Obsolescence,” published this month by Stanford University Press.

“Comedy has been a form for making this technology seem ordinary,” says Mangrum, an associate professor in MIT’s literature program. “Where in other circumstances computing might seem inhuman or impersonal, comedy allows us to incorporate it into our lives in a way that makes it make sense.”

Reversals of fortune

Mangrum’s interest in the subject was sparked partly by William Marchant’s 1955 play, “The Desk Set” — a romantic comedy later turned into a film starring Katharine Hepburn and Spencer Tracy — which queries, among other things, how office workers will co-exist alongside computers.

Perhaps against expectations, romantic comedies have turned out to be one of the most prominent contemporary forms of culture that grapple with technology and its effects on us. Mangrum, in the book, explains why: Their plot structure often involves reversals, which sometimes are extended to technology, too. Computing might seem forbidding, but it might also pull people together.

“One of the common tropes about romantic comedies is that there are characters or factors in the drama that obstruct the happy union of two people,” Mangrum observes. “And often across the arc of the drama, the obstruction or obstructive character is transformed into a partner, or collaborator, and assimilated within the happy couple’s union. That provides a template for how some cultural producers want to present the experience of computing. It begins as an obstruction and ends as a partner.”

That plot structure, Mangrum notes, dates to antiquity and was common in Shakespeare’s day. Still, as he writes in the book, there is “no timeless reality called Comedy,” as the vehicles and forms of it change over time. Beyond that, specific jokes about computing can quickly become outmoded. Steve Jobs made fun of mainframes, and the 1998 Nora Ephron comedy “You’ve Got Mail” got laughs out of dial-up modems, but those jokes might leave most people puzzled today.

“Comedy is not a fixed resource,” Mangrum says. “It’s an ever-changing toolbox.”

Continuing this evolution into the 21st century, Mangrum observes that a lot of computational comedy centers on an entire category of commentary he calls “the Great Tech-Industrial Joke.” This focuses on the gap between noble-sounding declared aspirations of technology and the sometimes-dismal outcomes it creates.

Social media, for instance, promised new worlds of connectivity and social exploration, and has benefits people enjoy — but it has also generated polarization, misinformation, and toxicity. Technology’s social effects are complex. Whole televisions shows, such as “Silicon Valley,” have dug into this terrain.

“The tech industry announces that some of its products have revolutionary or utopian aims, but the achievements of many of them fall far short of that,” Mangrum says. “It’s a funny setup for a joke. People have been claiming we’re saving the world, when actually we’re just processing emails faster. But it’s a mode of criticism aimed at big tech, since its products are more complicated.”

A complicated, messy picture

“The Comedy of Computation” digs into several other facets of modern culture and technology. The notion of personal authenticity, as Mangrum observes, is a fairly recent and modern construct in society — and it’s another sphere of life that collides with computing, since social media is full of charges of inauthenticity.

“That ethics of authenticity connects to comedy, as we make jokes about people not being authentic,” Mangrum says.

“The Comedy of Computation” has received praise from other scholars. Mark Goble, a professor of English at the University of California at Berkeley, has called it “essential for understanding the technological world in its complexity, absurdity, and vibrancy.”

For his part, Mangrum emphasizes that his book is an exploration of the full complexity of technology, culture, and society.

“There’s this really complicated, messy picture,” Mangrum says. “And comedy sometimes finds a way of experiencing and finding pleasure in that messiness, and other times it neatly wraps it up in a lesson that can make things neater than they actually are.”

Mangrum adds that the book focuses on “the combination of the threat and pleasure that’s involved across the history of the computer, in the ways it’s been assimilated and shaped society, with real advances and benefits, along with real threats, for instance to employment. I’m interested in the duality, the simultaneous and seemingly conflicting features of that experience.”

For all their impressive capabilities, large language models (LLMs) often fall short when given challenging new tasks that require complex reasoning skills.

While an accounting firm’s LLM might excel at summarizing financial reports, that same model could fail unexpectedly if tasked with predicting market trends or identifying fraudulent transactions.

To make LLMs more adaptable, MIT researchers investigated how a certain training technique can be strategically deployed to boost a model’s performance on unfamiliar, difficult problems.

They show that test-time training, a method that involves temporarily updating some of a model’s inner workings during deployment, can lead to a sixfold improvement in accuracy. The researchers developed a framework for implementing a test-time training strategy that uses examples of the new task to maximize these gains.

Their work could improve a model’s flexibility, enabling an off-the-shelf LLM to adapt to complex tasks that require planning or abstraction. This could lead to LLMs that would be more accurate in many applications that require logical deduction, from medical diagnostics to supply chain management.

“Genuine learning — what we did here with test-time training — is something these models can’t do on their own after they are shipped. They can’t gain new skills or get better at a task. But we have shown that if you push the model a little bit to do actual learning, you see that huge improvements in performance can happen,” says Ekin Akyürek PhD ’25, lead author of the study.

Akyürek is joined on the paper by graduate students Mehul Damani, Linlu Qiu, Han Guo, and Jyothish Pari; undergraduate Adam Zweiger; and senior authors Yoon Kim, an assistant professor of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Jacob Andreas, an associate professor in EECS and a member of CSAIL. The research will be presented at the International Conference on Machine Learning.

Tackling hard domains

LLM users often try to improve the performance of their model on a new task using a technique called in-context learning. They feed the model a few examples of the new task as text prompts which guide the model’s outputs.

But in-context learning doesn’t always work for problems that require logic and reasoning.

The MIT researchers investigated how test-time training can be used in conjunction with in-context learning to boost performance on these challenging tasks. Test-time training involves updating some model parameters — the internal variables it uses to make predictions — using a small amount of new data specific to the task at hand.

The researchers explored how test-time training interacts with in-context learning. They studied design choices that maximize the performance improvements one can coax out of a general-purpose LLM.

“We find that test-time training is a much stronger form of learning. While simply providing examples can modestly boost accuracy, actually updating the model with those examples can lead to significantly better performance, particularly in challenging domains,” Damani says.

In-context learning requires a small set of task examples, including problems and their solutions. The researchers use these examples to create a task-specific dataset needed for test-time training.

To expand the size of this dataset, they create new inputs by slightly changing the problems and solutions in the examples, such as by horizontally flipping some input data. They find that training the model on the outputs of this new dataset leads to the best performance.

In addition, the researchers only update a small number of model parameters using a technique called low-rank adaption, which improves the efficiency of the test-time training process.

“This is important because our method needs to be efficient if it is going to be deployed in the real world. We find that you can get huge improvements in accuracy with a very small amount of parameter training,” Akyürek says.

Developing new skills

Streamlining the process is key, since test-time training is employed on a per-instance basis, meaning a user would need to do this for each individual task. The updates to the model are only temporary, and the model reverts to its original form after making a prediction.

A model that usually takes less than a minute to answer a query might take five or 10 minutes to provide an answer with test-time training, Akyürek adds.

“We wouldn’t want to do this for all user queries, but it is useful if you have a very hard task that you want to the model to solve well. There also might be tasks that are too challenging for an LLM to solve without this method,” he says.

The researchers tested their approach on two benchmark datasets of extremely complex problems, such as IQ puzzles. It boosted accuracy as much as sixfold over techniques that use only in-context learning.

Tasks that involved structured patterns or those which used completely unfamiliar types of data showed the largest performance improvements.

“For simpler tasks, in-context learning might be OK. But updating the parameters themselves might develop a new skill in the model,” Damani says.

In the future, the researchers want to use these insights toward the development of models that continually learn.

The long-term goal is an LLM that, given a query, can automatically determine if it needs to use test-time training to update parameters or if it can solve the task using in-context learning, and then implement the best test-time training strategy without the need for human intervention.

This work is supported, in part, by the MIT-IBM Watson AI Lab and the National Science Foundation.

During photosynthesis, an enzyme called rubisco catalyzes a key reaction — the incorporation of carbon dioxide into organic compounds to create sugars. However, rubisco, which is believed to be the most abundant enzyme on Earth, is very inefficient compared to the other enzymes involved in photosynthesis.

MIT chemists have now shown that they can greatly enhance a version of rubisco found in bacteria from a low-oxygen environment. Using a process known as directed evolution, they identified mutations that could boost rubisco’s catalytic efficiency by up to 25 percent.

The researchers now plan to apply their technique to forms of rubisco that could be used in plants to help boost their rates of photosynthesis, which could potentially improve crop yields.

“This is, I think, a compelling demonstration of successful improvement of a rubisco’s enzymatic properties, holding out a lot of hope for engineering other forms of rubisco,” says Matthew Shoulders, the Class of 1942 Professor of Chemistry at MIT.

Shoulders and Robert Wilson, a research scientist in the Department of Chemistry, are the senior authors of the new study, which appears this week in the Proceedings of the National Academy of Sciences. MIT graduate student Julie McDonald is the paper’s lead author.

Evolution of efficiency

When plants or photosynthetic bacteria absorb energy from the sun, they first convert it into energy-storing molecules such as ATP. In the next phase of photosynthesis, cells use that energy to transform a molecule known as ribulose bisphosphate into glucose, which requires several additional reactions. Rubisco catalyzes the first of those reactions, known as carboxylation. During that reaction, carbon from CO2 is added to ribulose bisphosphate.

Compared to the other enzymes involved in photosynthesis, rubisco is very slow, catalyzing only one to 10 reactions per second. Additionally, rubisco can also interact with oxygen, leading to a competing reaction that incorporates oxygen instead of carbon — a process that wastes some of the energy absorbed from sunlight.

“For protein engineers, that’s a really attractive set of problems because those traits seem like things that you could hopefully make better by making changes to the enzyme’s amino acid sequence,” McDonald says.

Previous research has led to improvement in rubisco’s stability and solubility, which resulted in small gains in enzyme efficiency. Most of those studies used directed evolution — a technique in which a naturally occurring protein is randomly mutated and then screened for the emergence of new, desirable features.

This process is usually done using error-prone PCR, a technique that first generates mutations in vitro (outside of the cell), typically introducing only one or two mutations in the target gene. In past studies on rubisco, this library of mutations was then introduced into bacteria that grow at a rate relative to rubisco activity. Limitations in error-prone PCR and in the efficiency of introducing new genes restrict the total number of mutations that can be generated and screened using this approach. Manual mutagenesis and selection steps also add more time to the process over multiple rounds of evolution.

The MIT team instead used a newer mutagenesis technique that the Shoulders Lab previously developed, called MutaT7. This technique allows the researchers to perform both mutagenesis and screening in living cells, which dramatically speeds up the process. Their technique also enables them to mutate the target gene at a higher rate.

“Our continuous directed evolution technique allows you to look at a lot more mutations in the enzyme than has been done in the past,” McDonald says.

Better rubisco

For this study, the researchers began with a version of rubisco, isolated from a family of semi-anaerobic bacteria known as Gallionellaceae, that is one of the fastest rubisco found in nature. During the directed evolution experiments, which were conducted in E. coli, the researchers kept the microbes in an environment with atmospheric levels of oxygen, creating evolutionary pressure to adapt to oxygen.

After six rounds of directed evolution, the researchers identified three different mutations that improved the rubisco’s resistance to oxygen. Each of these mutations are located near the enzyme’s active site (where it performs carboxylation or oxygenation). The researchers believe that these mutations improve the enzyme’s ability to preferentially interact with carbon dioxide over oxygen, which leads to an overall increase in carboxylation efficiency.

“The underlying question here is: Can you alter and improve the kinetic properties of rubisco to operate better in environments where you want it to operate better?” Shoulders says. “What changed through the directed evolution process was that rubisco began to like to react with oxygen less. That allows this rubisco to function well in an oxygen-rich environment, where normally it would constantly get distracted and react with oxygen, which you don’t want it to do.”

In ongoing work, the researchers are applying this approach to other forms of rubisco, including rubisco from plants. Plants are believed to lose about 30 percent of the energy from the sunlight they absorb through a process called photorespiration, which occurs when rubisco acts on oxygen instead of carbon dioxide.

“This really opens the door to a lot of exciting new research, and it’s a step beyond the types of engineering that have dominated rubisco engineering in the past,” Wilson says. “There are definite benefits to agricultural productivity that could be leveraged through a better rubisco.”

The research was funded, in part, by the National Science Foundation, the National Institutes of Health, an Abdul Latif Jameel Water and Food Systems Lab Grand Challenge grant, and a Martin Family Society Fellowship for Sustainability.

MIT Professor Emeritus Barry Lloyd Vercoe, a pioneering force in computer music, a founding faculty member of the MIT Media Lab, and a leader in the development of MIT’s Music and Theater Arts Section, passed away on June 15. He was 87.

Vercoe’s life was a rich symphony of artistry, science, and innovation that led to profound enhancements of musical experience for expert musicians as well as for the general public — and especially young people.

Born in Wellington, New Zealand, on July 24, 1937, Vercoe earned bachelor’s degrees in music (in 1959) and mathematics (in 1962) from the University of Auckland, followed by a doctor of musical arts in music composition from the University of Michigan in 1968.

After completing postdoctoral research in digital audio processing at Princeton University and a visiting lectureship at Yale University, Vercoe joined MIT’s Department of Humanities (Music) in 1971, beginning a tenure in the department that lasted through 1984. During this period, he played a key role in advancing what would become MIT’s Music and Theater Arts (MTA) Section, helping to shape its forward-thinking curriculum and interdisciplinary philosophy. Vercoe championed the integration of musical creativity with scientific inquiry, laying the groundwork for MTA’s enduring emphasis on music technology and experimental composition.

In 1973, Vercoe founded MIT’s Experimental Music Studio (EMS) — the Institute’s first dedicated computer music facility, and one of the first in the world. Operated under the auspices of the music program, EMS became a crucible for innovation in algorithmic composition, digital synthesis, and computer-assisted performance. His leadership not only positioned MIT as a hub for music technology, but also influenced how the Institute approached the intersection of the arts with engineering. This legacy is honored today by a commemorative plaque in the Kendall Square MBTA station.

Violist, faculty founder of the MIT Chamber Music Society, and Institute Professor Marcus Thompson says: “Barry was first and foremost a fine musician, and composer for traditional instruments and ensembles. As a young professor, he taught our MIT undergraduates to write and sing Renaissance counterpoint as he envisioned how the act of traditional music-making offered a guide to potential artistic interaction between humans and computers. In 1976, he enlisted me to premiere what became his iconic, and my most-performed, work, ‘Synapse for Viola and Computer.’”

During a Guggenheim Fellowship in 1982–83, Vercoe developed the Synthetic Performer, a groundbreaking real-time interactive accompaniment system, while working closely with flautist Larry Beauregard at the Institute for Research and Coordination in Acoustics/Music (IRCAM) in Paris.

In 1984, Vercoe became a founding faculty member of the MIT Media Lab, where he launched the Music, Mind, and Machine group. His research spanned machine listening, music cognition, and real-time digital audio synthesis. His Csound language, created in 1985, is still widely used for music programming, and his contributions helped define the MPEG-4 Structured Audio standard.

He also served as associate academic head of the Media Lab’s graduate program in Media Arts and Sciences (MAS). Vercoe mentored many future leaders in digital music and sound computation, including two of his MAS graduate students — Anna Huang SM ’08 and Paris Smaragdis PhD ’01 — who have recently joined MIT’s music faculty, and Miller Puckette, an emeritus faculty member at the University of California at San Diego, and Richard Boulanger, a professor of electronic production and design at the Berklee College of Music.

“Barry Vercoe will be remembered by designers, developers, researchers, and composers for his greatest ‘composition,’ Csound, his free and open-source software synthesis language,” states Boulanger. “I know that, through Csound, Barry’s musical spirit will live on, not only in my teaching, my research, and my music, but in the apps, plugins, and musical compositions of generations to come.”

Tod Machover, faculty director of the MIT Media Lab and Muriel R. Cooper Professor of Music and Media, reflects, “Barry Vercoe was a giant in the field of computer music whose innovations in software synthesis, interactive performance, and educational tools for young people influenced and inspired many, including myself. He was a superb mentor, always making sure that artistic sensibility drove music tech innovation, and that sophisticated expression was at the core of Media Lab — and MIT — culture.”

Vercoe’s work earned numerous accolades. In addition to the Guggenheim Fellowship, he was also honored with the 1992 Computerworld Smithsonian Award for innovation and the 2004 SEAMUS Lifetime Achievement Award.

Beyond MIT, Vercoe consulted with Analog Devices and collaborated with international institutions like IRCAM under the direction of Pierre Boulez. His commitment to democratizing music technology was evident in his contributions to the One Laptop per Child initiative, which brought accessible digital sound tools to young people in underserved communities worldwide.

He is survived by his former wives, Kathryn Veda Vaughn and Elizabeth Vercoe; their children, Andrea Vercoe and Scott Vercoe; and generations of students and collaborators who continue to build on his groundbreaking work. A memorial service for family will be held in New Zealand later this summer, and a special event in his honor will take place at MIT in the fall. The Media Lab will share details about the MIT gathering as they become available.

Named professor emeritus at the MIT Media Lab upon his retirement in 2010, Vercoe’s legacy embodies the lab’s — and MIT’s — vision of creative, ethical, interdisciplinary research at the convergence of art, science, and technology. His music, machines, and generously inventive spirit will continue to forever shape the way we listen, learn, and communicate.