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🔊 Mass Surveillance for… Loud Music? | EFFector 38.11
Across the country, surveillance companies have spun a vast web of tens of thousands of license plate cameras. The people selling this tech want you to believe that it's for your safety, but how are authorities really using automated license plate readers (ALPR)? In this week's EFFector newsletter, we're looking at how these powerful surveillance networks have become universal people-trackers used for noise complaints and other low-level investigations.
For over 35 years, EFFector has been your guide to understanding the intersection of technology, civil liberties, and the law. This week's issue covers a victory for facial privacy, EFF's testimony to Congress about AI and surveillance, and troubling new examples of ALPR mission creep.
Prefer to listen in? EFFector is now available on all major podcast platforms. This week, we're chatting with EFF Associate Director of State Affairs Rindala Alajaji about what she uncovered about police use of ALPR. And don't miss the EFFector news quiz. You can find the episode and subscribe on your podcast platform of choice:
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Pablo Jarillo-Herrero wins Kavli Prize in Nanoscience
MIT professor of physics Pablo Jarillo-Herrero is among 10 researchers worldwide to receive this year’s prestigious Kavli Prize.
Jarillo-Herrero is co-recipient of the 2026 Kavli Prize in Nanoscience “for foundational work that established the field of twistronics.” His co-recipients are professors Eva Y. Andrei at Rutgers University and Allan MacDonald from the University of Texas at Austin.
These three physicists are being honored for the theoretical foundation and experimental validation of a new field of “twistronics,” where superconductivity, magnetism, and other properties can be obtained by rotating two-dimensional materials such as graphene to a “magic angle.”
A partnership among the Norwegian Academy of Science and Letters, the Norwegian Ministry of Education and Research, and the Kavli Foundation, the Kavli Prizes are awarded every two years to “honor scientists for breakthroughs in astrophysics, nanoscience and neuroscience that transform our understanding of the big, the small and the complex.” The laureates in each field will share $1 million.
“Pablo’s groundbreaking research has once again been given well-deserved recognition,” says Nergis Mavalvala, dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics. “Pablo and his co-recipients have pioneered twistronics, very fundamental scientific research that has opened up a new field with myriad possibilities for novel quantum materials.”
In 2009, using scanning tunneling microscopy and spectroscopy on graphene, most commonly found as a single layer of carbon atoms arranged in hexagons resembling a honeycomb structure, Andrei and her research group demonstrated that small variations in twist angle profoundly modified the electronic structure. This demonstration — that geometric control, rather than chemical composition, could modify a material’s electronic structure — represented a fundamental advance in materials design and arguably launched the field now known as “twistronics.”
In 2011, MacDonald quantitatively explained the emergence of this electronic structure by geometries at discrete magic angles. This framework has since become the theoretical foundation of what are known as moiré materials, and has guided subsequent experimental and theoretical developments across a wide range of twisted and layered systems.
In 2018, Jarillo-Herrero’s group observed correlated insulating phases and superconductivity in magic-angle twisted bilayer graphene devices. The resulting platform, “combining atomic-scale structural simplicity with electronic tunability, has enabled systematic investigations has had broad and lasting impact across nanoscience and quantum material research,” according to the Kavli Prize citation.
“It was a big surprise, because the technique we used, though conceptually straightforward, was hard to pull off in the lab,” said Jarillo-Herrero recently. He is also the Cecil and Ida Green Professor of Physics at MIT and a member of the Research Laboratory of Electronics.
“I’m humbled and incredibly honored to be sharing this award with [Andrei and MacDonald],” Jarillo-Herrero noted in an essay describing his journey to the Kavli Prize. “I want to also emphasize that this award honors fundamental physics research in nanoscience. It is incredibly important for society to continue to support fundamental research: Although it often doesn’t have a direct near-term application, in the long run it happens to be the most transformative and impactful in society.”
“Pablo’s research has helped spark a revolution in condensed matter physics and nanoscience, inspiring physicists worldwide to explore superconductivity and other emergent phenomena in engineered quantum materials. This work could potentially lead to the creation of superconductors at room temperature, which would would have an enormous technological impact,” says Deepto Chakrabarty, physics department head and William A. M. Burden Professor in Astrophysics.
Jarillo-Herrero's win brings the number of all-time MIT faculty recipients of the Kavli Prize to nine. Prior winners include Nancy Kanwisher in neuroscience (2024), Bob Langer in nanoscience (2024), Sara Seager in astrophysics (2024), Rainer Weiss in astrophysics (2016), Alan Guth in astrophysics (2014), Mildred Dresselhaus in nanoscience (2012), Ann Graybiel in neuroscience (2012), and Jane Luu in astrophysics (2012).
NSO Group Hacking WhatsApp Despite Court Order
WhatsApp has caught the NSO Group phishing its users, in violation of a court order.
The worst-case climate scenario is gone. The catch? The best case is, too.
Why two giant power lines aren’t enough to green the Northeast grid
Top insurance candidate in California seeks ‘radical’ overhaul
EIA says global oil demand to fall by 1M barrels a day this year
EU wants African sunlight to power Europe’s electric revolution
Turkey, Australia to push for global electrification goal at UN climate summit
Extreme heat risks losses for Indian suppliers to Uniqlo, Tesco
Tropical Storm Cristina forms off coast of Nicaragua, forecasters say
Augmented reality system could make medical ultrasounds easier to interpret
Interpreting medical ultrasound images is a difficult task, requiring a technician to look at 2D images and mentally arrange them into a 3D representation of what the tissue looks like.
To make that job easier, MIT researchers developed a new approach to ultrasound imaging that allows the user to visualize a 3D augmented-reality image of the object being scanned. Using a virtual-reality headset, they can see a precise 3D digital representation of what the object actually looks like, making it easier to identify and analyze.
This technique could help speed up the training process for ultrasound technicians and other health care providers who use ultrasound. It could also be deployed for use in hospitals, for tasks such as using ultrasound to place a needle in the right location for a biopsy.
“For training, this could make ultrasound more intuitive and more understandable. On the clinical side, it could be less time-consuming, more accurate, and also give health care providers more peace of mind. They wouldn’t have to wonder if they missed anything,” says Canan Dagdeviren, an associate professor of media arts and sciences at MIT and the senior author of the study.
MIT graduate students Jason Hou and Shrihari Viswanath are the lead authors of the paper, which appears today in Nature Communications Engineering. Other authors of the paper include Bowen Wu ’24 and two MIT Summer Research Program students, Cinay Dilibal, a senior at Dartmouth College, and Tanisha Shende, a senior at Oberlin College.
3D representations
Ultrasound imaging works by bouncing high-frequency sound waves off tissues in the body, which are then reflected back to an ultrasound transducer. The transducer converts these sound waves to electrical signals, which are used to create a 2D image of the tissue. Ultrasound technicians are trained to convert these images into a 3D mental representation of the tissue.
“It's a difficult skill to master, and there are long learning curves,” says Hou. “The hardest thing is this mental tomography bottleneck where you’re trained to reconstruct the 2D slices in your 3D mental space. That is a cognitive burden that can lead to inaccuracies in scanning.”
To reduce that cognitive load, the MIT team thought it could be helpful to combine two technologies: 3D ultrasound imaging and augmented reality (AR).
Three-dimensional ultrasound imaging is occasionally used in fields such as fetal imaging and echocardiography, which is used to image the heart, but most 3D ultrasound imaging systems are expensive and not widely available. For this study, the MIT team used a real-time 3D system they developed recently for use in breast-cancer detection.
Their new system includes an ultrasound probe, slightly smaller than a deck of cards, that transmits information using a chirped data acquisition system (cDAQ). The probe contains an ultrasound array arranged in the shape of an empty square, a configuration that allows the array to take 3D images of the tissue below.
Because this system has fewer ultrasound elements than a typical 3D ultrasound system, it requires less power and is less expensive to build.
The data collected by the ultrasound probe can then be compressed and streamed into a 3D computer graphics engine called Unreal Engine, which converts the voxel data from the ultrasound image into a direct 3D representation of the object, with no loss of information. Wearing an AR/VR headset, the user can see this 3D rendering representing the internal structure, superimposed over the object’s actual location — like X-ray vision. By tilting their head or approaching from a different direction, the user can see different views of the object, making it easier to identify.
Easier to use
The researchers tested their new technology, which they call AR-VIU (augmented real-time volumetric imaging in ultrasound), with a group of 18 participants. Nine of the subjects were experts in ultrasound technology (including sonographers and physicians), and nine had never used ultrasound before.
Each user performed identification tasks using four different ultrasound technologies. In one condition, they viewed 2D images on a regular screen, which is the way that most ultrasounds are now performed. They also viewed 3D images on a regular screen, as well as two augmented reality conditions: one 2D and one 3D (AR-VIU).
In one round of experiments, users were asked to identify an object embedded in gelatin — such as a spring, a ball, or a screw — inside an opaque container that was scanned with ultrasound. In a second set, they were asked to use a pen to mark the location of “tissue phantom” — a gel-like material engineered to mimic human tissue. This simulates the task of locating the right spot for a needle during a biopsy.
The researchers found that the AR-VIU system significantly improved all users’ ability to identify and locate objects. The effect was especially strong for novices, who performed nearly as well as experts when using AR-VIU. When using the traditional 2D imaging system, experts performed much better than novices.
“Overlaying images with the anatomy and providing 3D visual context makes ultrasound significantly easier for novices to understand,” Viswanath says.
In interviews after the experiments, most of the novices reported that they preferred the AR-VIU approach, with many saying that it made the tasks easier.
“The 3D system imposes less brain drain, it’s more intuitive, and it’s easier to understand what is happening in the targeted region,” Dagdeviren says.
Many of the experts said they preferred the traditional 2D imaging because that is what they were accustomed to and had been trained to use. However, those experts also said they could see the benefits of the AR-VIU system in some situations, such as placing a needle for a biopsy or visualizing the movement of the heart wall during echocardiography.
The researchers are now working on further improving the resolution of the imaging and doing additional tests to demonstrate the accuracy of the AR-VIU technology.
The research was funded by the MIT Media Lab Consortium, the National Science Foundation, an MIT HEALS graduate fellowship, and an MIT-Tata graduate fellowship.
Human-driven sea-level rise has quadrupled the frequency of coastal sea-level extremes since 1900
Nature Climate Change, Published online: 10 June 2026; doi:10.1038/s41558-026-02659-0
Sea-level rise in conjunction with storm surge and tidal variations leads to extreme sea levels that threaten coastal systems. Here the authors use tide-gauge data and models to quantify how anthropogenic climate change has increased the risk of these extreme sea-level events since 1900.Author Correction: Rising temperatures increase added sugar intake disproportionately in disadvantaged groups in the USA
Nature Climate Change, Published online: 10 June 2026; doi:10.1038/s41558-026-02689-8
Author Correction: Rising temperatures increase added sugar intake disproportionately in disadvantaged groups in the USAIncreasing tropical cyclone rainfall and landslide risk in Southern California
Nature Climate Change, Published online: 10 June 2026; doi:10.1038/s41558-026-02633-w
Southern California is rarely affected by tropical cyclones at present. Here the authors show that this could change with warming, leading to an increase in landslide risk that is expected to disproportionately affect low-income households.Startup’s nuclear-inspired cooling system could make data centers more sustainable
The rise of artificial intelligence is riding on the back of an enormous data center expansion. Data centers are projected to account for anywhere from 9 to 17 percent of total electricity usage in the U.S. by the end of the decade. Today, around a third of data center electricity is devoted to cooling the chips that run AI models.
That’s the process Ferveret is working to make more efficient. The startup, founded by Reza Azizian, a former MIT postdoc in nuclear engineering, and Matteo Bucci, MIT’s Esther and Harold E. Edgerton Associate Professor in the Department of Nuclear Science and Engineering, is adapting an approach from nuclear reactors to cool chips using no water and significantly less electricity.
The company’s cooling system submerges computer servers in a specialized liquid that absorbs heat much more efficiently than air from a fan. What makes the solution different from other liquid cooling systems are the bubbles: Ferveret’s Adaptive Phase Cooling (APC) solution produces much smaller bubbles at the surface of the server, which detach more frequently, accelerating the heat transfer process.
Ferveret is already testing its solutions with companies including CleanSpark, the data center developer and operator, as well as FuriosaAI, an AI accelerator company, and Switch, one of the largest data center operators in the U.S.
In a recent study in collaboration with the Samueli Computer Science Department at the University of California at Los Angeles, Ferveret found its APC solution led to a 15 percent improvement in computational power efficiency compared to state-of-the-art liquid cooling solutions. By combining those savings with Ferveret’s power control system to optimize operating conditions, the company says it allows data centers to get 35 percent more tokens — small pieces of text or data — from their AI models with the same amount of power.
“Our goal is to make data centers as sustainable as possible and help them use every single watt of power to generate tokens, which are the most useful outputs,” Azizian says. “Our system enables the operation of more powerful chips, it helps data centers waste a lot less energy, and it accomplishes all that with zero water consumption.”
From nuclear reactors to AI
Azizian was a postdoc at MIT in 2013 when he met Bucci, who was then a research scientist. They worked on heat transfer in nuclear reactors before Azizian went into industry, where he shifted his focus to cooling chips. Azizian first worked on Microsoft’s HoloLens augmented reality headset and then joined Nvidia, which produces the graphical processing units companies use to train and run the latest AI models. Meanwhile, Bucci continued conducting research at MIT, becoming an assistant professor in 2016.
Azizian walked into his first data center in 2017, where he was struck by the massive, noisy fans that filled the building as they cooled.
“I thought, ‘Holy crap, this is not how you cool facilities,’” Azizian recalls, noting air cooling can still take up 40 percent of the power going into a data center. “It was not an efficient way of doing things, but since it wasn’t hurting the performance, no one cared that the cooling technology was 50 years old.”
Azizian began talking with Bucci about applying their knowledge around optimizing heat transfer in nuclear reactors to data centers. Scientists have spent decades finding better ways to move heat in nuclear reactors.
“Heat transfer determines how much energy you can extract from the reactor core, which translates directly to revenue,” Azizian explains.
The founders started Ferveret in 2021. A lot has changed since Azizian walked into his first data center. Chip companies have packed more and more components onto their chips as the explosion in artificial intelligence has put a premium on squeezing as much computing capacity as possible out of limited power supplies.
That has driven data center operators to use liquid to cool chips — often through a technique known as immersion cooling that submerges chips in liquid. The most effective form of immersion cooling brings the liquid to a boil.
“Liquid is a better heat transfer medium than air. That’s why when you stick your hand into room temperature water it still feels cold,” Bucci explains. “When liquid is boiling, it becomes even better at removing heat because the phase change requires a lot of energy, which is the energy you remove from the chip. That lets you transfer large quantities of heat with minimal temperature differences between the chips and the liquid.”
Unfortunately, boiling liquid adds complexity to the system because it forces operators to capture and reliquefy the bubbles while controlling for pressure, temperature, and fluid inventory.
Ferveret’s system is adapted from a process in nuclear reactors called subcooled boiling. It uses a liquid with a low boiling point and none of the toxic PFAS “forever chemicals” that other approaches rely on. At the surface of the chip, Ferveret’s liquid produces smaller bubbles than other immersion cooling approaches. Those bubbles detach more frequently and quickly recondense in the surrounding liquid, accelerating the bubble-rewetting cycle at the surface of the chip to hasten heat transfer.
Ferveret delivers its APC system in small boxes, each of which houses one server. The founders say their modular systems make it easier to deploy the system and simplify maintenance.
“The physics enable us to get to form factors that weren’t possible in the past,” Azizian says. “Most immersion cooling solutions are large tanks that people submerge the servers in. We have a smaller, modular rack-mounted solution that makes it adaptable to the current infrastructure, so it’s easier for people to deploy our technology.”
Ferveret also offers control software that adjusts the power going to each server in real-time to further improve efficiency.
“We deliver full-stack systems that include the cooling box, the rack, the cooling distribution units, and sensors that measure the temperature and pressure,” Bucci says. “Our software monitors those sensors and optimizes the operating condition inside each box to ensure that energy consumption is minimized in the system.”
AI with fewer resources
In addition to helping data centers to run more efficiently, Ferveret is also improving sustainability by making it easier to operate data centers in remote regions with more renewable energy.
“The sun shines in places where you don’t have much water, so the advantage of us being water-free is we allow you to build data centers where you have solar energy but nothing to cool the data center down,” Bucci says. “This technology can help deploy data centers in regions where normally you wouldn’t have the resources to do so, including Africa, the Middle East, and of course parts of America. It’s a huge unlock.”
Ferveret is in talks with the large cloud computing companies known as hyperscalers, and is currently part of Nvidia’s Inception program for startups. The company plans to announce expanded partnerships later this year. From there, the founders plan to quickly scale their technology to help the AI industry continue to grow without further straining the planet.
“The computing industry is facing a huge challenge in the form of access to power, and they have a problem with access to water in many regions,” Azizian says. “That will only become more limiting as the industry grows. The main goal for these data center operators would be to get more tokens from the power they have. We’ve shown we can do that.”
Tell Congress: Just Say No to NO FAKES
The Senate Judiciary Committee is set to consider and vote on the Nurture Originals, Foster Art, and Keep Entertainment Safe Act (NO FAKES). Instead of targeting the real privacy harms posed by AI-generated replicas, this law would create another layer of internet censorship on top of the already existing legal and voluntary takedown systems. Congress should reject NO FAKES.
Tell Congress to Say No to NO FAKES
As currently written, NO FAKES proposes to tackle the problems of misleading AI-generated replicas by creating a broad property right in someone's look, voice, and general style. However, there are all kinds of First Amendment-protected expression that would be swept under the NO FAKES regime—think about parody, news, criticism.
NO FAKES also does a laughable job of protecting artists from use of their image in misleading ways. It doesn’t create a privacy right, but rather a property right that can easily be signed away—as major studios and record labels are almost certain to require in their contracts with artists. As a result, NO FAKES actually creates a new avenue for the exploitation of artists by companies instead of protection from misleading replicas.
The bill also makes it trivially easy for protected speech to be censored. It is a supercharged version of the already flawed copyright takedown regime. It would essentially require platforms to institute filters that don't just look for exact matches of copyrighted material, as current filters do, but anything that might be a digital replica. Even though the latest version of this bill adds some forms of redress for bad faith takedowns, those provisions lack the teeth required to deter a malicious actor.
NO FAKES targets speech, tools, and innovation instead of focusing on the real concern posed by these replicas: privacy. This bill was a bad idea when it was introduced, and got even worse when it was amended last year. Tell Congress to just say no to NO FAKES.
The consequences of relying on AI for accurate news
It’s no secret that the last few years have seen a massive explosion in the use of artificial intelligence for general information-gathering. An even more recent trend, though, is how large language models (LLMs) like ChatGPT, Claude, and Gemini are increasingly being used for verifying and consuming news; reports from the Pew Research Center over the last year found that one-in-five U.S. teens regularly use LLMs to get their news, while one-in-four young adults have reported using them for that purpose at least once.
A new open-access study from the MIT Media Lab should give some of those users pause: Researchers found that, over the course of a month, participants who relied on AI systems to verify facts actually got worse at detecting misinformation on their own when their chatbots were taken away.
This phenomenon, which is often referred to as the “AI dependency paradox,” has been observed in a wide range of knowledge domains, like the 2025 study that found that doctors who used AI got worse at detecting cancer on their own. The dynamic mirrors broader tech trends around so-called “deskilling” (or “cognitive offloading”) that have been well-documented for decades, from calculators weakening our math skills to Global Positioning System (GPS) technologies impacting our natural sense of direction.
In the new Media Lab study, which tracked 67 people over four weeks as they evaluated news headline-image pairs, participants were 21 percent more accurate in detecting fake news when assisted by an AI chatbot during a session — confirming previous research out of the MIT Sloan School of Management demonstrating that AI can be an effective tool in reducing people’s beliefs in false information.
However, the study showed that a new wrinkle emerged when the AI was no longer present: By week four, participants’ unassisted performance on new news items declined by 15 percentage points compared to before the study started. (Roughly a quarter of all participants actually reported feeling that they were getting better at detection, even as their performance declined.)
Dunning-Kruger creeps in
“Users get excited about these ‘magical’ LLMs, but forget that they’re just statistical models that predict the next ‘token’ in a sequence [of letters/words],” says MIT media arts and sciences (MAS) PhD student Anku Rani, co-lead author of a new paper about the research, alongside fellow MAS PhD student Valdemar Danry. “Many impressive behaviors emerge from scaling this, but it comes with real limitations, both in what the model can reliably generate and in its broader impact on the people using it.”
Qualitative analysis identified distinct behavioral patterns, with the team labeling one-fifth of all participants as "Dependency Developers” who gradually shifted from active self-reliance to passive acceptance of AI guidance.
In the post-experiment survey, one respondent explicitly acknowledged this transition, noting their passive role in the process. “While [the chatbots] did emphasize that you must check across multiple sources to make sure a story is true, they didn’t teach me much about exploring the context of the images themselves,” the participant said.
The research team said that these AI models are particularly vulnerable to mistakes in the midst of emotionally charged breaking news, as exhibited by the widespread misinformation that accompanied President Trump’s recent assassination attempt and major events during the Iranian war. (The authors also point out that the original human-created news content that’s used to train the AI models is increasingly unreliable and/or biased, further exacerbating the problem.)
The paper, which Danry and Rani presented at the 2026 CHI Conference on Human Factors in Computing Systems, was co-authored by Assistant Professor Paul Pu Liang, Senior Research Scientist Andrew Lippman, and senior author Pattie Maes, the Germeshausen Professor of Media Arts and Sciences.
The solution: Being a coach, not a crutch
The researchers say that the results of their project suggest that the specific way in which an AI interacts with a user determines whether its impact will be “as a coach, versus as a crutch.” The study found a clear distinction between conversational strategies that simply help in the moment and those that actually support active learning and skill development.
For the latter, the Media Lab team uncovered several strategies associated with stronger independent detection later on, even if the strategies initially slowed down performance during the interaction. This included the Socratic method of the AI asking guided questions, as well as so-called “deep probing,” where the system provides gently persuasive statements if the user appears to be veering away from the correct response.
“AIs that ‘tell’ by providing direct answers are more likely to foster reliance, while those that ‘ask’ via Socratic questioning are better at engaging someone to actually learn how to discern the truth on their own,” says Danry. “But it’s very much a trade-off between speed and effort.”
Rani noted a few key limitations to the one-month study, from the small dataset of roughly 50 validated news items to the demographic focus on the United States and the United Kingdom. In the future, she says that the team hopes to do similar experiments with more geographically diverse cohorts, including low-resource communities, and is also eager to explore whether other multi-modal interaction strategies — like interacting with culturally adaptive digital twins instead of text-based chatbots — help people improve their abilities to detect misinformation.
At a higher level, the researchers hope that the project will be something that educators can examine as they develop teaching plans that incorporate AI tools into their school curricula.
“It’s especially important to raise awareness in our schools and academic communities about the shortcomings of using AI as learning tools,” says Maes. “People need to know that if they ‘delegate’ their thinking, they’re not going to get better at that particular brand of problem-solving. Ultimately, the ability to question and analyze information is important for everyone, because it empowers us to solve problems and form our own independent opinions about the world.”
Danry adds that the rapidly-evolving field of machine learning and deep learning will require continuous education on the benefits and drawbacks of LLMs.
“There’s a lot of work to do in making sure that we don’t just fully offload critical tasks that we want to be able to keep on doing to these models,” he says. “We need to develop a new kind of AI literacy.”
The research project was supported, in part, by the Media Lab Consortium, an MIT Tata Center Technology and Design Fellowship, and a Google PhD Fellowship in Human–Computer Interaction.
GPS As a Key Distribution Platform
This is interesting:
The U.S. military has likely been quietly broadcasting codes for its global encryption network using public GPS for nearly 20 years, turning each satellite into a hidden “numbers station,” according to Steven Murdoch…
That means every device that uses GPS has been receiving hidden government information for years, and nobody outside the military knew it until now.
[…]
Murdoch discovered that this particular sentinel was transmitted by all 31 operational satellites within a window of a few hours on May 26, 2011, potentially heralding the activation of a new operational system. He confirmed that this timeline coincided with the rollout of the military’s Over-the-Air Distribution (OTAD) and the Over-the-Air Rekeying (OTAR) by cross-referencing declassified documents, including a 2015 presentation about the dates of the operation...
Chris Zegras appointed director and CEO of the Singapore-MIT Alliance for Research and Technology
Chris Zegras, professor of mobility and urban planning and the current head of the MIT Department of Urban Studies and Planning (DUSP), has been appointed chief executive officer and director of the Singapore-MIT Alliance for Research and Technology (SMART), effective Sept. 1. Zegras succeeds Bruce Tidor, professor of biological engineering and computer science, who has served as interim CEO and director since January 2025.
Established in collaboration with the National Research Foundation of Singapore in 2007, SMART is MIT’s only research center outside the United States. Housed within the Campus for Research Excellence and Technological Enterprise, SMART serves as a key platform for collaboration between MIT and Singapore’s research ecosystem, bringing together leading experts and institutions from the United States, Singapore, and the region for world-class research and innovation.
“Professor Zegras brings a distinguished track record of interdisciplinary leadership and a deep understanding of SMART’s mission and impact,” says Anantha Chandrakasan, MIT’s provost, who announced Zegras’ appointment in a letter to the MIT community today. “His appointment reinforces MIT’s commitment to the alliance, which has advanced innovation and driven global impact, and which remains as important as ever in a time of accelerating technological and global change.”
Zegras joined the MIT faculty in 2005 and has served as the head of DUSP since 2020. His own research spans interrelated areas critical to tackling metropolitan mobility challenges: leveraging computational technologies for understanding and modeling human behaviors and enhancing strategic planning capabilities.
Zegras brings extensive experience in interdisciplinary research and leadership and a long-standing connection to SMART, where he led collaborative research on next-generation mobility sensing and simulation systems. From 2010 to 2020, he was a principal investigator on the Future Urban Mobility interdisciplinary research group; from 2016 to 2020, he was the group’s lead principal investigator. During this time, the group spearheaded Singapore’s first-ever public autonomous vehicle trials, developed and deployed large-scale urban simulation and visualization systems, and conducted research that evolved into spinoff companies, among other activities.
“Bringing together leading experts from the U.S., Singapore, and around the world, SMART has established itself as a unique hub for interdisciplinary collaboration and innovation that addresses pressing societal issues,” says Zegras. “Having experienced firsthand what this distinctive model can achieve, I look forward to building on this strong foundation to deepen collaboration, strengthen our innovation ecosystem, and accelerate the translation of research into meaningful real-world impact.”
SMART is built around interdisciplinary research groups, all headed by senior MIT faculty members. At present, there are six groups, focused on antimicrobial resistance; the use of living cells as personalized medicines to treat and prevent diseases; social and institutional challenges arising from the proliferation of AI and emerging technologies; new agricultural technologies; wafer-scale 3D sensing technologies; and wearable ultrasound imaging. SMART is also home to the SMART Innovation Center, which aims to get research ideas from lab to market.