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

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

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

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

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

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

Overcoming the limits

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

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

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

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

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

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

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

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

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

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

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

Leveraging magnetism

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

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

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

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

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

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

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

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

The government should not help a religious institution to punish or deter members from inquiring about their faith. Yet, once again, the Watch Tower Bible and Tract Society is trying to use flimsy copyright claims to exploit the special legal tools available to copyright owners in order to unmask anonymous online speakers. And, once again, EFF has stepped in to urge the courts not to give Watch Tower’s attempts the force of law, with the help of local counsel Jonathan Phillips of Phillips & Bathke, P.C.

EFF’s client, J. Doe, is a member of the Jehovah’s Witnesses who became interested in the history of the organization’s public statements, and how they’ve changed over time. They created research tools to analyze those documents and ultimately created a website, JWS Library, allowing others to use those tools and verify their findings through an archive that included documents suppressed by the church. Doe and others discovered prophecies that failed to come true, erasure of a leader’s disgrace, increased calls for obedience and donations, and other insights about the Jehovah’s Witnesses’ practices. Doe also used machine translation on a foreign-language document to help the community understand what the church was saying to different audiences and also to help understand potential changes in the organization’s attitudes towards dissent.

Within the church, dissent or even asking questions has often been punished by labeling members as apostates and ostracizing—or “disfellowshipping”— them. As a result, Doe and others choose to speak anonymously to avoid retaliation that could cost them family, friend, and professional relationships.

There is no law against questioning the Jehovah’s Witnesses. Instead, Watch Tower argues that Doe’s activities constitute copyright infringement and seeks to use the special process provided in the Digital Millennium Copyright Act (DMCA) to unmask them. It sent DMCA subpoenas to Google and Cloudflare, seeking information that would help them uncover Doe’s identity.

The problem for Watch Tower is that Doe’s research and commentary are clear fair uses allowed under copyright law. The First Amendment does not permit the unmasking of anonymous speakers based on such weak claims. Indeed, the First Amendment protects anonymous speakers precisely because some would be deterred from speaking if they faced retribution for doing so.

EFF stands with those who question the claims of those in power and who share the tools and knowledge needed to do so. We urge the judges in the Southern District of New York to quash these improper subpoenas and not allow copyright to be used to suppress important, legitimate speech.

With time dwindling in the Olympic women’s ice hockey gold medal game on Feb. 19, players for Team USA and Team Canada lined up for a key faceoff in Canada’s end. Canada had a 1-0 lead. USA had 2:23 left, and an ace up their sleeve: analytics.

USA Coach John Wroblewski pulled the goalkeeper, to get a player advantage, and had forward Alex Carpenter take the faceoff. Statistics show that Carpenter is not only very good at winning faceoffs; she also wins a lot of them cleanly. That allows her team to quickly regain possession, without too many teammates nearby. Knowing that, Wroblewski directed the USA players to spread out, largely away from the faceoff circle, in position to circulate the puck as soon as they got it back.

Carpenter won the faceoff, and Team USA quickly started a passing move. Laila Edwards soon launched a shot that longtime star Hilary Knight deflected in for the crucial, game-tying goal with 2:04 left. Team USA then won in overtime. And data-driven decision-making had also won big; indeed, it helped change the Olympics.

“What it does for a coach, the other thing these analytics do, is … it allows you to move forward with this confidence level,” Wroblewski said on Saturday at the 20th annual MIT Sloan Sports Analytics Conference (SSAC), during a hockey analytics panel where he detailed his decision-making for that faceoff, and in the gold medal game generally.

Using the data, he added, lets coaches “limit the emotion” that might cloud their in-game decisions.

“By the time you get to that decision, you’re then allowed the freedom to step away from the decision, to allow the players to go earn their medal,” Wroblewski added.

You don’t usually find coaches divulging their tactical secrets just three weeks after a big game has been played. But then, this is the MIT Sloan conference, a trailblazing forum that has helped analytics ideas spread throughout sports. Coaches, players, and analysts know any data-driven discussion will find an interested audience.

“Analytics was massive for us going into the gold medal game,” Wroblewski said.

20 years on: From classrooms to convention halls

The 20th edition of SSAC was a strong one, with many substantive panel discussions and interviews; the annual research paper, hackathon, and case study contests; mentorship events and informal networking opportunities; and more. Over 2,500 people attended the two-day event, held at Boston’s Menino Conference and Exhibition Center (MCEC). The conference was founded in 2007 by Daryl Morey, now president of basketball operations for the NBA Philadelphia 76ers, and Jessica Gelman, now CEO of the Kraft Analytics Group.

The first three editions of the conference were held on the MIT campus. In 2010, it first moved to the MCEC (one of two regular convention-center sites it uses), and starting in 2011, the conference became a two-day event.

Today people attend for the panels, the career opportunities, and, in some cases, to make news. NBA Commissioner Adam Silver was on hand this year, engaging in an on-stage conversation with former WNBA great Sue Bird, publicly addressing some of the key issues facing his league, and drawing wide media coverage.

First, though, Silver reflected about attending the second edition of the conference on the MIT campus in 2008, when he was deputy commissioner.

“It was literally a classroom of 20 people we were talking to,” Silver recalled. “I think it was the beginning of the moment when people were taking sports as a discipline more seriously. … I give Jessica and Daryl a lot of credit [for that].”

Addressing tanking and gambling

A core part of Silver’s comments focused on two big issues in pro basketball: tanking and gambling. About eight NBA teams appear to be tanking this season, that is, losing games in order to increase their chances of getting a high draft pick.

“We are going to make substantial changes for next year,” Silver said, although he also added: “I am an incrementalist. I think we’ve got to be a little bit careful about how huge a change we make at once. I’m not ruling anything out. But I am paying attention to that.”

To be sure, tanking has long been a part of professional basketball, as Bird noted during the conversation.

“We did it in Seattle, to be honest,” Bird said. “Breanna Stewart was coming out of college. We were in a ‘rebuild.’”

Still, in this NBA season, tanking has become an epidemic, in “a little bit of a perfect storm,” as Silver put it on Friday. And almost every proposed solution seems to have drawbacks. Perhaps the simplest cure for tanking, actually, would be robust analytical studies showing that it is not a very effective team-building strategy. If that is what the numbers reveal, of course.

Meanwhile, multiple arrests of NBA players and coaches at the beginning of the season show further that sports gambling continues to present challenges to professional sports leagues.

“I personally think there should be more regulation now, not less,” Silver said on Friday, suggesting that federal rules would simplify things in the U.S., where 39 states allow sports gambling to some extent. He also said the NBA can continue to work on monitoring data to protect against gambling scandals.

“I think there are some large-platform companies are that are looking at a business opportunity to come in and in a much more sophisticated way work as a detection service with the league,” Silver said.

Through it all, Silver said, the NBA will continue to be a data-driven operation. Have you watched a game with a long instant-replay review, and gotten a little impatient? Still, have you kept watching that game? So does almost everyone.

“For years people would tell us, ‘Don’t use instant replay, because you’ll turn fans off,’” Silver said. However, he added, “The data suggests, in terms of ratings and what servers tell us, you almost never lose a fan when you’re going to replay. Because they want to see the replay and they want to see what happened.”

The minnows got big

Sports analytics took root in baseball, with its discrete pitcher-hitter actions. Legendary MLB general manager Branch Rickey employed a statistician for the great Brooklyn Dodgers of the 1950s; the famous manager Earl Weaver thought analytically with the Baltimore Orioles in the 1970s. Baseball analyst Bill James made sports analytics a viable pursuit with his annual “Baseball Abstract” bestsellers in the 1980s, and Michael Lewis’ “Moneyball” popularized it.

But data can be applied to all sports — and sometimes is most valuable when only some teams are interested in it. Take soccer. In the English Premier League, about three clubs have been heavily oriented around analytics over the last decade: Liverpool FC, Brighton FC, and Brentford FC. That has helped Liverpool win multiple titles, while Brighton and Brentford, smaller clubs, have startled many with their success.

Saturday at SSAC, Brentford’s majority owner Matthew Benham made one of his most visible public appearances, in an onstage interview with podcaster Roger Bennett. Benham first made money wagering on soccer, then invested in Brentford, his childhood club.

“The information we used in the early days was really, really rudimentary,” Benham said. In his account, his success building an analytics-based club has only partly been about the numbers.

“A lot of the success has just been in running things efficiently.” Benham said. He prefers to have management discussions that are an “exchange of views, rather than debate,” since the latter implies an interaction with a clear winner and loser. Instead, compiling independent-minded views from his executives is more important.

Brentford also uses “a combination of old-style scouting and data” for its player acquisition decisions, Benham said. Not every decision works. Brentford could have signed current Arsenal FC star Eberechi Eze for a mere $4 million pounds in 2019, and passed; Crystal Palace FC acquired Eze, then realized a windfall when Arsenal purchased his services.

Still, pressed by Bennett to specify a little more about his analytical thinking, Benham implied that strikers are valuable not only for their finishing skills, but for consistently getting open for shots on goal. Fans tend to focus too much on a player’s misses, rather than how many chances are created by their off-ball work.

“Getting in position is way, way more informative than finishing,” Benham said.

A similar insight seems to have guided Liverpool’s thinking. As it happens, a Friday panel at SSAC featured Ian Graham, who ran Liverpool’s analytics operations from 2012 to 2023, and weighed in on a number of subjects. Among other things, Graham noted, teams are too cautious when tied late in a match; soccer grants three points for a win, one for a draw, and zero for a loss, so from a tied position, the reward for winning is twice as great as the penalty for losing.

“Teams don’t go for it enough,” Graham said. “Teams think a draw is an okay result.”

The limits of knowledge

Sports, of course, are ultimately played by imperfect, injury-prone, and sometimes exhausted athletes. One consistent lesson from the MIT Sloan conference involves the limits of data and plans.

“We think the data is giving us an answer, when actually it’s giving us some information, and we still have to make a choice,” said Ariana Andonian, vice president of player personnel for the Philadelphia 76ers, during a basketball panel on Saturday.

Asked about the promise of artificial intelligence for sports analytics, Sonia Raman, head coach of the WNBA’s Seattle Storm, noted that its insights might always be limited by circumstances.

“It’s not like you can just get an AI report in the middle of the game that says, ‘Get some shooting in,’” said Raman, who, prior to coaching in the WNBA and NBA served for 12 years as head coach of the MIT women’s basketball team.

“You can have a great plan, but if it’s poorly executed, it’s way worse than a poor plan that’s well executed,” added Steven Adams, a center for the NBA’s Houston Rockets (who is currently not playing due to injury), during the same panel.

And yet, in some games and matches, the analytics do work, the plans do come to fruition, and the numbers do make a difference. When that happens, as John Wroblewski can now attest, the results are golden. 

Over the last decade or so, the tech industry has tried, and mostly failed, to make “smart glasses”—tech-infused glasses with cameras, AI, maps, displays, and more—a thing. But over the past year, products like Meta’s Ray-Ban Display Glasses and Oakley’s Meta Glasses have gone from a curious niche to the mainstream. 

Before you strap a dashcam to your face and sprint out into the world filming everything and everyone in your life, there are some civil liberties and privacy concerns to consider before buying or using a pair.

Meta is the biggest company that makes these sorts of glasses and their partnerships with Ray-Ban and Oakely are the most popular options, so we’ll be mostly focusing on them here. Others, like models from Snapchat are similar in form but far less ubiquitous. But Meta won’t hold this space for long. Google’s already announced a partnership with Warby Parker for their “AI-powered smart glasses,” and there are rumors around a competing product from Apple. 

With that, let’s dive into some of the considerations you should make before purchasing a pair.

If You’re Thinking About Buying Smart Glasses You’re likely not the only one who can see (and hear) your footage

The photos and videos you record with most smartglasses will likely be stored online at some point in the process. On Meta’s offerings, unless you are livestreaming, media you capture when you press the camera button is kept on the glasses until you import them onto your phone, but media is imported automatically by default into the Meta AI mobile app, which is required to set up the glasses. 

You can't use any AI features locally on the glasses. So anytime you use AI features, like when you say, “Hey Meta, start recording,” the footage is fed to Meta. You can use the glasses without the Meta AI app entirely, but considering you can’t easily download footage from the glasses to your phone without it, most people will likely use the app.

Some videos are fed to Meta for AI training, and we know at least in some cases that those videos go through human review. An investigation by Swedish newspapers found that workers were reviewing and annotating camera footage, which includes all sorts of sensitive videos, including nudity, sex, and going to the bathroom. Meta claimed to the BBC that this is in accordance with its terms of use, all in the name of AI training, which states:

In some cases, Meta will review your interactions with AIs, including the content of your conversations with or messages to AIs, and this review may be automated or manual (human).

This all means that Meta and their third-party contractors will have access to at least some of what you record, and it’s very hard as a user to know where footage goes, who will have access to it, and what they will do with it. When you save footage to your phone’s camera roll, which is where the Meta AI app stores content, that might also be sent to Apple or Google’s servers, depending on your settings. Employees at these companies can then possibly access that media, and it could be shared with law enforcement.

The recorded audio from conversations with Meta AI are also saved by default, and if you don’t like that, tough luck, unless you go in and manually delete them every time you say something.

Filming all the time is even more privacy invasive than you think

A common argument in favor of using the cameras in smartglasses is that phones and cameras can do this too, and it’s never been a problem. 

But smartglasses are designed to resemble regular glasses, to the point where most reviews point out how friends didn’t notice that they had cameras embedded in them. They’re designed to be invisible to those being recorded outside of a small indicator light when they’re recording video footage (that cheap hacks can disable). Whereas it is often obvious that a person is recording if they pull their phone out of their pocket and point it at someone else.

They’re designed to be invisible to those being recorded outside of a small indicator light when they’re recording video footage

Moreover, constant recording of everything in public spaces can create all sorts of potential privacy problems, some more obvious than others. This is another way that cameras on glasses are different from cameras on phones: it is far easier to constantly record one’s whereabouts with the former than the latter. If you continuously record, maybe you just happen to catch someone entering their passcode or password onto their phone or computer at a coffee shop, or broadcast someone’s bank details when you’re standing in line at an ATM. That doesn’t even begin to get into when smartglasses are intentionally used for less socially responsible means. And some people may forget to turn off their smartglasses when they enter a private space like a bathroom.  

And if you find yourself caught on someone’s camera, there’s not much you can do in recourse. If you do notice a stranger recording you, it’s up to you to intervene and ask not to be included in that footage, which can easily turn awkward or confrontational.

Our expectations of privacy shift when we’re in public, but bystanders in many cases will still have privacy interests. Public spaces are a place where you will be seen, but that shouldn’t mean it’s suddenly okay to catalog and identify everyone.

Consider the company’s the track record and public statements

Meta, Google, Apple—perhaps one benefit of all the major tech companies entering this market is that we already have a good idea of how much they tend to respect the privacy of their users or the openness of their platforms. Spoiler, it’s often not much.

Meta has a long history of privacy invasive technologies and practices. We’ve heard rumblings that Meta hopes to add face recognition to its smartglasses, preferably, “during a dynamic political environment where many civil society groups that we would expect to attack us would have their resources focused on other concerns.” Yikes. This is a monumentally bad idea that should be abandoned by Meta and any of its competitors considering a similar feature. But regardless of whether they launch this feature, it’s a pretty clear indication of where Meta wants these sorts of devices to go. 

If You Have Smartglasses Already Opt out of sharing with Meta where you can

You can disable a couple of the features where unnecessary data is sent to Meta. In the Meta AI app, under the device settings, there’s a privacy page where you can disable sharing additional data, and more importantly, turn off “Cloud media,” where your photos and videos are sent to Meta’s cloud for processing and temporary storage. 

Decide your use-case and stick to it

These glasses can be useful for filming a variety of activities. We’ve seen fascinating scenes of tattoo artists doing their work (with client’s permission), and it doesn’t take a stretch of the imagination to see how people might use it to film extreme sports. Even on an everyday level, you might find them useful for capturing holidays, birthdays, and all sorts of other private occasions. 

But if you buy these glasses for a specific, mostly private purpose, it is probably best to stick to that, instead of wearing them everywhere and recording everything you do.

Follow the rules of a businesses and social expectations

You often have a right to record in public spaces, but that doesn’t mean other people will like it. Businesses, including restaurants and stores, may want nothing to do with continuous filming and may either post a sign asking you not to use smartglasses, or ask you to stop. This may reflect the preferences not just of the business owner, but the people around you. And don’t use glasses to record when you enter other people’s private spaces like bathrooms or changing rooms.

It’s also a good idea to check in with friends and family before tapping that record button at a social gathering. Some people may not be as comfortable with these glasses as they are with other recording equipment.

Consider blurring strangers if you’re going to upload video

Blurring video footage isn’t an easy task, but if you’re considering uploading footage from something like a protest, it may be worth the effort to do so (apps like Meta’s Edits simplify this process, as do some other video sites, like YouTube). Some people don’t want the government to see their faces at protests, and might be afraid to attend if other people are uploading their faces.

Some people don’t want the government to see their faces at protests, and might be afraid to attend if other people are uploading their faces.

It would be better if Meta leveraged its AI features to offer this sort of feature automatically, especially with livestreaming. It’s not that outlandish of a request, as it seems like the company tries to blur faces automatically in footage it captures for annotation, though it’s not always reliable. After all, Google began redacting faces in Street View years ago, following privacy concerns from groups like EFF.

Resist face recognition

Adding facial recognition technology to smartglasses would obliterate the privacy of everyone. We cannot let companies push face recognition into these glasses, and as a user, you should make your voice clear that this is not something you want.

Smartglasses don’t have to be used to decimate the privacy of anyone you encounter during the day. There are legitimate uses out there, but it’s up to those who use them to respect the social norms of the spaces they enter and the people they encounter.

Just as Darwin’s finches evolved in response to natural selection in order to endure, the cells that make up a cancerous tumor similarly counter selective pressures in order to survive, evolve, and spread. Tumors are, in fact, complex sets of cells with their own unique structure and ability to change. 

Today, artificial Intelligence and machine learning tools offer an unparalleled opportunity to illuminate the generalizable rules governing tumor progression on the genetic, epigenetic, metabolic, and microenvironmental levels. 

Matthew G. Jones, an assistant professor in the MIT Department of Biology, the Koch Institute for Integrative Cancer Research, and the Institute for Medical Engineering and Science, hopes to use computational approaches to build predictive models — to play a game of chess with cancer, making sense of a tumor’s ability to evolve and resist treatment with the ultimate goal of improving patient outcomes. In this interview, he describes his current work.

Q: What aspect of tumor progression are you working to explore and characterize? 

A: A very common story with cancer is that patients will respond to a therapy at first, and then eventually that treatment will stop working. The reason this largely happens is that tumors have an incredible, and very challenging, ability to evolve: the ability to change their genetic makeup, protein signaling composition, and cellular dynamics. The tumor as a system also evolves at a structural level. Oftentimes, the reason why a patient succumbs to a tumor is because either the tumor has evolved to a state we can no longer control, or it evolves in an unpredictable manner. 

In many ways, cancers can be thought of as, on the one hand, incredibly dysregulated and disorganized, and on the other hand, as having their own internal logic, which is constantly changing. The central thesis of my lab is that tumors follow stereotypical patterns in space and time, and we’re hoping to use computation and experimental technology to decode the molecular processes underlying these transformations.  

We’re focused on one specific way tumors are evolving through a form of DNA amplification called extrachromosomal DNA. Excised from the chromosome, these ecDNAs are circularized and exist as their own separate pool of DNA particles in the nucleus. 

Initially discovered in the 1960s, ecDNA were thought to be a rare event in cancer. However, as researchers began applying next-generation sequencing to large patient cohorts in the 2010s, it seemed like not only were these ecDNA amplifications conferring the ability of tumors to adapt to stresses, and therapies, faster, but that they were far more prevalent than initially thought.

We now know these ecDNA amplifications are apparent in about 25 percent of cancers, in the most aggressive cancers: brain, lung, and ovarian cancers. We have found that, for a variety of reasons, ecDNA amplifications are able to change the rule book by which tumors evolve in ways that allow them to accelerate to a more aggressive disease in very surprising ways. 

Q: How are you using machine learning and artificial intelligence to study ecDNA amplifications and tumor evolution? 

A: There’s a mandate to translate what I’m doing in the lab to improve patients’ lives. I want to start with patient data to discover how various evolutionary pressures are driving disease and the mutations we observe. 

One of the tools we use to study tumor evolution is single-cell lineage tracing technologies. Broadly, they allow us to study the lineages of individual cells. When we sample a particular cell, not only do we know what that cell looks like, but we can (ideally) pinpoint exactly when aggressive mutations appeared in the tumor’s history. That evolutionary history gives us a way of studying these dynamic processes that we otherwise wouldn’t be able to observe in real time, and helps us make sense of how we might be able to intercept that evolution. 

I hope we’re going to get better at stratifying patients who will respond to certain drugs, to anticipate and overcome drug resistance, and to identify new therapeutic targets.

Q: What excited you about joining the MIT community?

A: One of the things that I was really attracted to was the integration of excellence in both engineering and biological sciences. At the Koch Institute, every floor is structured to promote this interface between engineers and basic scientists, and beyond campus, we can connect with all the biomedical research enterprises in the greater Boston area. 

Another thing that drew me to MIT was the fact that it places such a strong emphasis on education, training, and investing in student success. I’m a personal believer that what distinguishes academic research from industry research is that academic research is fundamentally a service job, in that we are training the next generation of scientists. 

It was always a mission of mine to bring excellence to both computational and experimental technology disciplines. The types of trainees I’m hoping to recruit are those who are eager to collaborate and solve big problems that require both disciplines. The KI [Koch Institute] is uniquely set up for this type of hybrid lab: my dry lab is right next to my wet lab, and it’s a source of collaboration and connection, and that reflects the KI’s general vision. 

The rapidly escalating conflict between Anthropic and the Pentagon, which started when the company refused to let the government use its technology to spy on Americans, has now gone to court. The Department of Defense retaliated by designating the company a “supply chain risk” (SCR). Now, Anthropic is asking courts to block the designation, arguing that the First Amendment does not permit the government to coerce a private actor to rewrite its code to serve government ends.

We agree.

As EFF, the Foundation for Individual Rights and Expression, and multiple other public interest organizations explained in a brief filed in support of Anthropic’s motion, the development and operation of large language models involve multiple expressive choices protected by the First Amendment. Requiring a company to rewrite its code to remove guardrails means compelling different expression, a clear constitutional violation. Further, the public record shows that the SCR designation is intended to punish the company both for pushing back and for its CEO’s public statements explaining that AI may supercharge surveillance practices that current law has proven ill-equipped to address.

As we also explain, the company’s concerns about how the government will use its technology are well-founded. The U.S. government has a long history of illegally surveilling its citizens without adequate judicial oversight based on questionable interpretations of its Constitutional and statutory obligations. The Department of Defense acquires vast troves of personal information from commercial entities, including individuals’ physical location, social media, and web browsing data. Other government agencies continue to collect and query vast quantities of Americans’ information, including by acquiring information from third party data brokers.

A growing body of social science research illustrates the chilling effects of these pervasive activities. Fearing retribution for unpopular views, dissenters stay silent. And AI only exacerbates the problem. AI can quickly analyze the government’s massive datasets or combine that information with data scraped off the internet, purchased through the commercial data broker market, or from local police surveillance devices and use all of that data to construct a comprehensive picture of a person’s life and infer sensitive details like their religious beliefs, medical conditions, political opinions, or even sex partners. For example, an agency could use AI to infer an individual’s association with a particular mosque based on data showing that they visited its website, followed its social media accounts, and were located near the mosque during religious services. AI can also deanonymize online speech by using public information to unmask anonymous users.

It is easy to conceive how an agency, a government employee with improper intent, or a malicious hacker could exploit these capabilities to monitor public discourse, preemptively squelch dissent, or persecute people from marginalized communities. Against this background and absent meaningful changes to the governing national security laws and judicial oversight structure, it is entirely reasonable for Anthropic—or any other company—to insist on its own guardrails.

Without action from Congress, the task of protecting your privacy has fallen in large part to Big Tech—something no one wants, including Big Tech. But if Congress won’t do it, companies like Anthropic must be allowed to step in, without facing retribution.

Joseph Paradiso thinks that the most engaging research questions usually span disciplines. 

Paradiso was trained as a physicist and completed his PhD in experimental high-energy physics at MIT in 1981. His father was a photographer and filmmaker working at MIT, MIT Lincoln Laboratory, and the MITRE Corporation, so he grew up in a house where artists, scientists, and engineers regularly gathered and interesting music was always playing. 

That mix of influences led him to the MIT Media Lab, where he is the Alexander W. Dreyfoos Professor, academic head of the Program in Media Arts and Sciences, and director of the Responsive Environments research group.

At the Media Lab, Paradiso conducts research that engages sensing of different kinds and applies it across diverse and often extreme applications. He works on developing technologies that can efficiently capture and process multiple sensing modalities, and leverages this capability in application domains like the internet of things, medicine, environmental sensing, space exploration, and artistic expression. These efforts use that information to help people better understand the world, express themselves, and connect with one another.

Early in his career, Paradiso helped pioneer the field of wireless wearable sensing. He built many systems with multiple embedded sensors that could send information from the human body in real-time. One of his early flagship projects in this area was a pair of shoes fielded in 1997 for real-time augmented dance performance that embedded 16 sensors in each shoe, allowing wearers’ movements to directly generate music through algorithmic mapping. And Paradiso’s research at the Media Lab has consistently focused on sensing and using that information in new ways. 

“When I would list all the sensors … people would laugh. But now, my watch is measuring most of these things,” Paradiso notes. “The world has moved.” 

That progression from early prototypes to everyday technology helped lay the groundwork for devices people now use regularly to track activity, health, and performance.

As sensing systems improved, Paradiso expanded his work from individuals to groups. He developed platforms that allowed dance ensembles to create music together through their collective motion. Achieving this required Paradiso and his team to develop new ways for compact wearable devices to communicate wirelessly at high speed, as well as new approaches to real-time data processing and extending the range of available microelectromechanical systems (MEMS) sensors.

Those same sensing platforms were later adapted for sports medicine in 2006. Working with doctors who support elite athletes, his array of compact, wearable sensors captured large amounts of high-speed motion data from multiple points on the body, aimed at helping clinicians assess injury risk, performance, and recovery on the go, without the complex equipment typically associated with biomechanical monitoring and clinical settings.

More recently, Paradiso’s research has extended beyond humans. Through collaborations with National Geographic Explorers, his team has deployed sensors in remote environments to study animal behavior, including low-power compact wearable devices to detect the environmental conditions around the animal as well as track them (currently on lions and hyenas in Botswana and goats in Chile), and acoustic sensors with onboard AI to detect and monitor populations of endangered honeybees in Patagonia. This work provides new ways to understand how ecosystems function and how the planet is changing.

Paradiso was named an IEEE Fellow in January, recognizing his achievement in wireless wearable sensing and mobile energy harvesting. This is the highest grade of membership in IEEE, the world’s leading professional association dedicated to advancing technology for the benefit of humanity.

Across art, health, and the natural world, Paradiso’s work reflects how foundational research at MIT can seed technologies that ripple outward over time, shaping new applications and opening new fields. As advances in wearable technologies drive the rush toward the ever-more-connected human, a persistent existential question lurks. 

“Where do I stop, versus others begin?” Paradiso asks. 

For him, the aim is not novelty for its own sake, but amplification: using technology to help people become more perceptive, better connected, and more aware of their place in a larger system.

Each year, faculty and researchers across the MIT School of Engineering are recognized with prestigious awards for their contributions to research, technology, society, and education. To celebrate these achievements, the school periodically highlights select honors received by members of its departments, institutes, labs, and centers. The following individuals were recognized in fall 2025:

Hal Abelson, the Class of 1922 Professor in the Department of Electrical Engineering and Computer Science, received the 2025 Lifetime Achievement Award for Excellence from Open Education Global. The award honors his foundational impact on open education, Creative Commons, and open knowledge movements.

Faez Ahmed, the Henry L. Doherty Career Development Professor in Ocean Utilization in the Department of Mechanical Engineering, received an Amazon Research Award for his project “AutoDA‑Sim: A Multi‑Agent Framework for Safe, Aesthetic, and Aerodynamic Vehicle Design.” Amazon Research Awards provide unrestricted funds and AWS Promotional Credits to academic researchers investigating various research topics in multiple disciplines.

Pulkit Agrawal, an associate professor in the Department of Electrical Engineering and Computer Science, received the 2025 IROS Toshio Fukuda Young Professional Award for contributions to robot learning, policy learning, agile locomotion, and dexterous manipulation. The award recognizes outstanding contributions of an individual of the IROS community who has pioneered activities in robotics and intelligent systems.

Ahmad Bahai, a professor of the practice in the Department of Electrical Engineering and Computer Science, was elected to the 2025 class of Fellows of the National Academy of Inventors for contribution to innovation in new semiconductor devices with extensive applications in clinical grade personal sensors for a variety of biomarkers. The honor recognizes inventors whose patented work has made a meaningful global impact.

Yufeng (Kevin) Chen, an associate professor in the Department of Electrical Engineering and Computer Science, received the 2025 IROS Toshio Fukuda Young Professional Award for contributions to insect‑scale multimodal robots and soft‑actuated aerial systems. The award recognizes outstanding contributions of an individual of the IROS community who has pioneered activities in robotics and intelligent systems.

Angela Koehler, the Charles W. and Jennifer C. Johnson Professor in the Department of Biological Engineering, received the 2025 Sato Memorial International Award from the Pharmaceutical Society of Japan, recognizing advancements in pharmaceutical sciences and U.S.–Japan scientific collaboration.

Dina Katabi, the Thuan (1990) and Nicole Pham Professor in the Department of Electrical Engineering and Computer Science, was elected to the National Academy of Medicine for pioneering digital health technology that enables noninvasive, off-body remote health monitoring via AI and wireless signals, and for developing digital biomarkers for Parkinson’s progression and detection. Election to the academy is considered one of the highest honors in the fields of health and medicine, and recognizes individuals who have demonstrated outstanding professional achievement and commitment to service.

Darcy McRose, the Thomas D. and Virginia W. Cabot Career Development Professor in the Department of Civil and Environmental Engineering, was selected as a 2025 Packard Fellow for Science and Engineering. The Packard Foundation established the Packard Fellowships for Science and Engineering to allow the nation’s most promising early-career scientists and engineers flexible funding to take risks and explore new frontiers in their fields of study.

Muriel Médard, the NEC Professor of Software Science and Engineering in the Department of Electrical Engineering and Computer Science, received the 2026 IEEE Richard W. Hamming Medal for contributions to coding for reliable communications and networking. Recognized for breakthroughs in network coding and information theory, Médard’s innovations improve the reliability of data transmission in applications such as streaming video, wireless networks, and satellite communications. The award is given for exceptional contributions to information sciences, systems and technology.

Tess Smidt, an associate professor in the Department of Electrical Engineering and Computer Science, was selected as a 2025 AI2050 Fellow by Schmidt Sciences for her project, “Hierarchical Representations of Complex Physical Systems with Euclidean Neural Networks.” The program supports research that aims to help AI benefit humanity by mid‑century.

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