The man who reinvented the hammer

A trip to Walmart. An aging German shepherd. A cheap disposable camera.

These are just a few of the seemingly mundane things that have sparked the relentlessly imaginative mind of Kurt Schroder ’90, leading to some of his groundbreaking inventions.

“I just can’t stop doing it,” he says, with a chuckle and a tiny trace of southern Indiana twang. “I invent all the time. It doesn’t matter what it is. I’m always doing experiments.”

Schroder grew up on a farm but always knew his future wasn’t in agriculture. With his heart set on studying physics, he applied only to MIT—ignorant, he says, of just how academically rigorous it would be. Once enrolled, he watched as his “super genius” classmates appeared to sail through their classes, while he worked harder than they did but earned only Bs. 

Everything changed when he made his way through the notorious gauntlet of Course 8 Junior Lab, considered one of the most demanding two-term lab classes at the Institute. While tinkering during that advanced experimental physics class, he found his path.

“It eliminates a lot of people, but for some reason it was the easiest class for me,” he remembers now. “I would not only fix the machines and get them working but actually get better measurements than other people did, and figured out ways to use the equipment to do things that no one had noticed.”

But in his regular classes, he still felt he was treading water. “I realized that, okay, I still wanted to be a physicist, but maybe a slightly different kind of physicist,” he says.  

For example, the kind of physicist who manages to improve the everyday hammer—a tool so ubiquitous and taken for granted that it hadn’t been reconceived in hundreds, maybe thousands, of years until Schroder came along. Or the kind who would save an old dog using nanoparticles of silver. Or one who would use a $7 camera to brainstorm his way to a new thermal processing technique that has revolutionized the mass production of electronic circuits.

After MIT, Schroder spent two years designing weapons for the US Navy before enrolling in a doctoral program in plasma physics at the University of Texas at Austin. As he was approaching his final year, he and his wife, Lisa, went to Walmart one day to run an errand. “Like a stereotypical guy, I walked into the tool section and I started looking at the hammers,” Schroder recalls. “I realized all the hammers were designed incorrectly. It became almost an obsession for me.” 

“I became enamored with the fact that I could work on something that everybody had the opportunity to fix and did not.”

What Schroder picked up on wasn’t the design of the tools, exactly, but the fact that the manufacturers were effectively broadcasting a flaw. “The labels of all the hammers said ‘We have a shock-­reduction grip’ or a ‘vibration-reducing grip’ and I would try it and it didn’t work,” he says. “They were saying: ‘This is not a solved problem.’ They just gave me the information I needed. Have you ever heard of a tire company that says ‘Our tires are round’?”

At the time, Schroder was taking another exacting class, this one on mechanics. The professor told students he planned to cover 14 weeks of the syllabus in a mere six weeks and focus on special topics in the remaining time. Many students were intimidated and dropped out, but Schroder stuck with it. (“It was the type of abuse I was used to at MIT,” he jokes, pointing to his brass rat. “So it was just fine.”) Somewhat fortuitously, one of those “special topics” was baseball bats. 

hammer

WYATT MCSPADDEN

Because Schroder was so consumed by the hammer vibration problem—another activity that involves the mechanics of swinging—he read books about the legendary Boston Red Sox batter Ted Williams to learn more. He interviewed carpenters. He spent a fair amount of time with a hammer in his hand. “I got to be pretty good at it myself. I was just hammering all the time,” he says. “I ended up losing part of my hearing because I was doing all this work on anvils.”

He developed tests to measure vibrations and crafted a “cyberglove” that would read them and upload the data into a computer program. After two years of data collection and analysis, he concluded that most attempts to improve hammers involved adding length and therefore weight. That causes fatigue and potentially exacerbates what is known as “hammer elbow” or lateral epicondylitis, a repetitive stress disorder that can plague construction workers. 

Schroder determined that there was a “little spot in a hammer where there’s not much vibration”—the part of the handle most people would naturally grasp. He figured out that if you remove weight from the parts of the handle adjacent to the grip and insert foam there, that insulates the user’s hand from the shock of impact and resulting vibration. Using foam inserts also made it feasible for him to redesign the hammer head to increase the effective length of the hammer—and boost momentum transfer by about 15%—without adding weight. In other words, his design not only reduced vibration but made the hammer hit harder with less effort. 

These modifications also cut manufacturing costs. Today, Schroder’s design improvements have made their way into the majority of hammers sold in the United States, making hammering much easier on users’ elbows—and relieving manufacturers from the mounting threat of lawsuits for vibration-related workplace injuries. 

“It’s kind of a boring thing, really. It’s not something that physicists work on,” he says. “I became enamored with the fact that I could work on something that everybody had the opportunity to fix and did not.”

In the course of tackling the hammer problem, Schroder says, he learned that being an inventor is as much about perseverance and grit as it is about science or imagination. His professors told him he was wasting his time and shouldn’t bother. Then, after he presented his innovations to hammer companies, they said they didn’t think his developments were patentable—yet proceeded to incorporate them into their new designs. Two patents were ultimately issued to Schroder, and 16 years later, after suing the hammer companies, he was finally compensated for his innovations. He paid off his house, took his wife and five kids to Italy, and gave the rest of the proceeds to charity, he says.

By that time, he had already moved on.

In the early 2000s, while working at a company then called Nanotechnologies, Schroder was applying the concept of pulsed power, a subfield of physics and electrical engineering he’d studied at MIT, to synthesize nanoparticles. Pulsed power involves extremely brief, intense bursts of electric current that deliver “a huge amount of power—a ridiculous amount of power—for a short period of time,” Schroder explains. For example, a flash camera might take five seconds to charge, drawing a mere five watts from an AA battery. But when it releases that stored energy in less than a thousandth of a second, the flash is about 20,000 watts.

“Inventing is a skill, not a talent. Everyone can be an inventor.”

For one of its many projects, the company had been developing an electro-­thermal gun, originally intended for military purposes, that Schroder says had “a very intense arc discharge—a spark, but 100,000 amps.” He describes the 50-megawatt prototypes they produced as “a little bit scary” and calls it a “failed device that never got out of the laboratory.” But his predecessors at the company realized that if they pulled the trigger after removing the projectile from the barrel, the high heat of the pulsed arc discharge would erode the silver electrodes inside the barrel, generating plasma that shot out of the device. When the plasma rapidly cooled, these eroded, or ablated, electrodes reacted with gases to form nanoparticles. An inert gas, like helium, would generate silver nanoparticles. A reactive gas would form nanoparticles of a compound, like silver oxide.

Abandoning the idea of an electro­thermal gun altogether, Schroder and his colleagues drew on his expertise in pulsed power and focused on applying it to rods of, say, silver or aluminum to produce nanoparticles of those materials. Then they determined that if they tweaked the length of the pulse, from one millisecond to two or more, they could change the average particle size to suit a broader range of applications. The discovery was “really exciting,” Schroder says now, but it proved difficult to capitalize on given the lack of commercial demand for nanoparticles at the time. The company was on the verge of bankruptcy.

Around this time, in 2001, Schroder inherited an ailing 12-year-old German shepherd named Heidi. “She had these pus-y wounds that were a half-inch in diameter and a half-inch deep in her knees and elbows,” Schroder recalls. “The infection was so bad she couldn’t get up.” He began to treat Heidi with a salve made for dogs and horses, but after a couple of weeks she was not improving. “I thought, darn it, I don’t want to put her down,” Schroder remembers.

But then he thought of the silver nanoparticles that his company had developed. “I had heard that some of the stuff might be antimicrobial,” he says. So he mixed the nanoparticles into the salve and applied it to Heidi’s wounds. Within two weeks, they had healed, and Heidi could stand and even run. Now the nanoparticle-­infused salve is an FDA-approved product that hospitals use to treat burn victims. “We referred to her, lovingly, as Heidi the Nano Dog,” Schroder says.

Today, Schroder is best known for his second nanoparticle invention, which he dreamed up when he became fascinated with the idea of printed electronics.

“I thought, wouldn’t it be kind of cool if you could take an inkjet printer cartridge, jailbreak it, and [add metallic] nanoparticles and make a dispersion, make an ink?” he says. “You could print wires on a piece of paper and make the cheapest circuit in the world.”

hands hold a print; glowing green LEDs form the outline of a leaf-shape.
Schroder’s belief that
everything can be made better has motivated all his work, from rethinking hammers to developing low-cost printable circuits.
COURTESY OF KURT SCHRODER ’90

The problem is that cheaper substrates, including paper and plastic, will ignite at the high temperatures necessary to sinter, or cure, the nanoparticles into wires. (Melting silver requires a temperature of 962 °C, but paper ignites at 233 °C, or the novelistically famous Fahrenheit 451.) Equally problematic, the ovens in which this sintering takes place are often very large and slow, and they require a lot of energy.  

This is where a disposable camera enters the picture.

“The first one I got from Walgreens. It cost me seven bucks, but I jailbroke it so I could keep on flashing it,” he recalls. Schroder says he figured that he could use the intense flash of light to heat only the nanoparticles (which are black and readily absorb light), sintering them together into wires so fast that the paper or plastic substrate on which he’d printed them did not have a chance to melt or warp. The idea, Schroder explains, was to harness the intensity of the flash (the pulsed power) to generate millisecond bursts of high power using minimal energy. “It was one of those rare times in technological development in which faster, better, and cheaper all happened simultaneously,” he says.

He and his colleagues ultimately scaled up the flash concept into an industrial system known as PulseForge, which can generate bursts of heat hot enough to cure nanoparticles into conductive traces—and do it so quickly that their substrates survive the heat.

“With this flash lamp technology—­photonic curing, that’s what I called it—we can go up to about 400 °C. But we can do in one millisecond what normally would take 10 minutes or longer,” Schroder says. “This replaces an oven, which can be hundreds of meters long and take up an entire building and use tons and tons of energy.” Today, he is CTO of the company, which is now known as PulseForge. It offers digital thermal processing systems that make manufacturing more sustainable and more affordable.

Though he can’t be specific about what the company’s clients manufacture, Schroder says PulseForge’s technology is used to make consumer electronics that most people own today.  

After 30 years of experimentation in many fields—including mechanical engineering, chemistry, pulsed power, nanotechnology, and printed electronics—Schroder holds 41 US patents and more than 70 international ones. He’s won the prestigious R&D 100 Award twice. In 2012, the Texas State Bar named him Inventor of the Year, and in 2023, the Austin Intellectual Property Law Association did the same.

Schroder says he won’t live long enough to explore all the ideas bouncing around in his head. But one thing he’d like to do is provide some guidance to fledgling inventors—a kind of practical and personal road map to success. He’s already started writing a book, called simply How to Invent.

The book was partially inspired by a gathering he organized a few years ago for his oldest daughter, who was then 11, and 40 or so of her friends from a scouting group. Schroder called it an “invention fair.”

“I told them: I want you to identify problems in the world,” he says. “You’re going to try to solve them.”

He was so impressed with the girls’ ideas, including his daughter’s—a backpack that dispenses M&Ms—that something struck him. “Inventing is a skill, not a talent,” he says. “Everyone can be an inventor, and seeing these 40 little girls come up with some pretty darn good inventions—I realized there’s a process for this.”

One of his hard-won pieces of advice is to find joy in that process—to be happy simply because an experiment works. “Don’t focus too much [on] if you’re going to make a zillion dollars or be in charge of it,” he says. “Because guess what? There are a hundred more inventions after that.”

There is, however, one intangible trait that every inventor should have: the outlook that a glass is neither half full nor half empty.

“The inventor says: ‘I can make a better glass,’” he says. “An inventor always sees a future in which everything is better.” 

An environmentally friendly alternative to plastic microbeads

The tiny beads added to some cleansers and cosmetics are one source of the long-­lasting microplastics that threaten the environment. But MIT researchers have found a way to address the problem at its source: replacing them with polymers that break down into harmless sugars and amino acids. Particles of this polymer could also be used to encapsulate nutrients such as vitamin A to fortify foods, which could help some of the 2 billion people around the world who suffer from nutrient deficiencies.

To develop the material, graduate student Linzixuan (Rhoda) Zhang and her colleagues turned to poly-beta-amino esters, a class of polymers previously developed in the lab of Institute Professor Robert Langer, ScD ’74, which have shown promise for medical applications.

By changing the composition of these materials’ building blocks, researchers can optimize properties such as hydrophobicity (ability to repel water), mechanical strength, and pH sensitivity. One property the team targeted, with an eye to using the polymer to add nutrients to food, was the ability to dissolve when exposed to acidic environments such as the stomach.

The researchers showed that they could use particles of the polymer to encapsulate vitamins A, D, E, and C, as well as zinc and iron. Many of these nutrients are susceptible to heat and light degradation, but the team found that the particles could protect them from boiling water for two hours. They also showed that even after being stored for six months at high temperature and high humidity, more than half of the encapsulated vitamins were undamaged.

To demonstrate the particles’ potential for fortifying food, the researchers incorporated them into bouillon cubes—a common ingredient in Africa, where nutrient deficiencies are common, says Ana Jaklenec, a principal investigator at the Koch Institute for Integrative Cancer Research and a senior author, with Langer, of a paper on the work. 

In this study, the researchers also tested the particles’ safety by exposing them to cultured human intestinal cells. At the amounts that would be used in food, the particles were not found to damage the cells.

To explore the particles’ potential for use in cleansers, the researchers mixed them with soap foam. This mixture, they found, removed permanent marker and waterproof eyeliner much more effectively than soap alone. Soap mixed with the new microparticles was also more effective than a cleanser that includes polyethylene microbeads, and the particles did a better job of absorbing potentially toxic elements such as heavy metals.

The researchers plan to run a small human trial later this year and are gathering data that could be used to apply for GRAS (generally recognized as safe) classification from the US Food and Drug Administration. They are also planning a clinical trial of foods fortified with the particles.

Their work on the polymer, they hope, could help significantly reduce the amount of microplastic released into the environment from health and beauty products. “One way to mitigate the microplastics problem is to figure out how to clean up existing pollution,” Jaklenec says. “But it’s equally important to look ahead and focus on creating materials that won’t generate microplastics in the first place.” 

Tiny tubes wrap around brain cells

Wearable devices like smart watches and fitness trackers help us measure and learn from physical functions such as heart rates and sleep stages. Now MIT researchers have developed a tiny equivalent for individual brain cells.

These soft, battery-free wireless devices, actuated with light, are designed to wrap around different parts of neurons, such as axons and dendrites, without damaging them. They could be used to measure or modulate a neuron’s electrical and metabolic activity. They could also serve as synthetic myelin for axons that have lost this insulation, helping to address neuronal degradation in diseases like multiple sclerosis.

The devices are made from thin sheets of a soft polymer called azobenzene, which roll when exposed to light. Researchers can precisely control the direction of the rolling and the size and shape of the tubes by varying the intensity and polarization of the light. This enables the devices to snugly, but gently, wrap around curved axons and dendrites.

“To have intimate interfaces with these cells, the devices must be soft and able to conform to these complex structures. That is the challenge we solved in this work,” says Deblina Sarkar, an assistant professor in the Media Lab and the senior author of a paper on the research. “We were the first to show that azobenzene could even wrap around living cells.”

The researchers, who developed a scalable fabrication technique that doesn’t require the use of a cleanroom, have demonstrated that the devices can be combined with optoelectrical materials that can stimulate cells. Moreover, atomically thin materials can be patterned on top of the tubes, offering opportunities to integrate sensors and circuits.

In addition, because they make such a tight connection with cells, they could make it possible to stimulate subcellular regions with very little energy. This could enable a researcher or clinician to treat brain diseases by modulating neurons’ electrical activity. 

A Nobel laureate on the economics of artificial intelligence

For all the talk about artificial intelligence upending the world, its economic effects remain uncertain. But Institute Professor and 2024 Nobel winner Daron Acemoglu has some insights.

Despite some predictions that AI will double US GDP growth, Acemoglu expects it to increase GDP by 1.1% to 1.6% over the next 10 years, with a roughly 0.05% annual gain in productivity. This assessment is based on recent estimates of how many jobs are affected—but his view is that the effect will be targeted.

“We’re still going to have journalists, we’re still going to have financial analysts, we’re still going to have HR employees,” he says. “It’s going to impact a bunch of office jobs that are about data summary, visual matching, pattern recognition, etc. And those are essentially about 5% of the economy.”

He does think the technology has more potential, but he’s concerned that AI companies so far have focused on innovations that could replace human workers at the expense of those that could make them more productive. “My argument is that we currently have the wrong direction for AI,” Acemoglu says. “We’re using it too much for automation and not enough for providing expertise and information to workers.”

Innovations that keep people employed should sustain growth better, he believes. But “I don’t think complementary uses of AI will miraculously appear by themselves unless the industry devotes significant energy and time to them,” he says. And even then, whether the advances benefit workers themselves is far from guaranteed.

Given this mix of benefits and drawbacks, Acemoglu and his colleagues think it may be best to adopt AI more slowly than market fundamentalists might like. While government regulation is one way to promote that measured pace, he also thinks that if the cycle of “hype” around AI diminishes, then the rush to use it “will naturally slow down.” 

“I think that hype is making us invest badly in terms of the technology,” he says.

“The faster you go, and the more hype you have, that course correction becomes less likely. It’s very difficult, if you’re driving 200 miles an hour, to make a 180-degree turn.” 

From climate-warming pollutant to useful material

Although it is less abundant than carbon dioxide, methane gas contributes disproportionately to global warming. Its molecular structure of single carbon atoms bound to four hydrogen atoms makes it a potentially useful building block for products that could keep this carbon out of the atmosphere, but it’s hard to get it to react with other molecules under ordinary conditions.

Now a catalyst designed by MIT chemical engineer Michael Strano and colleagues could help solve that problem.

The catalyst has two components. The first, a mineral called a zeolite, converts methane to methanol. The second, a natural enzyme called alcohol oxidase, converts the methanol to formaldehyde. With the addition of urea, a nitrogen-containing molecule found in urine, the formaldehyde can be turned into a polymer used in particleboard, textiles, and other products.

The researchers say this catalyst could act to seal cracks in pipes transporting natural gas, a common source of methane leakage. It could also be used to coat surfaces that are exposed to methane gas, producing polymers that could be collected for use in manufacturing.

“Other systems operate at high temperature and high pressure,” says MIT postdoc Jimin Kim, lead author with Daniel Lundberg, PhD ’24, of a paper on the work. That takes money and energy. But, she says, “I think our system could be very cost-effective and scalable.” 

This is your brain on movies

The cerebral cortex contains regions devoted to processing different types of sensory information, including visual and auditory input. Now researchers led by Robert Desimone, director of MIT’s McGovern Institute for Brain Research, and colleagues have developed the most comprehensive picture yet of what all these regions do. They achieved this by analyzing data collected as people performed a surprisingly complex task: watching a movie.

Over the past few decades, scientists have identified many networks that are involved in this kind of processing, often using functional magnetic resonance imaging (fMRI) to measure brain activity as subjects perform a single task (such as looking at faces) or do nothing. The problem is that while people are resting, many parts of the cortex may not be active at all.

“By using a rich stimulus like a movie, we can drive many regions of the cortex very efficiently. For example, sensory regions will be active to process different features of the movie, and high-level areas will be active to extract semantic and contextual information,” says Reza Rajimehr, a research scientist in the McGovern Institute and the lead author of a paper on the work. “By activating the brain in this way, now we can distinguish different areas or different networks based on their activation patterns.”

Using high-resolution fMRI data collected by an NIH-funded consortium, the researchers analyzed brain activity from 176 people as they watched a variety of movie clips. Then they used a machine-learning algorithm to analyze the activity patterns of each brain region. What they found was 24 networks with different activity patterns and functions. Some are located in sensory areas such as the visual or auditory cortex, while others respond to features such as actions, language, or social interactions. The researchers also identified networks that hadn’t been seen before, including one in the prefrontal cortex that appears highly responsive to visual scenes. This network was most active in response to pictures of scenes within the movie frames.

Three of the networks they found are involved in “executive control” and were most active during transitions between clips. The researchers also observed that when networks specific to a particular feature were very active, the executive control networks were mostly quiet, and vice versa.

“Whenever the activations in domain-specific areas are high, it looks like there is no need for the engagement of these high-level networks,” Rajimehr says. “But in situations where perhaps there is some ambiguity and complexity in the stimulus, and there is a need for the involvement of the executive control networks, then we see that these networks become highly active.”

The researchers hope that their new map will serve as a starting point for more precise study of what each of these networks is doing. For example, within the social processing network, they have found regions that are specific to processing social information about faces and bodies.

“This is a new approach that reveals something different from conventional approaches in neuroimaging,” says Desimone. “It’s not going to give us all the answers, but it generates a lot of interesting ideas.” 

Laser imaging peers deeper into living tissue

Metabolic imaging is a valuable noninvasive method for studying living cells with laser light, but it’s been constrained by the way light scatters when it shines into tissue, limiting the resolution and depth of penetration. MIT researchers have developed a new technique that more than doubles the usual depth limit while boosting imaging speeds, yielding richer and more detailed images.

This technique does not require samples to be sliced and stained with contrast dyes. Instead, when a specialized laser shines light deep into tissues, certain molecules within them emit light of different colors, revealing molecular contents and cellular structures. By using a recently developed fiber shaper—a device controlled by bending it—the researchers can tune the color and pulses of light to minimize scattering and maximize the signal. This allows them to see much further and capture clearer images. In tests, the light was able to penetrate more than 700 micrometers into a sample, whereas the best previous techniques reached about 200 micrometers.

This method is particularly well suited for applications like cancer research, tissue engineering, drug discovery, and the study of immune responses. “It opens new avenues for studying and exploring metabolic dynamics deep in living biosystems,” says Sixian You, an assistant professor of EECS and senior author of a paper on the technique.

Recent books from the MIT community

Differential Privacy
By Simson L. Garfinkel ’87, PhD ’05 
MIT PRESSS, 2025, $18.95

Small, Medium, Large: How Government Made the US into a Manufacturing Powerhouse
By Colleen A. Dunlavy, PhD ’88  
POLITY BOOKS, 2024, $29.95

The Miraculous from the Material: Understanding the Wonders of Nature 
By Alan Lightman, professor of the practice of the humanities 
PANTHEON, 2024, $36

The Path to Singularity: How Technology Will Challenge the Future of Humanity
By J. Craig Wheeler ’65, with a foreword by Neil deGrasse Tyson 
PROMETHEUS BOOKS, 2024, $32.95

Assembly by Design: The United Nations and Its Global Interior
By Olga Touloumi, SM ’06
UNIV. OF MINNESOTA PRESS, 2024, $35

The Finite Element Method: Its Basis and Fundamentals 
By O.C. Zienkiewicz, R.L. Taylor, and Sanjay Govindjee ’86 
BUTTERWORTH-HEINNEMANN, 2024, $286.99

Where Biology Ends and Bias Begins: Lessons on Belonging from Our DNA 
By Shoumita Dasgupta ’97 
UNIV. OF CALIF. PRESS, 2025, $29.95

A Moving Meditation: Life on a Cape Cod Kettle Pond 
By Stephen G. Waller ’73 
BRIGHT LEAF, 2023, $24.95


Send book news to MITAlumniNews@technologyreview.com or 196 Broadway, 3rd Floor Cambridge, MA 02139

Calligraphy bot

Gloria Zhu ’26 and Lee Liu ’26 set out to make a calligraphy machine during IAP 2024. They built its mechatronic parts in a month; then, fueled by Hershey’s dark chocolates, they put in many late nights in the Metropolis makerspace’s electronics mezzanine to finish the job. The resulting device can move its brush pen with five degrees of freedom, and its carriage moves up and down to vary the stroke width.

Forging the digital future

Dan Huttenlocher, SM ’84, PhD ’88, leads the way up to the eighth floor of Building 45, the recently completed headquarters of the MIT Schwarzman College of Computing. “There’s an amazing view of the Great Dome here,” he says, pointing out a panoramic view of campus and the Boston skyline beyond. The floor features a high-end event space with an outdoor terrace and room for nearly 350 people. But it also serves an additional purpose—luring people into the building, which opened last January. The event space “wasn’t in the original building plan,” says Huttenlocher, Schwarzman’s inaugural dean, “but the point of the building is to be a nexus, bringing people across campus together.” 

Launched in 2019–’20, Schwarzman is MIT’s only college, so called because it cuts across the Institute’s five schools in a new effort to integrate advanced computing and artificial intelligence into all areas of study. “We want to do two things: ensure that MIT stays at the forefront of computer science, AI research, and education,” Huttenlocher says, “and infuse the forefront of computing into disciplines across MIT.” He adds that safety and ethical considerations are also critical.

To that end, the college now encompasses multiple existing labs and centers, including the Computer Science and Artificial Intelligence Laboratory (CSAIL), and multiple academic units, including the Department of Electrical Engineering and Computer Science. (EECS—which was reorganized into the overlapping subunits of electrical engineering, computer science, and artificial intelligence and decision-making—is now part of both the college and the School of Engineering.) At the same time, the college has embarked on a plan to hire 50 new faculty members, half of whom will have shared appointments in other departments across all five schools to create a true Institute-wide entity. Those faculty members—two-thirds of whom have already been hired—will conduct research at the boundaries of advanced computing and AI.

“We want to do two things: ensure that MIT stays at the forefront of computer science, AI research, and education and infuse the forefront of computing into disciplines across MIT.”

Dan Huttenlocher

The new faculty members have already begun helping the college respond to an undeniable reality facing many students: They’ve been overwhelmingly drawn to advanced computing tools, yet computer science classes are often too technical for nonmajors who want to apply those tools in other disciplines. And for students in other majors, it can be tricky to fit computer science classes into their schedules. 

Meanwhile, the appetite for computer science education is so great that nearly half of MIT’s undergraduates major in EECS, voting with their feet about the importance of computing. Graduate-level classes on deep learning and machine vision are among the largest on campus, with over 500 students each. And a blended major in cognition and computing has almost four times as many enrollees as brain and cognitive sciences.

“We’ve been calling these students ‘computing bilinguals,’” Huttenlocher says, and the college aims to make sure that MIT students, whatever their field, are fluent in the language of computing. “As we change the landscape,” he says, “it’s not about seeing computing as a tool in service of a particular discipline, or a discipline in the service of computing, but asking: How can we bring these things together to forge something new?” 

The college has been the hub of this experiment, sponsoring over a dozen new courses that integrate computing with other disciplines, and it provides a variety of spaces that bring people together for conversations about the future of computing at MIT.

More than just a nexus for computing on campus, the college has also positioned itself as a broad-based leader on AI, presenting policy briefs to Congress and the White House about how to manage the pressing ethical and political concerns raised by the rapidly evolving technology. 

“Right now, digital technologies are changing every aspect of our lives with breakneck speed,” says Asu Ozdaglar, SM ’98, PhD ’03, EECS department head and Schwarzman’s deputy dean of academics. “The college is MIT’s response to the ongoing digital transformation of our society.” 


Huttenlocher, who also holds the title of Henry Ellis Warren (1894) Professor of Electrical Engineering and Computer Science and coauthored the book The Age of AI: And Our Human Future with Henry Kissinger and Eric Schmidt, has long been exploring such issues. He started programming computers back in middle school in Connecticut in the 1970s on an ASR 33 teletype machine, and eventually he studied at the University of Michigan as a double major in cognitive psychology and computer science, exploring speech recognition and visual perception. “AI work back then was relatively disconnected from the physical world,” he says. “Being interested in the perceptual side of things was kind of an outlier for what was going on in AI then.” When he looked at grad schools in the 1980s, only MIT, Carnegie Mellon, and Stanford were doing significant work in AI, he says: “I applied to those three schools and figured if it didn’t work out, I’d get a job.”

It worked out, of course. He headed to Cambridge and gravitated to MIT’s AI Lab in Technology Square, where he first worked on speech recognition and then transitioned into computer vision, at the time still in its infancy. After earning his PhD, he served simultaneously as a computer science professor at Cornell and a researcher at Xerox PARC, flying between New York and the burgeoning Silicon Valley, where he worked on computer vision for the digital transformation of copiers and scanners. “In academia, you have more curiosity-driven research projects, where in the corporate world you have the opportunity to build things people will actually use,” he says. “I’ve spent my career moving back and forth between them.”

Along the way, Huttenlocher gained administrative experience as well. He was a longtime board member and eventual chair of the MacArthur Foundation, and he also helped launch Cornell Tech, the university’s New York City–based graduate school for business, law, and technology, serving as its first dean and vice provost. When Stephen Schwarzman, CEO of the investment firm Blackstone Group, gave $350 million to MIT to establish a college of computing in 2018, he was eager to return to the Institute to lead it. “The fact that MIT was making a bold commitment to become a broad-based leader in the AI-driven age—and that it was cutting across all of its schools—was exciting,” he says. 

Schwarzman College took shape through task forces involving more than 100 MIT faculty members. By the fall of 2019 a plan had been nailed down, and Huttenlocher was in place as director with EECS head Ozdaglar named deputy dean of academics. “I never believed that everybody wants to do computer science at MIT,” she says. “Students come in with a lot of passions, and it’s our responsibility to educate these bilinguals, so they are fluent in their own discipline but also able to use these advanced frontiers of computing.” 

Ozdaglar’s background is in using machine learning to optimize communications, transportation, and control systems. Recently she has become interested in applying machine-learning algorithms to social media, examining how the choices people make when sharing content affect the information—and misinformation—recommended to them. This work builds on her longstanding interdisciplinary collaborations in the social sciences, including collaborations with her husband, economics professor (and recent Nobel laureate) Daron Acemoglu. “I strongly feel that to really address the important questions in society, these old department or disciplinary silos aren’t adequate anymore,” she says. “The college has enabled me to work much more broadly across MIT and share all that I’ve learned.”

Ozdaglar has been a driving force behind faculty hiring for the college, working with 18 departments to bring on dozens of scholars at the forefront of computing. In some ways, she says, it’s been a challenge to integrate the new hires into existing disciplines. “We have to keep teaching what we’ve been teaching for tens or hundreds of years, so change is hard and slow,” she says. But she has also noticed a palpable excitement about the new tools. Already, the college has brought in more than 30 new faculty members in four broad areas: climate and computing; human and natural intelligence; humanistic and social sciences; and AI for scientific discovery. In each case, they receive an academic home in another department, as well as an appointment, and often lab space, within the college. 

Asu Ozdaglar, SM ’98, PhD ’03, Schwarzman’s deputy dean of academics, in the lobby of the new headquarters building.

That commitment to interdisciplinary work has been built into every aspect of the new headquarters. “Most buildings at MIT come across as feeling pretty monolithic,” Huttenlocher says as he leads the way along brightly lit hallways and common spaces with large walls of glass looking out onto Vassar Street. “We wanted to make this feel as open and accessible as possible.” While the Institute’s high-end computing takes place mostly at a massive computing center in Holyoke, about 90 miles away in Western Massachusetts, the building is honey­combed with labs and communal workspaces, all made light and airy with glass and natural blond wood. Along the halls, open doorways offer enticing glimpses of such things as a giant robot hanging from a ceiling amid a tangle of wires. 

Lab and office space for faculty research groups working on related problems­—who might be from, say, CSAIL and LIDS—is interspersed on the same floor to encourage interaction and collaboration. “It’s great because it builds connections across labs,” Huttenlocher says. “Even the conference room does not belong to either the lab or the college, so people actually have to collaborate to use it.” Another dedicated space is available six months at a time, by application, for special collaborative projects. The first group to use it, last spring, focused on bringing computation to the climate challenge. To make sure undergrads use the building too, there’s a classroom and a 250-seat lecture hall, which now hosts classic Course 6 classes (such as Intro to Machine Learning) as well as new multidiscipline classes. A soaring central lobby lined with comfortable booths and modular furniture is ready-made for study sessions. 


For some of the new faculty, working at the college is a welcome change from previous academic experiences in which they often felt caught between disciplines. “The intersection of climate sustainability and AI was nascent when I started my PhD in 2015,” says Sherrie Wang, an assistant professor with a shared appointment in mechanical engineering and the Institute for Data, Systems, and Society, who is principal investigator of the Earth Intelligence Lab. When she hit the job market in 2022, it still wasn’t clear which department she’d be in. Now a part of Schwarzman’s climate cluster, she says her work uses machine learning to analyze satellite data, examining crop distribution and agricultural practices across the world. “It’s great to have a cohort of people who have similar philosophical motivations in applying these tools to real-world problems,” she says. “At the same time, we’re pushing the tools forward as well.”

Among other researchers, she plans to collaborate with Sara Beery, a CSAIL professor who analyzes vast troves of visual, auditory, and other data from a diverse range of sensors around the world to better understand how climate change is affecting distribution of species. “AI can be successful in helping human experts efficiently process terabytes and petabytes of data so they can make informed management decisions in real time rather than five years later,” says Beery, who was drawn to the college’s unique hybrid nature. “We need a new generation of researchers that frame their work by bringing different types of knowledge together. At Schwarzman, there is a clear vision that this type of work is going to be necessary to solve these big, essential problems.” 

Beery is now working to develop a class in machine learning and sustainability with two other new faculty members in the climate cluster: Abigail Bodner, an assistant professor in EECS and Earth, Atmospheric, and Planetary Sciences (whose work uses AI to analyze fluid dynamics), and Priya Donti, assistant professor in EECS and LIDS (who uses AI and computing to optimize integration of renewable energy into power grids). “There’s already a core course on AI and machine learning­—an on-ramp for people without prior exposure who want to gain those fundamentals,” says Donti. “The new class would be for those who want to study advanced AI/ML topics within the context of sustainability-­related disciplines, including power systems, biodiversity, and climate science.” 

The class on machine learning and sustainability would be part of Common Ground for Computer Education, an initiative cochaired by Ozdaglar and involving several dozen faculty members across MIT to develop new classes integrating advanced computing with other disciplines. So far, says Ozdaglar, it has generated more than a dozen new courses. One machine-learning class developed with input from nine departments provides exposure to a variety of practical applications for AI algorithms. Another collaboration, between computer science and urban studies, uses data visualization to address housing issues and other societal challenges. 

Julia Schneider ’26, a double major in AI and mathematics, took the Common Ground class on optimization methods, which she says demonstrated how computer science concepts like shortest-path algorithms and reinforcement learning could be applied in other areas, such as economics and business analytics. She adds that she values such classes because they blend her two areas of study and highlight multidisciplinary opportunities. 

“Even faculty who are leading researchers in this area say ‘I can’t read fast enough to keep up with what’s going on.’”

Dan Huttenlocher

Natasha Hirt ’23, MEng ’23, came to MIT thinking that computer science was peripheral to her major in architecture and urban planning. Then she took a course with building technology professor Caitlin Mueller on structural optimization and design—and it changed the trajectory of her MIT career. That led her to Interactive Data Visualization and Society, a Common Ground class, and several interdisciplinary classes combining computer science and field-specific knowledge. She says these provided the perfect introduction to algorithms without delving too much into math or coding,giving her enough working knowledge to set up models correctly and understand how things can go wrong. “They are teaching you what an engine is, what it looks like, and how it works without actually requiring you to know how to build an engine from scratch,” she says, though she adds that the classes also gave her the opportunity to tinker with the engine.

She’s now working on master’s degrees in both building technology and computation science and engineering, focusing on making buildings more sustainable by using computational tools to design novel, less material-intensive structures. She says that Common Ground facilitates an environment where students don’t have to be computer science majors to learn the computational skills they need to succeed in their fields. 

And that’s the intent. “My hope is that this new way of thinking and these educational innovations will have an impact both nationally and globally,” Ozdaglar says.

The same goes for recent papers MIT has commissioned, both on AI and public policy and on applications of generative AI. As generative AI has spread through many realms of society, it has become an ethical minefield, giving rise to problems from intellectual-property theft to deepfakes. “The likely consequence has been to both over- and under-­regulate AI, because the understanding isn’t there,” Huttenlocher says. But the technology has developed so rapidly it’s been nearly impossible for policymakers to keep up. “Even faculty who are leading researchers in this area say ‘I can’t read fast enough to keep up with what’s going on,’” Huttenlocher says, “so that heightens the challenge—and the need.”

The college has responded by engaging faculty at the cutting edge of their disciplines to issue policy briefs for government leaders. First was a general framework written in the fall of 2023 by Huttenlocher, Ozdaglar, and the head of MIT’s DC office, David Goldston, with input from more than a dozen MIT faculty members. The brief spells out essential tasks for helping the US maintain its AI leadership, as well as crucial considerations for regulation. The college followed that up with a policy brief by EECS faculty specifically focusing on large language models such as ChatGPT. Others dealt with AI’s impact on the workforce, the effectiveness of labeling AI content, and AI in education. Along with the written documents, faculty have briefed congressional committees and federal agencies in person to get the information directly into the hands of policymakers. “The question has been ‘How do we take MIT’s specific academic knowledge and put it into a form that’s accessible?’” Huttenlocher says. 

On a parallel track, in July of 2023 President Sally Kornbluth and Provost Cynthia Barnhart, SM ’86, PhD ’88, issued a call for papers by MIT faculty and researchers to “articulate effective road maps, policy recommendations, and calls for action across the broad domain of generative AI.” Huttenlocher and Ozdaglar played a key role in evaluating the 75 proposals that came in. Ultimately, 27 proposals­—exploring the implications of generative AI for such areas as financial advice, music discovery, and sustainability—were selected from interdisciplinary teams of authors representing all five schools. Each of the 27 teams received between $50,000 and $70,000 in seed funds to research and write 10-page impact papers, which were due by December 2023. 

Given the enthusiastic response, MIT sent out another call in the fall of 2023, resulting in an additional 53 proposals, with 16 selected in March, on topics including visual art, drug discovery, and privacy. As with the policy briefs, Huttenlocher says, “we are trying to provide the fresher information an active researcher in the field would have, presented in a way that a broader audience can understand.”

Even in the short time the college has been active, Huttenlocher and Ozdaglar have begun to see its effects. “We’re seeing departments starting to change some of the ways they are hiring around degree programs because of interactions with the college,” Huttenlocher says. “There is such a huge acceleration of AI in the world—it’s getting them to think with some urgency in doing this.” Whether through faculty hiring, new courses, policy papers, or just the existence of a space for high-level discussions about computing that had no natural home before, Huttenlocher says, the college hopes to invite the MIT community into a deeper discussion of how AI and other advanced computing tools can augment academic activities around campus. MIT has long been a leader in the development of AI, and for many years it has continued to innovate at the cutting edge of the field. With the college’s leadership, the Institute is in a position to continue innovating and to guide the future of the technology more broadly. “The next step,” says Ozdaglar, “is to take that impact out into the world.”