The accumulation of microplastics in the environment, and within our bodies, is an increasingly worrisome issue. But predicting where these ubiquitous particles will accumulate, and therefore where remediation efforts should be focused, has been difficult because of the many factors that contribute to their dispersal and deposition.

New research from MIT shows that one key factor in determining where microparticles are likely to build up has to do with the presence of biofilms. These thin, sticky biopolymer layers are shed by microorganisms and can accumulate on surfaces, including along sandy riverbeds or seashores. The study found that, all other conditions being equal, microparticles are less likely to accumulate in sediment infused with biofilms, because if they land there, they are more likely to be resuspended by flowing water and carried away.

The open-access findings appear in the journal Geophysical Research Letters, in a paper by MIT postdoc Hyoungchul Park and professor of civil and environmental engineering Heidi Nepf. “Microplastics are definitely in the news a lot,” Nepf says, “and we don’t fully understand where the hotspots of accumulation are likely to be. This work gives a little bit of guidance” on some of the factors that can cause these particles, and small particles in general, to accumulate in certain locations.

Most experiments looking at the ways microparticles are transported and deposited have been conducted over bare sand, Park says. “But in nature, there are a lot of microorganisms, such as bacteria, fungi, and algae, and when they adhere to the stream bed they generate some sticky things.” These substances are known as extracellular polymeric substances, or EPS, and they “can significantly affect the channel bed characteristics,” he says. The new research focused on determining exactly how these substances affected the transport of microparticles, including microplastics.

The research involved a flow tank with a bottom lined with fine sand, and sometimes with vertical plastic tubes simulating the presence of mangrove roots. In some experiments the bed consisted of pure sand, and in others the sand was mixed with a biological material to simulate the natural biofilms found in many riverbed and seashore environments.

Water mixed with tiny plastic particles was pumped through the tank for three hours, and then the bed surface was photographed under ultraviolet light that caused the plastic particles to fluoresce, allowing a quantitative measurement of their concentration.

The results revealed two different phenomena that affected how much of the plastic accumulated on the different surfaces. Immediately around the rods that stood in for above-ground roots, turbulence prevented particle deposition. In addition, as the amount of simulated biofilms in the sediment bed increased, the accumulation of particles also decreased.

Nepf and Park concluded that the biofilms filled up the spaces between the sand grains, leaving less room for the microparticles to fit in. The particles were more exposed because they penetrated less deeply in between the sand grains, and as a result they were much more easily resuspended and carried away by the flowing water.

“These biological films fill the pore spaces between the sediment grains,” Park explains, “and that makes the deposited particles — the particles that land on the bed — more exposed to the forces generated by the flow, which makes it easier for them to be resuspended. What we found was that in a channel with the same flow conditions and the same vegetation and the same sand bed, if one is without EPS and one is with EPS, then the one without EPS has a much higher deposition rate than the one with EPS.”

Nepf adds: “The biofilm is blocking the plastics from accumulating in the bed because they can’t go deep into the bed. They just stay right on the surface, and then they get picked up and moved elsewhere. So, if I spilled a large amount of microplastic in two rivers, and one had a sandy or gravel bottom, and one was muddier with more biofilm, I would expect more of the microplastics to be retained in the sandy or gravelly river.”

All of this is complicated by other factors, such as the turbulence of the water or the roughness of the bottom surface, she says. But it provides a “nice lens” to provide some suggestions for people who are trying to study the impacts of microplastics in the field. “They’re trying to determine what kinds of habitats these plastics are in, and this gives a framework for how you might categorize those habitats,” she says. “It gives guidance to where you should go to find more plastics versus less.”

As an example, Park suggests, in mangrove ecosystems, microplastics may preferentially accumulate in the outer edges, which tend to be sandy, while the interior zones have sediment with more biofilm. Thus, this work suggests “the sandy outer regions may be potential hotspots for microplastic accumulation,” he says, and can make this a priority zone for monitoring and protection.

“This is a highly relevant finding,” says Isabella Schalko, a research scientist at ETH Zurich, who was not associated with this research. “It suggests that restoration measures such as re-vegetation or promoting biofilm growth could help mitigate microplastic accumulation in aquatic systems. It highlights the powerful role of biological and physical features in shaping particle transport processes.”

The work was supported by Shell International Exploration and Production through the MIT Energy Initiative.

Stanley Fischer PhD ’69, MIT professor emeritus of economics and a towering figure in both academic macroeconomics and global economic policymaking, passed away on May 31. He was 81. Fischer was a foundational scholar as well as a wise mentor and a central force in shaping the macroeconomic tradition of MIT’s Department of Economics that continues today.

“Together with Rudi Dornbusch and later Olivier Blanchard, Stan was one of the intellectual engines that powered MIT macroeconomics in the 1970s and beyond,” says Ricardo Caballero PhD ’88, one of Fischer’s advisees and now the Ford International Professor of Economics at MIT. “He was quietly brilliant, never flashy, and always razor-sharp. His students learned not just from his lectures or his groundbreaking work on New Keynesian models and rational expectations, but from the clarity of his mind and the gentleness of his wit. Nearly 40 years later, I can still hear him saying: ‘Isn’t it easier to do it right the first time than to explain why you didn’t?’ That line has stayed with me ever since. A simple comment from Stan during a seminar — often offered with a disarming smile — could puncture a weak argument or crystallize a central insight. He taught generations of macroeconomists to prize discipline, clarity, and policy relevance.”

Olivier Blanchard PhD ’77, the Robert M. Solow Professor of Economics Emeritus at MIT and another advisee, explains that Fischer “was one of the most popular teachers, and one of the most popular thesis advisers. We flocked to his office, and I suspect that the only time for research he had was during the night. What we admired most were his technical skills — he knew how to use stochastic calculus — and his ability to take on big questions and simplify them to the point where the answer, ex post, looked obvious. When Rudi Dornbusch joined him in 1975, macro and international quickly became the most exciting fields at MIT.” Within a decade of his joining the MIT faculty, “Stan had acquired near-guru status.”

Fischer built bridges between economic theory and the practice of economic policy. He served as chief economist of the World Bank (1988-90), first deputy managing director at the International Monetary Fund (IMF, 1994-2001), governor of the Bank of Israel (2005-13), and vice chair of the U.S. Federal Reserve (2014-17). These leadership roles gave him a rare platform to implement ideas he helped develop in the classroom and he was widely praised for his successes at averting financial crises across several decades and continents. Yet even as he moved through the highest circles of global policymaking, he remained a teacher at heart — accessible, thoughtful, and generous with his time.

At MIT, Fischer is best remembered for inspiring generations of graduate students who moved between academics and policy just as he did. Over the course of two decades before he began his active policy role, he was primary adviser for 49 PhD students, secondary adviser to another 23, and a celebrated teacher for many more. 

Many of his students became important macroeconomic policymakers, including Ben Bernanke PhD ’79; Mario Draghi PhD ’77; Ilan Goldfajn PhD ’95; Philip Lowe PhD ’91; and Kazuo Ueda PhD ’80, who chaired the Federal Reserve Board, the European Central Bank, the Banco Central do Brazil, the Reserve Bank of Australia, and the Bank of Japan. Students Gregory Mankiw PhD ’84 and Christina Romer PhD ’85 chaired the Council of Economic Advisors; Maurice Obstfeld PhD ’79 and Kenneth Rogoff PhD ’80 were chief economist at the International Monetary Fund; and Frederic Mishkin PhD ’76 was a governor of the Federal Reserve. Another of his students, former Treasury Secretary Lawrence Summers ’75, explains that “no one had more cumulative influence on the macroeconomic policymakers of the last generation than Stanley Fischer … We all were shaped by his clarity of thought, intellectual balance, personal decency, and quality of character. In a broader sense, everyone who was involved in the macro policy enterprise was Stan Fischer’s disciple. People all over the world who never knew his name lived better, more secure, lives because of all that he did through his teaching, writing, and service.”

Fischer grew up in Northern Rhodesia (now Zambia), living behind the general store his family ran before moving to Southern Rhodesia (now Zimbabwe) at the age of 13. Inspired by the quality of writing in John Maynard Keynes’ “The General Theory of Employment, Interest, and Money,” he applied for and won a scholarship to study at the London School of Economics. He moved to MIT for his graduate studies, where his dissertation was supervised by Franklin M. Fisher. After several years on the University of Chicago faculty, he returned to MIT in 1973, where he stayed for the remainder of his academic career. He held the Elizabeth and James Killian Class of 1926 professorship from 1992 to 1995, serving as department chair in 1993–94, before being called away to the IMF.

Fischer’s intellectual journey from MIT to Chicago and back culminated in his most influential academic work. Ivan Werning, the Robert M. Solow Professor of Economics at MIT notes, “his research was pathbreaking and paved the way to the modern approach to macroeconomics. By merging nominal rigidities associated with MIT’s Keynesian tradition with rational expectations emanating from the Chicago school, his 1977 paper on ‘Long-Term Contracts, Rational Expectations, and the Optimal Money Supply Rule’ showed how the non-neutrality of money did not require agent irrationality or confusion.” The dynamic stochastic general equilibrium models now used at every central bank to evaluate monetary policy options are direct descendants of Fischer’s thinking.

Fischer’s influence goes beyond what has become known as New Keynesian Economics. Werning continues, “Fischer’s research combined theoretical insights to very applied questions. His textbook with Blanchard was instrumental to an entire generation of macroeconomists, showing macroeconomics as a rich and evolving field, ripe with tools and great questions to study. Along with Bob Solow, Rudi Dornbusch, and others, Fischer had a huge impact within the MIT economics department and helped build its day-to-day culture, with an inquisitive, open-minded, and friendly atmosphere.”

Macroeconomics — and MIT — owe him a profound debt.

Fischer is survived by his three sons, Michael, David, and Jonathan, and nine grandchildren.

Hydrogen has the potential to be a climate-friendly fuel since it doesn’t release carbon dioxide when used as an energy source. Currently, however, most methods for producing hydrogen involve fossil fuels, making hydrogen less of a “green” fuel over its entire life cycle.

A new process developed by MIT engineers could significantly shrink the carbon footprint associated with making hydrogen.

Last year, the team reported that they could produce hydrogen gas by combining seawater, recycled soda cans, and caffeine. The question then was whether the benchtop process could be applied at an industrial scale, and at what environmental cost.

Now, the researchers have carried out a “cradle-to-grave” life cycle assessment, taking into account every step in the process at an industrial scale. For instance, the team calculated the carbon emissions associated with acquiring and processing aluminum, reacting it with seawater to produce hydrogen, and transporting the fuel to gas stations, where drivers could tap into hydrogen tanks to power engines or fuel cell cars. They found that, from end to end, the new process could generate a fraction of the carbon emissions that is associated with conventional hydrogen production.

In a study appearing today in Cell Reports Sustainability, the team reports that for every kilogram of hydrogen produced, the process would generate 1.45 kilograms of carbon dioxide over its entire life cycle. In comparison, fossil-fuel-based processes emit 11 kilograms of carbon dioxide per kilogram of hydrogen generated.

The low-carbon footprint is on par with other proposed “green hydrogen” technologies, such as those powered by solar and wind energy.

“We’re in the ballpark of green hydrogen,” says lead author Aly Kombargi PhD ’25, who graduated this spring from MIT with a doctorate in mechanical engineering. “This work highlights aluminum’s potential as a clean energy source and offers a scalable pathway for low-emission hydrogen deployment in transportation and remote energy systems.”

The study’s MIT co-authors are Brooke Bao, Enoch Ellis, and professor of mechanical engineering Douglas Hart.

Gas bubble

Dropping an aluminum can in water won’t normally cause much of a chemical reaction. That’s because when aluminum is exposed to oxygen, it instantly forms a shield-like layer. Without this layer, aluminum exists in its pure form and can readily react when mixed with water. The reaction that occurs involves aluminum atoms that efficiently break up molecules of water, producing aluminum oxide and pure hydrogen. And it doesn’t take much of the metal to bubble up a significant amount of the gas.

“One of the main benefits of using aluminum is the energy density per unit volume,” Kombargi says. “With a very small amount of aluminum fuel, you can conceivably supply much of the power for a hydrogen-fueled vehicle.”

Last year, he and Hart developed a recipe for aluminum-based hydrogen production. They found they could puncture aluminum’s natural shield by treating it with a small amount of gallium-indium, which is a rare-metal alloy that effectively scrubs aluminum into its pure form. The researchers then mixed pellets of pure aluminum with seawater and observed that the reaction produced pure hydrogen. What’s more, the salt in the water helped to precipitate gallium-indium, which the team could subsequently recover and reuse to generate more hydrogen, in a cost-saving, sustainable cycle.

“We were explaining the science of this process in conferences, and the questions we would get were, ‘How much does this cost?’ and, ‘What’s its carbon footprint?’” Kombargi says. “So we wanted to look at the process in a comprehensive way.”

A sustainable cycle

For their new study, Kombargi and his colleagues carried out a life cycle assessment to estimate the environmental impact of aluminum-based hydrogen production, at every step of the process, from sourcing the aluminum to transporting the hydrogen after production. They set out to calculate the amount of carbon associated with generating 1 kilogram of hydrogen — an amount that they chose as a practical, consumer-level illustration.

“With a hydrogen fuel cell car using 1 kilogram of hydrogen, you can go between 60 to 100 kilometers, depending on the efficiency of the fuel cell,” Kombargi notes.

They performed the analysis using Earthster — an online life cycle assessment tool that draws data from a large repository of products and processes and their associated carbon emissions. The team considered a number of scenarios to produce hydrogen using aluminum, from starting with “primary” aluminum mined from the Earth, versus “secondary” aluminum that is recycled from soda cans and other products, and using various methods to transport the aluminum and hydrogen.

After running life cycle assessments for about a dozen scenarios, the team identified one scenario with the lowest carbon footprint. This scenario centers on recycled aluminum — a source that saves a significant amount of emissions compared with mining aluminum — and seawater — a natural resource that also saves money by recovering gallium-indium. They found that this scenario, from start to finish, would generate about 1.45 kilograms of carbon dioxide for every kilogram of hydrogen produced. The cost of the fuel produced, they calculated, would be about $9 per kilogram, which is comparable to the price of hydrogen that would be generated with other green technologies such as wind and solar energy.

The researchers envision that if the low-carbon process were ramped up to a commercial scale, it would look something like this: The production chain would start with scrap aluminum sourced from a recycling center. The aluminum would be shredded into pellets and treated with gallium-indium. Then, drivers could transport the pretreated pellets as aluminum “fuel,” rather than directly transporting hydrogen, which is potentially volatile. The pellets would be transported to a fuel station that ideally would be situated near a source of seawater, which could then be mixed with the aluminum, on demand, to produce hydrogen. A consumer could then directly pump the gas into a car with either an internal combustion engine or a fuel cell.

The entire process does produce an aluminum-based byproduct, boehmite, which is a mineral that is commonly used in fabricating semiconductors, electronic elements, and a number of industrial products. Kombargi says that if this byproduct were recovered after hydrogen production, it could be sold to manufacturers, further bringing down the cost of the process as a whole.

“There are a lot of things to consider,” Kombargi says. “But the process works, which is the most exciting part. And we show that it can be environmentally sustainable.”

The group is continuing to develop the process. They recently designed a small reactor, about the size of a water bottle, that takes in aluminum pellets and seawater to generate hydrogen, enough to power an electric bike for several hours. They previously demonstrated that the process can produce enough hydrogen to fuel a small car. The team is also exploring underwater applications, and are designing a hydrogen reactor that would take in surrounding seawater to power a small boat or underwater vehicle.

This research was supported, in part, by the MIT Portugal Program.

Hearing aids, mouth guards, dental implants, and other highly tailored structures are often products of 3D printing. These structures are typically made via vat photopolymerization — a form of 3D printing that uses patterns of light to shape and solidify a resin, one layer at a time.

The process also involves printing structural supports from the same material to hold the product in place as it’s printed. Once a product is fully formed, the supports are removed manually and typically thrown out as unusable waste.

MIT engineers have found a way to bypass this last finishing step, in a way that could significantly speed up the 3D-printing process. They developed a resin that turns into two different kinds of solids, depending on the type of light that shines on it: Ultraviolet light cures the resin into an highly resilient solid, while visible light turns the same resin into a solid that is easily dissolvable in certain solvents.

The team exposed the new resin simultaneously to patterns of UV light to form a sturdy structure, as well as patterns of visible light to form the structure’s supports. Instead of having to carefully break away the supports, they simply dipped the printed material into solution that dissolved the supports away, revealing the sturdy, UV-printed part.

The supports can dissolve in a variety of food-safe solutions, including baby oil. Interestingly, the supports could even dissolve in the main liquid ingredient of the original resin, like a cube of ice in water. This means that the material used to print structural supports could be continuously recycled: Once a printed structure’s supporting material dissolves, that mixture can be blended directly back into fresh resin and used to print the next set of parts — along with their dissolvable supports.

The researchers applied the new method to print complex structures, including functional gear trains and intricate lattices.

“You can now print — in a single print — multipart, functional assemblies with moving or interlocking parts, and you can basically wash away the supports,” says graduate student Nicholas Diaco. “Instead of throwing out this material, you can recycle it on site and generate a lot less waste. That’s the ultimate hope.”

He and his colleagues report the details of the new method in a paper appearing today in Advanced Materials Technologies. The MIT study’s co-authors include Carl Thrasher, Max Hughes, Kevin Zhou, Michael Durso, Saechow Yap, Professor Robert Macfarlane, and Professor A. John Hart, head of MIT’s Department of Mechanical Engineering.

Waste removal

Conventional vat photopolymerization (VP) begins with a 3D computer model of a structure to be printed — for instance, of two interlocking gears. Along with the gears themselves, the model includes small support structures around, under, and between the gears to keep every feature in place as the part is printed. This computer model is then sliced into many digital layers that are sent to a VP printer for printing.

A standard VP printer includes a small vat of liquid resin that sits over a light source. Each slice of the model is translated into a matching pattern of light that is projected onto the liquid resin, which solidifies into the same pattern. Layer by layer, a solid, light-printed version of the model’s gears and supports forms on the build platform. When printing is finished, the platform lifts the completed part above the resin bath. Once excess resin is washed away, a person can go in by hand to remove the intermediary supports, usually by clipping and filing, and the support material is ultimately thrown away.

“For the most part, these supports end up generating a lot of waste,” Diaco says.

Print and dip

Diaco and the team looked for a way to simplify and speed up the removal of printed supports and, ideally, recycle them in the process. They came up with a general concept for a resin that, depending on the type of light that it is exposed to, can take on one of two phases: a resilient phase that would form the desired 3D structure and a secondary phase that would function as a supporting material but also be easily dissolved away.

After working out some chemistry, the team found they could make such a two-phase resin by mixing two commercially available monomers, the chemical building blocks that are found in many types of plastic. When ultraviolet light shines on the mixture, the monomers link together into a tightly interconnected network, forming a tough solid that resists dissolution. When the same mixture is exposed to visible light, the same monomers still cure, but at the molecular scale the resulting monomer strands remain separate from one another. This solid can quickly dissolve when placed in certain solutions.

In benchtop tests with small vials of the new resin, the researchers found the material did transform into both the insoluble and soluble forms in response to ultraviolet and visible light, respectively. But when they moved to a 3D printer with LEDs dimmer than the benchtop setup, the UV-cured material fell apart in solution. The weaker light only partially linked the monomer strands, leaving them too loosely tangled to hold the structure together.

Diaco and his colleagues found that adding a small amount of a third “bridging” monomer could link the two original monomers together under UV light, knitting them into a much sturdier framework. This fix enabled the researchers to simultaneously print resilient 3D structures and dissolvable supports using timed pulses of UV and visible light in one run.

The team applied the new method to print a variety of intricate structures, including interlocking gears, intricate lattices, a ball within a square frame, and, for fun, a small dinosaur encased in an egg-shaped support that dissolved away when dipped in solution.

“With all these structures, you need a lattice of supports inside and out while printing,” Diaco says. “Removing those supports normally requires careful, manual removal. This shows we can print multipart assemblies with a lot of moving parts, and detailed, personalized products like hearing aids and dental implants, in a way that’s fast and sustainable.”

“We’ll continue studying the limits of this process, and we want to develop additional resins with this wavelength-selective behavior and mechanical properties necessary for durable products,” says professor of mechanical engineering John Hart. “Along with automated part handling and closed-loop reuse of the dissolved resin, this is an exciting path to resource-efficient and cost-effective polymer 3D printing at scale.”

This research was supported, in part, by the Center for Perceptual and Interactive Intelligence (InnoHK) in Hong Kong, the U.S. National Science Foundation, the U.S. Office of Naval Research, and the U.S. Army Research Office.

Artificial intelligence systems like ChatGPT provide plausible-sounding answers to any question you might ask. But they don’t always reveal the gaps in their knowledge or areas where they’re uncertain. That problem can have huge consequences as AI systems are increasingly used to do things like develop drugs, synthesize information, and drive autonomous cars.

Now, the MIT spinout Themis AI is helping quantify model uncertainty and correct outputs before they cause bigger problems. The company’s Capsa platform can work with any machine-learning model to detect and correct unreliable outputs in seconds. It works by modifying AI models to enable them to detect patterns in their data processing that indicate ambiguity, incompleteness, or bias.

“The idea is to take a model, wrap it in Capsa, identify the uncertainties and failure modes of the model, and then enhance the model,” says Themis AI co-founder and MIT Professor Daniela Rus, who is also the director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). “We’re excited about offering a solution that can improve models and offer guarantees that the model is working correctly.”

Rus founded Themis AI in 2021 with Alexander Amini ’17, SM ’18, PhD ’22 and Elaheh Ahmadi ’20, MEng ’21, two former research affiliates in her lab. Since then, they’ve helped telecom companies with network planning and automation, helped oil and gas companies use AI to understand seismic imagery, and published papers on developing more reliable and trustworthy chatbots.

“We want to enable AI in the highest-stakes applications of every industry,” Amini says. “We’ve all seen examples of AI hallucinating or making mistakes. As AI is deployed more broadly, those mistakes could lead to devastating consequences. Our software can make these systems more transparent.”

Helping models know what they don’t know

Rus’ lab has been researching model uncertainty for years. In 2018, she received funding from Toyota to study the reliability of a machine learning-based autonomous driving solution.

“That is a safety-critical context where understanding model reliability is very important,” Rus says.

In separate work, Rus, Amini, and their collaborators built an algorithm that could detect racial and gender bias in facial recognition systems and automatically reweight the model’s training data, showing it eliminated bias. The algorithm worked by identifying the unrepresentative parts of the underlying training data and generating new, similar data samples to rebalance it.

In 2021, the eventual co-founders showed a similar approach could be used to help pharmaceutical companies use AI models to predict the properties of drug candidates. They founded Themis AI later that year.

“Guiding drug discovery could potentially save a lot of money,” Rus says. “That was the use case that made us realize how powerful this tool could be.”

Today Themis is working with companies in a wide variety of industries, and many of those companies are building large language models. By using Capsa, the models are able to quantify their own uncertainty for each output.

“Many companies are interested in using LLMs that are based on their data, but they’re concerned about reliability,” observes Stewart Jamieson SM ’20, PhD ’24, Themis AI's head of technology. “We help LLMs self-report their confidence and uncertainty, which enables more reliable question answering and flagging unreliable outputs.”

Themis AI is also in discussions with semiconductor companies building AI solutions on their chips that can work outside of cloud environments.

“Normally these smaller models that work on phones or embedded systems aren’t very accurate compared to what you could run on a server, but we can get the best of both worlds: low latency, efficient edge computing without sacrificing quality,” Jamieson explains. “We see a future where edge devices do most of the work, but whenever they’re unsure of their output, they can forward those tasks to a central server.”

Pharmaceutical companies can also use Capsa to improve AI models being used to identify drug candidates and predict their performance in clinical trials.

“The predictions and outputs of these models are very complex and hard to interpret — experts spend a lot of time and effort trying to make sense of them,” Amini remarks. “Capsa can give insights right out of the gate to understand if the predictions are backed by evidence in the training set or are just speculation without a lot of grounding. That can accelerate the identification of the strongest predictions, and we think that has a huge potential for societal good.”

Research for impact

Themis AI’s team believes the company is well-positioned to improve the cutting edge of constantly evolving AI technology. For instance, the company is exploring Capsa’s ability to improve accuracy in an AI technique known as chain-of-thought reasoning, in which LLMs explain the steps they take to get to an answer.

“We’ve seen signs Capsa could help guide those reasoning processes to identify the highest-confidence chains of reasoning,” Amini says. “We think that has huge implications in terms of improving the LLM experience, reducing latencies, and reducing computation requirements. It’s an extremely high-impact opportunity for us.”

For Rus, who has co-founded several companies since coming to MIT, Themis AI is an opportunity to ensure her MIT research has impact.

“My students and I have become increasingly passionate about going the extra step to make our work relevant for the world," Rus says. “AI has tremendous potential to transform industries, but AI also raises concerns. What excites me is the opportunity to help develop technical solutions that address these challenges and also build trust and understanding between people and the technologies that are becoming part of their daily lives.”

The intersection of art, science, and technology presents a unique, sometimes challenging, viewpoint for both scientists and artists. It is in this nexus that art historian Lindsay Caplan positions herself: “My work as an art historian focuses on the ways that artists across the 20th century engage with new technologies like computers, video, and television, not merely as new materials for making art as they already understand it, but as conceptual platforms for reorienting and reimagining the foundational assumptions of their practice.”

With this introduction, Caplan, an assistant professor at Brown University, opened the inaugural Resonances Lecture — a new series by STUDIO.nano to explore the generative edge where art, science, and technology meet. Delivered on April 28 to an interdisciplinary crowd at MIT.nano, Caplan’s lecture, titled “Analogical Engines — Collaborations across Art and Technology in the 1960s,” traced how artists across Europe and the Americas in the 1960s engaged with and responded to the emerging technological advances of computer science, cybernetics, and early AI. “By the time we reached the 1960s,” she said, “analogies between humans and machines, drawn from computer science and fields like information theory and cybernetics, abound among art historians and artists alike.”

Kaplan’s talk centered on two artistic networks, with a particular emphasis on American artist Liliane Lijn: New Tendencies exhibitions (1961-79) and the Signals gallery in London (1964-66). She deftly analyzed the artist’s material experimentation with contemporary advances in emergent technologies — quantum physics and mathematical formalism, particularly Heisenberg's uncertainty principle. She argued that both art historical formalism and mathematical formalism share struggles with representation, indeterminacy, and the tension between constructed and essential truths.

Following her talk, Caplan was joined by MIT faculty Mark Jarzombek, professor of the history and theory of architecture, and Gediminas Urbonas, associate professor of art, culture, and technology (ACT), for a panel discussion moderated by Ardalan SadeghiKivi SM ’22, lecturer of comparative media studies. The conversation expanded on Caplan’s themes with discussions of artists’ attraction to newly developed materials and technology, and the critical dimension of reimagining and repurposing technologies that were originally designed with an entirely different purpose.

Urbonas echoed the urgency of these conversations. “It is exceptionally exciting to witness artists working in dialectical tension with scientists — a tradition that traces back to the founding of the Center for Advanced Visual Studies at MIT and continues at ACT today,” reflected Urbonas. “The dual ontology of science and art enables us to grasp the world as a web of becoming, where new materials, social imaginaries, and aesthetic values are co-constituted through interdisciplinary inquiry. Such collaborations are urgent today, offering tools to reimagine agency, subjectivity, and the role of culture in shaping the future.”

The event concluded with a reception in MIT.nano’s East Lobby, where attendees could view MIT ACT student projects currently on exhibition in MIT.nano’s gallery spaces. The reception was, itself, an intersection of art and technology. “The first lecture of the Resonances Lecture Series lived up to the title,” reflects Jarzombek. “A brilliant talk by Lindsay Caplan proved that the historical and aesthetical dimensions in the sciences have just as much relevance to a critical posture as the technical.”

The Resonances lecture and panel series seeks to gather artists, designers, scientists, engineers, and historians who examine how scientific endeavors shape artistic production, and vice versa. Their insights expose the historical context on how art and science are made and distributed in society and offer hints at the possible futures of such productions.

“When we were considering who to invite to launch this lecture series, Lindsay Caplan immediately came to mind,” says Tobias Putrih, ACT lecturer and academic advisor for STUDIO.nano. “She is one of the most exciting thinkers and historians writing about the intersection between art, technology, and science today. We hope her insights and ideas will encourage further collaborative projects.”

The Resonances series is one of several new activities organized by STUDIO,nano, a program within MIT.nano, to connect the arts with cutting-edge research environments. “MIT.nano generates extraordinary scientific work,” says Samantha Farrell, manager of STUDIO.nano, “but it’s just as vital to create space for cultural reflection. STUDIO.nano invites artists to engage directly with new technologies — and with the questions they raise.”

In addition to the Resonances lectures, STUDIO.nano organizes exhibitions in the public spaces at MIT.nano, and an Encounters series, launched last fall, to bring artists to MIT.nano. To learn about current installations and ongoing collaborations, visit the STUDIO.nano web page.

For weeks, the whiteboard in the lab was crowded with scribbles, diagrams, and chemical formulas. A research team across the Olivetti Group and the MIT Concrete Sustainability Hub (CSHub) was working intensely on a key problem: How can we reduce the amount of cement in concrete to save on costs and emissions? 

The question was certainly not new; materials like fly ash, a byproduct of coal production, and slag, a byproduct of steelmaking, have long been used to replace some of the cement in concrete mixes. However, the demand for these products is outpacing supply as industry looks to reduce its climate impacts by expanding their use, making the search for alternatives urgent. The challenge that the team discovered wasn’t a lack of candidates; the problem was that there were too many to sort through.

On May 17, the team, led by postdoc Soroush Mahjoubi, published an open-access paper in Nature’s Communications Materials outlining their solution. “We realized that AI was the key to moving forward,” notes Mahjoubi. “There is so much data out there on potential materials — hundreds of thousands of pages of scientific literature. Sorting through them would have taken many lifetimes of work, by which time more materials would have been discovered!”

With large language models, like the chatbots many of us use daily, the team built a machine-learning framework that evaluates and sorts candidate materials based on their physical and chemical properties. 

“First, there is hydraulic reactivity. The reason that concrete is strong is that cement — the ‘glue’ that holds it together — hardens when exposed to water. So, if we replace this glue, we need to make sure the substitute reacts similarly,” explains Mahjoubi. “Second, there is pozzolanicity. This is when a material reacts with calcium hydroxide, a byproduct created when cement meets water, to make the concrete harder and stronger over time.  We need to balance the hydraulic and pozzolanic materials in the mix so the concrete performs at its best.”

Analyzing scientific literature and over 1 million rock samples, the team used the framework to sort candidate materials into 19 types, ranging from biomass to mining byproducts to demolished construction materials. Mahjoubi and his team found that suitable materials were available globally — and, more impressively, many could be incorporated into concrete mixes just by grinding them. This means it’s possible to extract emissions and cost savings without much additional processing. 

“Some of the most interesting materials that could replace a portion of cement are ceramics,” notes Mahjoubi. “Old tiles, bricks, pottery — all these materials may have high reactivity. That’s something we’ve observed in ancient Roman concrete, where ceramics were added to help waterproof structures. I’ve had many interesting conversations on this with Professor Admir Masic, who leads a lot of the ancient concrete studies here at MIT.”

The potential of everyday materials like ceramics and industrial materials like mine tailings is an example of how materials like concrete can help enable a circular economy. By identifying and repurposing materials that would otherwise end up in landfills, researchers and industry can help to give these materials a second life as part of our buildings and infrastructure.

Looking ahead, the research team is planning to upgrade the framework to be capable of assessing even more materials, while experimentally validating some of the best candidates. “AI tools have gotten this research far in a short time, and we are excited to see how the latest developments in large language models enable the next steps,” says Professor Elsa Olivetti, senior author on the work and member of the MIT Department of Materials Science and Engineering. She serves as an MIT Climate Project mission director, a CSHub principal investigator, and the leader of the Olivetti Group.

“Concrete is the backbone of the built environment,” says Randolph Kirchain, co-author and CSHub director. “By applying data science and AI tools to material design, we hope to support industry efforts to build more sustainably, without compromising on strength, safety, or durability.

In addition to Mahjoubi, Olivetti, and Kirchain, co-authors on the work include MIT postdoc Vineeth Venugopal, Ipek Bensu Manav SM ’21, PhD ’24; and CSHub Deputy Director Hessam AzariJafari.

This spring, 25 MIT students and a postdoc traveled to Washington, where they met with congressional offices to advocate for federal science funding and specific, science-based policies based on insights from their research on pressing issues — including artificial intelligence, health, climate and ocean science, energy, and industrial decarbonization. Organized annually by the Science Policy Initiative (SPI), this year’s trip came at a particularly critical moment, as science agencies are facing unprecedented funding cuts.

Over the course of two days, the group met with 66 congressional offices across 35 states and select committees, advocating for stable funding for science agencies such as the Department of Energy, the National Oceanic and Atmospheric Administration, the National Science Foundation, NASA, and the Department of Defense.

Congressional Visit Days (CVD), organized by SPI, offer students and researchers a hands-on introduction to federal policymaking. In addition to meetings on Capitol Hill, participants connected with MIT alumni in government and explored potential career paths in science policy.

This year’s trip was co-organized by Mallory Kastner, a PhD student in biological oceanography at MIT and Woods Hole Oceanographic Institution (WHOI), and Julian Ufert, a PhD student in chemical engineering at MIT. Ahead of the trip, participants attended training sessions hosted by SPI, the MIT Washington Office, and the MIT Policy Lab. These sessions covered effective ways to translate scientific findings into policy, strategies for a successful advocacy meeting, and hands-on demos of a congressional meeting.

Participants then contacted their representatives’ offices in advance and tailored their talking points to each office’s committees and priorities. This structure gave participants direct experience initiating policy conversations with those actively working on issues they cared about.

Audrey Parker, a PhD student in civil and environmental engineering studying methane abatement, emphasizes the value of connecting scientific research with priorities in Congress: “Through CVD, I had the opportunity to contribute to conversations on science-backed solutions and advocate for the role of research in shaping policies that address national priorities — including energy, sustainability, and climate change.”

To many of the participants, stepping into the shoes of a policy advisor was a welcome diversion from their academic duties and scientific routine. For Alex Fan, an undergraduate majoring in electrical engineering and computer science, the trip was enlightening: “It showed me that student voices really do matter in shaping science policy. Meeting with lawmakers, especially my own representative, Congresswoman Bonamici, made the experience personal and inspiring. It has made me seriously consider a future at the intersection of research and policy.”

“I was truly impressed by the curiosity and dedication of our participants, as well as the preparation they brought to each meeting,” says Ufert. “It was inspiring to watch them grow into confident advocates, leveraging their experience as students and their expertise as researchers to advise on policy needs.”

Kastner adds: “It was eye-opening to see the disconnect between scientists and policymakers. A lot of knowledge we generate as scientists rarely makes it onto the desk of congressional staff, and even more rarely onto the congressperson’s. CVD was an incredibly empowering experience for me as a scientist — not only am I more motivated to broaden my scientific outreach to legislators, but I now also have the skills to do so.”

Funding is the bedrock that allows scientists to carry out research and make discoveries. In the United States, federal funding for science has enabled major technological breakthroughs and advancements in manufacturing and other industrial sectors, and led to important environmental protection standards. While participants found the degree of support for science funding variable among offices from across the political spectrum, they were reassured by the fact that many offices on both sides of the aisle still recognized the significance of science. 

When you’re trying to communicate or understand ideas, words don’t always do the trick. Sometimes the more efficient approach is to do a simple sketch of that concept — for example, diagramming a circuit might help make sense of how the system works.

But what if artificial intelligence could help us explore these visualizations? While these systems are typically proficient at creating realistic paintings and cartoonish drawings, many models fail to capture the essence of sketching: its stroke-by-stroke, iterative process, which helps humans brainstorm and edit how they want to represent their ideas.

A new drawing system from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Stanford University can sketch more like we do. Their method, called “SketchAgent,” uses a multimodal language model — AI systems that train on text and images, like Anthropic’s Claude 3.5 Sonnet — to turn natural language prompts into sketches in a few seconds. For example, it can doodle a house either on its own or through collaboration, drawing with a human or incorporating text-based input to sketch each part separately.

The researchers showed that SketchAgent can create abstract drawings of diverse concepts, like a robot, butterfly, DNA helix, flowchart, and even the Sydney Opera House. One day, the tool could be expanded into an interactive art game that helps teachers and researchers diagram complex concepts or give users a quick drawing lesson.

CSAIL postdoc Yael Vinker, who is the lead author of a paper introducing SketchAgent, notes that the system introduces a more natural way for humans to communicate with AI.

“Not everyone is aware of how much they draw in their daily life. We may draw our thoughts or workshop ideas with sketches,” she says. “Our tool aims to emulate that process, making multimodal language models more useful in helping us visually express ideas.”

SketchAgent teaches these models to draw stroke-by-stroke without training on any data — instead, the researchers developed a “sketching language” in which a sketch is translated into a numbered sequence of strokes on a grid. The system was given an example of how things like a house would be drawn, with each stroke labeled according to what it represented — such as the seventh stroke being a rectangle labeled as a “front door” — to help the model generalize to new concepts.

Vinker wrote the paper alongside three CSAIL affiliates — postdoc Tamar Rott Shaham, undergraduate researcher Alex Zhao, and MIT Professor Antonio Torralba — as well as Stanford University Research Fellow Kristine Zheng and Assistant Professor Judith Ellen Fan. They’ll present their work at the 2025 Conference on Computer Vision and Pattern Recognition (CVPR) this month.

Assessing AI’s sketching abilities

While text-to-image models such as DALL-E 3 can create intriguing drawings, they lack a crucial component of sketching: the spontaneous, creative process where each stroke can impact the overall design. On the other hand, SketchAgent’s drawings are modeled as a sequence of strokes, appearing more natural and fluid, like human sketches.

Prior works have mimicked this process, too, but they trained their models on human-drawn datasets, which are often limited in scale and diversity. SketchAgent uses pre-trained language models instead, which are knowledgeable about many concepts, but don’t know how to sketch. When the researchers taught language models this process, SketchAgent began to sketch diverse concepts it hadn’t explicitly trained on.

Still, Vinker and her colleagues wanted to see if SketchAgent was actively working with humans on the sketching process, or if it was working independently of its drawing partner. The team tested their system in collaboration mode, where a human and a language model work toward drawing a particular concept in tandem. Removing SketchAgent’s contributions revealed that their tool’s strokes were essential to the final drawing. In a drawing of a sailboat, for instance, removing the artificial strokes representing a mast made the overall sketch unrecognizable.

In another experiment, CSAIL and Stanford researchers plugged different multimodal language models into SketchAgent to see which could create the most recognizable sketches. Their default backbone model, Claude 3.5 Sonnet, generated the most human-like vector graphics (essentially text-based files that can be converted into high-resolution images). It outperformed models like GPT-4o and Claude 3 Opus.

“The fact that Claude 3.5 Sonnet outperformed other models like GPT-4o and Claude 3 Opus suggests that this model processes and generates visual-related information differently,” says co-author Tamar Rott Shaham.

She adds that SketchAgent could become a helpful interface for collaborating with AI models beyond standard, text-based communication. “As models advance in understanding and generating other modalities, like sketches, they open up new ways for users to express ideas and receive responses that feel more intuitive and human-like,” says Shaham. “This could significantly enrich interactions, making AI more accessible and versatile.”

While SketchAgent’s drawing prowess is promising, it can’t make professional sketches yet. It renders simple representations of concepts using stick figures and doodles, but struggles to doodle things like logos, sentences, complex creatures like unicorns and cows, and specific human figures.

At times, their model also misunderstood users’ intentions in collaborative drawings, like when SketchAgent drew a bunny with two heads. According to Vinker, this may be because the model breaks down each task into smaller steps (also called “Chain of Thought” reasoning). When working with humans, the model creates a drawing plan, potentially misinterpreting which part of that outline a human is contributing to. The researchers could possibly refine these drawing skills by training on synthetic data from diffusion models.

Additionally, SketchAgent often requires a few rounds of prompting to generate human-like doodles. In the future, the team aims to make it easier to interact and sketch with multimodal language models, including refining their interface. 

Still, the tool suggests AI could draw diverse concepts the way humans do, with step-by-step human-AI collaboration that results in more aligned final designs.

This work was supported, in part, by the U.S. National Science Foundation, a Hoffman-Yee Grant from the Stanford Institute for Human-Centered AI, the Hyundai Motor Co., the U.S. Army Research Laboratory, the Zuckerman STEM Leadership Program, and a Viterbi Fellowship.

The Hertz Foundation announced that it has awarded fellowships to eight MIT affiliates. The prestigious award provides each recipient with five years of doctoral-level research funding (up to a total of $250,000), which gives them an unusual measure of independence in their graduate work to pursue groundbreaking research.

The MIT-affiliated awardees are Matthew Caren ’25; April Qiu Cheng ’24; Arav Karighattam, who begins his PhD at the Institute this fall; Benjamin Lou ’25; Isabelle A. Quaye ’22, MNG ’24; Albert Qin ’24; Ananthan Sadagopan ’24; and Gianfranco (Franco) Yee ’24.

“Hertz Fellows embody the promise of future scientific breakthroughs, major engineering achievements and thought leadership that is vital to our future,” said Stephen Fantone, chair of the Hertz Foundation board of directors and president and CEO of Optikos Corp., in the announcement. “The newest recipients will direct research teams, serve in leadership positions in our government and take the helm of major corporations and startups that impact our communities and the world.”

In addition to funding, fellows receive access to Hertz Foundation programs throughout their lives, including events, mentoring, and networking. They join the ranks of over 1,300 former Hertz Fellows since the fellowship was established in 1963 who are leaders and scholars in a range of technology, science, and engineering fields. Former fellows have contributed to breakthroughs in such areas as advanced medical therapies, computational systems used by billions of people daily, global defense networks, and the recent launch of the James Webb Space Telescope.

This year’s MIT recipients are among a total of 19 Hertz Foundation Fellows scholars selected from across the United States.

Matthew Caren ’25 studied electrical engineering and computer science, mathematics, and music at MIT. His research focuses on computational models of how people use their voices to communicate sound at the Computer Science and Artificial Intelligence Lab (CSAIL) and interpretable real-time machine listening systems at the MIT Music Technology Lab. He spent several summers developing large language model systems and bioinformatics algorithms at Apple and a year researching expressive digital instruments at Stanford University’s Center for Computer Research in Music and Acoustics. He chaired the MIT Schwarzman College of Computing Undergraduate Advisory Group, where he led undergraduate committees on interdisciplinary computing AI and was a founding member of the MIT Voxel Lab for music and arts technology. In addition, Caren has invented novel instruments used by Grammy-winning musicians on international stages. He plans to pursue a doctorate at Stanford.

April Qiu Cheng ’24 majored in physics at MIT, graduating in just three years. Their research focused on black hole phenomenology, gravitational-wave inference, and the use of fast radio bursts as a statistical probe of large-scale structure. They received numerous awards, including an MIT Outstanding Undergraduate Research Award, the MIT Barrett Prize, the Astronaut Scholarship, and the Princeton President’s Fellowship. Cheng contributed to the physics department community by serving as vice president of advocacy for Undergraduate Women in Physics and as the undergraduate representative on the Physics Values Committee. In addition, they have participated in various science outreach programs for middle and high school students. Since graduating, they have been a Fulbright Fellow at the Max Planck Institute for Gravitational Physics, where they have been studying gravitational-wave cosmology. Cheng will begin a doctorate in astrophysics at Princeton in the fall.

Arav Karighattam was home schooled, and by age 14 had completed most of the undergraduate and graduate courses in physics and mathematics at the University of California at Davis. He graduated from Harvard University in 2024 with a bachelor’s degree in mathematics and will attend MIT to pursue a PhD, also in mathematics. Karighattam is fascinated by algebraic number theory and arithmetic geometry and seeks to understand the mysteries underlying the structure of solutions to Diophantine equations. He also wants to apply his mathematical skills to mitigating climate change and biodiversity loss. At a recent conference at MIT titled “Mordell’s Conjecture 100 Years Later,” Karighattam distinguished himself as the youngest speaker to present a paper among graduate students, postdocs, and faculty members.

Benjamin Lou ’25 graduated from MIT in May with a BS in physics and is interested in finding connections between fundamental truths of the universe. One of his research projects applies symplectic techniques to understand the nature of precision measurements using quantum states of light. Another is about geometrically unifying several theorems in quantum mechanics using the Prüfer transformation. For his work, Lou was honored with the Barry Goldwater Scholarship. Lou will pursue his doctorate at MIT, where he plans to work on unifying quantum mechanics and gravity, with an eye toward uncovering experimentally testable predictions. Living with the debilitating disease spinal muscular atrophy, which causes severe, full-body weakness and makes scratchwork unfeasible, Lou has developed a unique learning style emphasizing mental visualization. He also co-founded and helped lead the MIT Assistive Technology Club, dedicated to empowering those with disabilities using creative technologies. He is working on a robotic self-feeding device for those who cannot eat independently.

Isabelle A. Quaye ’22, MNG ’24 studied electrical engineering and computer science as an undergraduate at MIT, with a minor in economics. She was awarded competitive fellowships and scholarships from Hyundai, Intel, D. E. Shaw, and Palantir, and received the Albert G. Hill Prize, given to juniors and seniors who have maintained high academic standards and have made continued contributions to improving the quality of life for underrepresented students at MIT. While obtaining her master’s degree at MIT, she focused on theoretical computer science and systems. She is currently a software engineer at Apple, where she continues to develop frameworks that harness intelligence from data to improve systems and processes. Quaye also believes in contributing to the advancement of science and technology through teaching and has volunteered in summer programs to teach programming and informatics to high school students in the United States and Ghana.

Albert Qin ’24 majored in physics and mathematics at MIT. He also pursued an interest in biology, researching single-molecule approaches to study transcription factor diffusion in living cells and studying the cell circuits that control animal development. His dual interests have motivated him to find common ground between physics and biological fields. Inspired by his MIT undergraduate advisors, he hopes to become a teacher and mentor for aspiring young scientists. Qin is currently pursuing a PhD at Princeton University, addressing questions about the behavior of neural networks — both artificial and biological — using a variety of approaches and ideas from physics and neuroscience.

Ananthan Sadagopan ’24 is currently pursuing a doctorate in biological and biomedical science at Harvard University, focusing on chemical biology and the development of new therapeutic strategies for intractable diseases. He earned his BS at MIT in chemistry and biology in three years and led projects characterizing somatic perturbations of X chromosome inactivation in cancer, developing machine learning tools for cancer dependency prediction, using small molecules for targeted protein relocalization and creating a generalizable strategy to drug the most mutated gene in cancer (TP53). He published as the first author in top journals, such as Cell, during his undergraduate career. He also holds patents related to his work on cancer dependency prediction and drugging TP53. While at the Institute, he served as president of the Chemistry Undergraduate Association, winning both the First-Year and Senior Chemistry Achievement Awards, and was head of the events committee for the MIT Science Olympiad.

Gianfranco (Franco) Yee ’24 majored in biological engineering at MIT, conducting research in the Manalis Lab on chemical gradients in the gut microenvironment and helping to develop a novel gut-on-a-chip platform for culturing organoids under these gradients. His senior thesis extended this work to the microbiome, investigating host-microbe interactions linked to intestinal inflammation and metabolic disorders. Yee also earned a concentration in education at MIT, and is committed to increasing access to STEM resources in underserved communities. He co-founded Momentum AI, an educational outreach program that teaches computer science to high school students across Greater Boston. The inaugural program served nearly 100 students and included remote outreach efforts in Ukraine and China. Yee has also worked with MIT Amphibious Achievement and the MIT Office of Engineering Outreach Programs. He currently attends Gerstner Sloan Kettering Graduate School, where he plans to leverage the gut microbiome and immune system to develop innovative therapeutic treatments.

Former Hertz Fellows include two Nobel laureates; recipients of 11 Breakthrough Prizes and three MacArthur Foundation “genius awards;” and winners of the Turing Award, the Fields Medal, the National Medal of Technology, the National Medal of Science, and the Wall Street Journal Technology Innovation Award. In addition, 54 are members of the National Academies of Sciences, Engineering and Medicine, and 40 are fellows of the American Association for the Advancement of Science. Hertz Fellows hold over 3,000 patents, have founded more than 375 companies, and have created hundreds of thousands of science and technology jobs.

Every year, thousands of students take courses that teach them how to deploy artificial intelligence models that can help doctors diagnose disease and determine appropriate treatments. However, many of these courses omit a key element: training students to detect flaws in the training data used to develop the models.

Leo Anthony Celi, a senior research scientist at MIT’s Institute for Medical Engineering and Science, a physician at Beth Israel Deaconess Medical Center, and an associate professor at Harvard Medical School, has documented these shortcomings in a new paper and hopes to persuade course developers to teach students to more thoroughly evaluate their data before incorporating it into their models. Many previous studies have found that models trained mostly on clinical data from white males don’t work well when applied to people from other groups. Here, Celi describes the impact of such bias and how educators might address it in their teachings about AI models.

Q: How does bias get into these datasets, and how can these shortcomings be addressed?

A: Any problems in the data will be baked into any modeling of the data. In the past we have described instruments and devices that don’t work well across individuals. As one example, we found that pulse oximeters overestimate oxygen levels for people of color, because there weren’t enough people of color enrolled in the clinical trials of the devices. We remind our students that medical devices and equipment are optimized on healthy young males. They were never optimized for an 80-year-old woman with heart failure, and yet we use them for those purposes. And the FDA does not require that a device work well on this diverse of a population that we will be using it on. All they need is proof that it works on healthy subjects.

Additionally, the electronic health record system is in no shape to be used as the building blocks of AI. Those records were not designed to be a learning system, and for that reason, you have to be really careful about using electronic health records. The electronic health record system is to be replaced, but that’s not going to happen anytime soon, so we need to be smarter. We need to be more creative about using the data that we have now, no matter how bad they are, in building algorithms.

One promising avenue that we are exploring is the development of a transformer model of numeric electronic health record data, including but not limited to laboratory test results. Modeling the underlying relationship between the laboratory tests, the vital signs and the treatments can mitigate the effect of missing data as a result of social determinants of health and provider implicit biases.

Q: Why is it important for courses in AI to cover the sources of potential bias? What did you find when you analyzed such courses’ content?

A: Our course at MIT started in 2016, and at some point we realized that we were encouraging people to race to build models that are overfitted to some statistical measure of model performance, when in fact the data that we’re using is rife with problems that people are not aware of. At that time, we were wondering: How common is this problem?

Our suspicion was that if you looked at the courses where the syllabus is available online, or the online courses, that none of them even bothers to tell the students that they should be paranoid about the data. And true enough, when we looked at the different online courses, it’s all about building the model. How do you build the model? How do you visualize the data? We found that of 11 courses we reviewed, only five included sections on bias in datasets, and only two contained any significant discussion of bias.

That said, we cannot discount the value of these courses. I’ve heard lots of stories where people self-study based on these online courses, but at the same time, given how influential they are, how impactful they are, we need to really double down on requiring them to teach the right skillsets, as more and more people are drawn to this AI multiverse. It’s important for people to really equip themselves with the agency to be able to work with AI. We’re hoping that this paper will shine a spotlight on this huge gap in the way we teach AI now to our students.

Q: What kind of content should course developers be incorporating?

A: One, giving them a checklist of questions in the beginning. Where did this data came from? Who were the observers? Who were the doctors and nurses who collected the data? And then learn a little bit about the landscape of those institutions. If it’s an ICU database, they need to ask who makes it to the ICU, and who doesn’t make it to the ICU, because that already introduces a sampling selection bias. If all the minority patients don’t even get admitted to the ICU because they cannot reach the ICU in time, then the models are not going to work for them. Truly, to me, 50 percent of the course content should really be understanding the data, if not more, because the modeling itself is easy once you understand the data.

Since 2014, the MIT Critical Data consortium has been organizing datathons (data “hackathons”) around the world. At these gatherings, doctors, nurses, other health care workers, and data scientists get together to comb through databases and try to examine health and disease in the local context. Textbooks and journal papers present diseases based on observations and trials involving a narrow demographic typically from countries with resources for research. 

Our main objective now, what we want to teach them, is critical thinking skills. And the main ingredient for critical thinking is bringing together people with different backgrounds.

You cannot teach critical thinking in a room full of CEOs or in a room full of doctors. The environment is just not there. When we have datathons, we don’t even have to teach them how do you do critical thinking. As soon as you bring the right mix of people — and it’s not just coming from different backgrounds but from different generations — you don’t even have to tell them how to think critically. It just happens. The environment is right for that kind of thinking. So, we now tell our participants and our students, please, please do not start building any model unless you truly understand how the data came about, which patients made it into the database, what devices were used to measure, and are those devices consistently accurate across individuals?

When we have events around the world, we encourage them to look for data sets that are local, so that they are relevant. There’s resistance because they know that they will discover how bad their data sets are. We say that that’s fine. This is how you fix that. If you don’t know how bad they are, you’re going to continue collecting them in a very bad manner and they’re useless. You have to acknowledge that you’re not going to get it right the first time, and that’s perfectly fine. MIMIC (the Medical Information Marked for Intensive Care database built at Beth Israel Deaconess Medical Center) took a decade before we had a decent schema, and we only have a decent schema because people were telling us how bad MIMIC was.

We may not have the answers to all of these questions, but we can evoke something in people that helps them realize that there are so many problems in the data. I’m always thrilled to look at the blog posts from people who attended a datathon, who say that their world has changed. Now they’re more excited about the field because they realize the immense potential, but also the immense risk of harm if they don’t do this correctly.

Below is the text of Melissa Nobles’ remarks, as prepared for delivery today.

Wow, thank you Emily and Andrew! Emily Jin on vocals and Andrew Li on saxophone, and their fellow musicians!

Class of 2025! Look at you, you’re looking really good in your regalia! It’s your graduation day! You did it! Congratulations!

And congratulations to all of your loved ones, all of the people who helped support you.

Your parents, your brothers and sisters, your aunties and your uncles, and your friends. This is a special day for them too. They are so proud of you!

A warm welcome to the loved ones who are here with us today on Killian Court — they’ve come here from all over to celebrate you!

And a special shout out to those who are watching from afar, wishing they could be here with you in person!

Class of 2025, you’ve made a lot of memories during your time here: from classes to crushes, from the East Campus REX build to the Simmons ball pit to Next Haunt, from UROPs to the Hobby Shop, and from the Outfinite to the Infinite!

So, I’d like to take you back to the fall of 2021, when you arrived here at MIT.

You traveled from all parts of this country and the world — from 62 countries, to be exact — and landed right here in Cambridge. Together, you became MIT’s Class of 2025.

And you arrived on campus — all bright-eyed and beaver-tailed — after missing a lot of in-person high school rituals, a lot of the high school experience. So, you were extra eager for college, and, more specifically, super excited to be MIT students!

Although the campus was officially fully open for the first time since the Covid shutdown — students, staff, and faculty were all here in person, with Zoom taking a back seat to meeting in real life — there were still a lot of protocols in place.

You had to get through all the Covid tests because we were still testing. Do you remember those Ziploc bags?

You swabbed and submitted attestations because you wanted the keys to unlock doors to labs, classrooms, and all the experiences that make MIT, MIT.

And once you gained access, you discovered a campus that was shiny and welcoming, yet dusty after being mostly empty for a long while. And there was no manual for how to reanimate this place.

You didn’t flinch.

You chose MIT because you like to solve problems, and your inner beaver came out to bring the campus back to life, to make it a home.

You were curious, you surveyed the landscape, and you started to dig into the past in order to build your future.

You sought out seniors, the Class of 2022, to read you in, to show you the ropes, and they really came through for you. They felt the urgency of their limited time left on campus, and they taught you “how to MIT.”

You also pored through archival records of clubs, soaking up history to guide you forward. You filled in the gaps by speaking with faculty and staff and alums. You evaluated the options, decided what you wanted to revive and what you wanted to scrap.

And true to your nature as MIT students, you launched new stuff. You innovated and invented.

And you built communities, from FPOPs and orientation through 8.01, 18.02, your HASS classes, and your p-set groups.

You built communities in your dorms and in your sororities and fraternities.

You built communities through your sports, through your hobbies and through the arts.

You built communities all across campus.

And you learned that building communities is not always easy and quick. It takes effort, patience, and a willingness to listen to and learn from others.

But, in the end, it is so worth it because you’ve met and made friends with really interesting people. Some with similar backgrounds and others from very different backgrounds. And from that interesting and diverse group, you’ve identified your crew — the people with whom you’ve shared not only interests — but your dreams, your fears, your concerns, laughs, and tears. You’ve made real connections — connections that lead to a lifetime of friendship.

And over the past four years, right before our eyes, you’ve demonstrated the enduring value and power of higher education to change lives.

Throughout your time at MIT, you ideated, prototyped, and tested. You created new knowledge, waded through ambiguity, worked collaboratively, and, of course, you optimized.

Now, on your graduation day, we send you on your way with enormous pride and hope.

But at the same time, we are sending you out into the world at a very difficult and challenging time. It’s a time when we all are being asked to focus on traditions that we should honor and defend. It’s also a time calling on us to create new traditions, better suited to human thriving in this century.

It’s a time when the issues are big, the answers are complex, the stakes are high, and the paths are uncharted.

But, Class of 2025, you are prepared to face these daunting conditions. In the words of one of your classmates: MIT taught the Class of 2025 to have “confidence in your competence.”

You are ready to assess your environment, diagnose what is stale and what is broken, learn from history, apply your talents and skills, and create new knowledge.

You are ready to tackle the toughest of problems! You are ready to shape the future.   

And while you are doing so, I ask that you keep MIT’s values and mission at the center of your efforts: to be bold and imaginative in tackling these big problems and to do so with compassion and generosity.

Now, more than ever, we — meaning the world’s people — need you to lean in.

Once again, Congratulations Class of 2025!

“Class of 2025, are you ready?”

This was the question Hashim Sarkis, dean of the MIT School of Architecture and Planning, posed to the graduating class at the school’s Advanced Degree Ceremony at Kresge Auditorium on May 29. The response was enthusiastic applause and cheers from the 224 graduates from the departments of Architecture and Urban Studies and Planning, the Program in Media Arts and Sciences, and the Center for Real Estate.

Following his welcome to an audience filled with family and friends of the graduates, Sarkis introduced the day’s guest speaker, whom he cited as the “perfect fit for this class.” Recognizing the “international rainbow of graduates,” Sarkis welcomed Mary Robinson, former president of Ireland and head of the Mary Robinson Foundation — Climate Justice to the podium. Robinson, a lawyer by training, has had a wide-ranging career that began with elected positions in Ireland followed by leadership roles in global causes for justice, human rights, and climate change.

Robinson laced her remarks with personal anecdotes from her career, from with earning a master’s in law at nearby Harvard University in 1968 — a year of political unrest in the United States — to founding The Elders in 2007 with world leaders: former South African President Nelson Mandela, anti-apartheid and human rights activist Desmond Tutu, and former U.S. President Jimmy Carter.

She described an “early lesson” in recounting her efforts to reform the laws of contraception in Ireland at the beginning of her career in the Irish legislature. Previously, women were not prescribed birth control unless they were married and had irregular menstrual cycles certified by their physicians. Robinson received thousands of letters of condemnation and threats that she would destroy the country of Ireland if she would allow contraception to be more broadly available. The legislation introduced was successful despite the “hate mail” she received, which was so abhorrent that her fiancé at the time, now her husband, burned it. That experience taught her to stand firm to her values.

“If you really believe in something, you must be prepared to pay a price,” she told the graduates.

In closing, Robinson urged the class to put their “skills and talent to work to address the climate crisis,” a problem she said she came late to in her career.

“You have had the privilege of being here at the School of Architecture and Planning at MIT,” said Robinson. “When you leave here, find ways to lead.”

Below is the text of President Sally Kornbluth’s 2025 MIT Commencement remarks, as prepared for delivery today.

Good afternoon, everyone! Governor Healey. The members of the Class of 1975, in their incredibly fashionable red jackets! And of course, all the members of the Class of 2025 — and your devoted family and friends!

At MIT, it’s customary for the president to deliver a “charge” to the graduating class. And I’ll start by reflecting briefly on the world we make together here at MIT.

At MIT, we allow a lot of room for disagreement, whether the subject is scientific, personal, or political. The friction of disagreement is a very effective way to sharpen each other’s thinking. (If you don’t believe me, I’d urge you to attend a faculty meeting!)

But in this disconcerting time, as we prepare to send the Class of 2025 out into the world, I want to 
celebrate three fundamental things we do agree on — the rock-solid foundation of our shared work and understanding.

First, we believe in the beauty and power of the scientific method. Winston Churchill once observed that, “No one pretends that democracy is perfect or all-wise,” In fact, as he famously acknowledged, “Democracy is the worst form of government — except for all the other forms that have been tried.”

And you could say the same — with reverence! — for the scientific method. None of us would argue that it’s “perfect or all-wise.”

But the scientific method remains the single most reliable tool humans have ever devised to arrive at the truth about the physical world. It’s designed to root out error, protect us against our own biases and assumptions, and provide a systematic way to turn facts we cannot see at first into knowledge we can act on. 

It’s hard to imagine anything more useful than that.

Second, we believe in the beauty and power of fundamental scientific discovery – that incredibly intricate, maddening, heroic, intoxicating process of exploration and testing that somehow got stuck with the bland label “basic research.” 
 

We believe scientific discovery is deeply valuable and inspiring, in itself — and we know that it’s absolutely essential for driving innovation and delivering new tools, technologies, treatments, and cures.

And finally — from direct personal experience here at MIT — we all know that we’re sharper, more rigorous, more curious, more inventive and more likely to achieve breakthrough results when we work together with brilliant people, across a broad spectrum of backgrounds, perspectives, and viewpoints, from across the country and all around the world.

You don’t find the big ideas in an echo chamber! 

And I want to say something I’ve said repeatedly: MIT would not be MIT without our international students!

*              *

The beauty and power of the scientific method. The beauty and power of scientific discovery. And frankly, the beauty and power of the Institute’s incredible global community. 

For those of us associated with MIT, these three concepts may seem almost too obvious to require explanation, let alone celebration.

But we find ourselves in a bewildering time, a time when these concepts have never been more important — and have rarely been in such peril.

So now, I offer my charge to the members of the Class of 2025.

To today’s graduates:

I hope and believe that, in your time here, you’ve prepared yourselves very effectively for the next steps in your life and career. I wish you every success in that next step, and all that come after it.

But I must ask that each of you take on another job. A lifelong job. An urgent job.

I need you all to become ambassadors for the way we think and work and thrive at MIT.

Ambassadors for scientific thinking and scientific discovery! For thoughtful research of every kind, here — and at universities across the country! For the importance of research to the advancement of our nation — and our species! And ambassadors for the limitless possibilities when we understand, appreciate and magnify each other’s talent and potential, in a thriving global community.

This ambassadorship has no salary besides your sense of its crucial importance. But I hope you will accept the responsibility — because no one else can make the case more effectively. And these concepts are the indispensable foundation of everything else we aim to achieve.

*              *

There’s only one way to get through MIT.

The hard way.

Each of you has done that — and in the context of historic challenges. May all the strengths and insights that you’ve gained here serve you brilliantly on the road ahead. Thank you — and congratulations!

An energetic OneMIT Commencement ceremony today featured calls for MIT’s newest graduates to have a positive impact on society while upholding the Institute’s core values of open inquiry and productive innovation.

“Orient yourself not just toward the construction and acquisition of new tools, but to the needs of people,” said science communicator Hank Green, in the event’s keynote remarks. He urged MIT’s newest graduates to focus their work on the “everyday solvable problems of normal people,” even if it is not always the easiest or most obvious course of action.

“Because people are so complex and messy, some of you may be tempted to build around them and not for them,” Green continued. “But remember to ask yourself where value and meaning originate, where they come from.” He then provided one answer: “Value and meaning come from people.”

Green is a hugely popular content creator and YouTuber whose work often focuses on science and STEM issues, and who has built, with his brother, John, the educational media company Complexly. Their content, including the channels SciShow and CrashCourse, is widely used in schools and has tallied over 2 billion views. Green, a cancer survivor, is also writing a book explaining the biology of cancer.

The ceremony also featured remarks from MIT President Sally A. Kornbluth, who delivered the traditional “charge” to new graduates while reflecting on the values of MIT and the value it brings society.

“We believe scientific discovery is deeply valuable and inspiring in itself — and we know that it’s absolutely essential for driving innovation and delivering new tools, technologies, treatments, and cures,” she said.

Kornbluth challenged graduates to be “ambassadors” for the open-minded inquiry and collaborative work that marks everyday life at MIT.

“I need you all to become ambassadors for the way we think and work and thrive at MIT,” she said. “Ambassadors for scientific thinking and scientific discovery. For thoughtful research of every kind — here, and at universities across the country. For the importance of research to the advancement of our nation — and our species. And ambassadors for the limitless possibilities when we understand, appreciate and magnify each other’s talent and potential, in a thriving global community.”

Kornbluth also elaborated on the core elements of the work MIT has always pursued.

“At MIT, we allow a lot of room for disagreement, whether the subject is scientific, personal or political,” Kornbluth said. Still, she noted, “in this disconcerting time, as we prepare to send the Class of 2025 out into the world, I want to celebrate three fundamental things we do agree on — the rock-solid foundation of our shared work and understanding.”

The first of these, Kornbluth said, is that “we believe in the beauty and power of the scientific method. … It’s designed to root out error, protect us against our own biases and assumptions, and provide a systematic way to turn facts we cannot see at first into knowledge we can act on. It’s hard to imagine anything more useful than that.” Secondly, she said, in a similar vein, “we believe in the beauty and power of fundamental scientific discovery.”

A third element, Kornbluth observed, is that “we all know that we’re sharper, more rigorous, more curious, more inventive and more likely to achieve breakthrough results when we work together with brilliant people, across a broad spectrum of backgrounds, perspectives and viewpoints, from across the country and all around the world. You don’t find the big ideas in an echo chamber.”

Kornbluth added: “I want to say something I’ve said repeatedly: MIT would not be MIT without our international students.”

MIT’s Commencement celebrations are taking place this week, from May 28 through May 30. The OneMIT Commencement Ceremony is an Institute-wide event, held in MIT’s Killian Court and streamed online. MIT’s undergraduates, as well as advanced degree students in its five schools and the MIT Schwarzman College of Computing, also have additional, separate ceremonies in which graduates receive their degrees individually.The OneMIT event also featured remarks from Massachusetts Governor Maura Healey, who said she was “incredibly proud” of the graduates and the Institute itself.

“You stand for the qualities that make Massachusetts special: a passion for learning and discovery that is so powerful it changes the world,” Healey said. “Curing disease. Inventing technologies. Solving tough problems for communities, organizations, and people all around the globe. Making lives better and powering our economies. Thanks to you, Massachusetts is No. 1 for innovation and education.” She added: “MIT’s contributions to our knowledge economy — and our culture of discovery — are a pillar of Massachusetts’ national and global leadership.”

Speaking of the economic impact of MIT-linked businesses, Healey had an additional suggestion for the graduates: “Put your talents to work in Massachusetts, a place where you are valued, respected, and surrounded by incredibly talented, engaged innovators and investors. Make your discoveries here. Found your startups here. Scale your companies here.”

She even quipped, “We put forward some pretty good incentives through our economic development legislation and we’ll help you find a way to spend that. Just reach out to my economic development team.”

Green imparted general life advice as well.

“One of the problems you will solve is how to find joy in an imperfect world,” Green said in his Commencement address. “And you might struggle with not feeling productive, unless and until you accept that your own joy can be one of the things you produce.”

On another note, Green added, “Ideas do not belong in your head. They can’t help anyone in there. I sometimes see people become addicted to their good idea. … They can’t bring themselves to expose it to the imperfection of reality. Stop waiting. Get the ideas out. … You may fail, but while you fail, you will build new tools.”

Throughout his speech, Green emphasized the humanitarian qualities of MIT’s students. This past semester, after being named Commencement speaker, he sent the graduating class a survey that about half of the class responded to.

The survey included the question, “What gives you hope?” In his speech, Green said the many of the responses involved other people. Or, as he characterized it, “People who care. People who focus on improving life in their communities. People who are standing up for what they believe in. People who see big problems and have the determination to fix them.”

The OneMIT ceremony began with the annual alumni parade, this time featuring the undergraduate class of 1975, while the Killian Court Brass Ensemble, conducted by Kenneth Amis, played the processional entry music.

The Chaplain to the Institite, Thea Keith-Lucas, delivered the invocation, while the campus a capella group, the Chorallaries of MIT, sang “The Star Spangled Banner,” and later, the school song, “In praise of MIT,” as well as another Institute anthem, “Take Me Back to Tech.”

Despite many uncertainties facing higher education, the MIT students, families, friends, and community members present reveled in a festive moment, celebrating the achievements of the graduates. A total of 1,158 undergraduate and 2,593 graduate students received MIT diplomas this academic year.

“There’s only one way to get through MIT,” Kornbluth quipped. “The hard way.” 

Below is the text of Hank Green’s Commencement remarks as prepared for delivery on May 29.

I don’t really do imposter syndrome, that’s where you feel like you don’t belong. I have a superior syndrome called “Hahaha I fooled them again” syndrome where I know that I don’t belong, but I also am very pleased that I have once again cleverly convinced you that I do.

I, a man you might very well know as a tiktoker, a man who recently blind-ranked AI company logos by how much they look like buttholes, have snuck into giving MIT’s Commencement speech. And I can admit this because you can’t kick me off now, I’ve already started speaking! It would be weird if you stopped … but still, I’m going to try to do a good job.

Hello and thank you very much to everybody for welcoming me out, all the lovely people up here, the president, the governor, the alumni, Class of 75, and also of course, thank you especially to a class of extremely impressive charismatic and attractive students of the Massachusetts Institute of Technology graduating Class of 2025.

To express my thanks: The average human skeleton has more than 25,000 calories. More than half of your bones are in your hands and feet, and all together your skeleton contains enough oxygen atoms that, if you freed them, you could produce around 24 hours of breathable air.

Those were some of my best bone facts, and I assume that good bone facts are a totally normal way for humans to show gratitude.

I gave you my very best bone facts because I owe an extra debt of gratitude to you, the Class of 2025, because more than half of you filled out a survey I sent you! I assume you did it late at night while you should have been p-setting, whatever that is, but instead you did this.

And I have loved looking through your responses and learning a little bit about you, and a little bit from you.

One of the things asked you what the most MIT thing you did at MIT was, and this was my favorite section to read.

Some of it was definitely not meant for me to understand, like several of you counted up all the smoots on the Harvard Bridge.

Whatever that means … good work.

One of you was Tim the Beaver. Another tried to impress a date with train facts.

I see you. Same … but with bones.

A lot, and I mean a lot of you simply said the word “hack,” and the lack of specificity there, I have to say, does make me feel like whatever you did, the statute of limitations has not yet kicked in.

But by far the most common beginning of a sentence in this section was “I built…” You built robots and bridges and incubators and startups and Geiger counters and a remote-controlled shopping cart and a ukelele and an eight-foot-wide periodic table. Y’all built … a lot.

And that is something I found reassuring. We are going to need to do a lot of building.

I took a look at your shoes as you were coming, but it turns out I didn’t need to see them to know I wouldn’t want to be in them.

I think the only people jealous of you right now is the Class of 2026 because I’m sure things will be even more screwed up by the time they’re sitting where you are. But what a terribly messy time to be graduating from college. The attacks on speech, on science, on higher education, on trans rights, on the federal workforce, on the rule of law … they’re coming from inside the house.

Meanwhile, the world is getting hotter faster. And the sudden acceleration in the abilities of artificial intelligence, communication, and biotechnology promise huge opportunities, and massive disruption.

So, if I were you, I would want some advice! But as previously mentioned, I am a TikTok-er who will now forever be known as the first person to ever say the word “butthole” during an MIT commencement speech. So the advice — some of it — is going to come from you. I asked you, in my survey, what you would say to your classmates from a stage like the one I am now on. And here’s a selection.

One of your classmates wrote:

I always forget which Green brother is Hank and which is John!

There is no one definition of success. The idea you have in your head of what success is, it’s going to change, and you should let it.

Is one of your classmates 45 years old?

And here’s another 45-year-old hiding among you:

Open a Roth IRA.

Jeez! Did your dad fill out my survey for you? Seriously though, you should.

Here’s one of my real favorites:

Collaborate and help each other, be brave in reaching out, and be forgiving in your interactions.

Even if it probably won't work, try anyway.

Don’t start with the solution, start with the problem.

Now a lot of you might be thinking right now: Did he just make us write his Commencement speech for him? And the answer to that is, well, at least you know that Claude didn’t write it.

I’ve had a good time here focusing on the ludicrous aspects of my career, and I do want to emphasize its ludicriousness.

I’ve done TikTok dances to Elmo remixes, and I’ve also published two best-selling science fiction novels. I’ve written fart listicles, and I’ve interviewed presidents. I’ve made multiple videos about giraffe sex, and I’ve sold multiple companies. I helped build an educational media company that provides videos for free to everyone with an internet connection, and our content is used in most American schools.

And yes, that was the section I put in so your parents could feel better about me being here. I left it as long as I could.

I am good at having an idea I believe in and then just doing it, consequences be damned, and that has served me well, though it has not always been relaxing.

And I did that all on the uncertain and rapidly changing ground of online video and social media over the last 20 years. So perhaps I do have something to say to a class of graduates heading out into an uncertain and unstable world.

If I could attribute my success, whatever it is, to anything besides luck, it’s that I literally can’t stop believing that there is any better use of time than learning something new.

And curiosity doesn’t just expand the number of tools you have and how well you’re able to use them, it expands your understanding of the problem space.

And so maybe the advice is very simple. Just be curious about the world and you’ll have everything you need for the future and, look, it is almost that simple.

There’s a really important question I asked y’all in my survey that I haven’t mentioned yet. I asked, “What’s giving you hope?”

And though one of you wrote “Macallan 12,” most of you, in your response, talked entirely about people: my friends, my family, my peers, over and over.

People who care. People who focus on improving life in their communities. People who are standing up for what they believe in. People who see big problems and have the determination to fix them.

At a school like MIT, I imagine that the focus can definitely be on the building and less on the people. This is an institute of technology, not of humanities. But I read the humanity in your answers.

And this brings me back to the simplicity of curiosity leading you both toward understanding problems and acquiring new tools. Because your curiosity is not out of your control. You decide how you orient it, and that orientation is going to affect the entire rest of your life. It may be the single most important factor in your career.

And my guess is that it’s going to be really easy to be focused on the problem of just building ever more powerful tools. That’s exciting stuff and also it can be surprisingly uncomplicated. But even though the problem space is much bigger than just “build bigger tools,” it is surprisingly easy to simply never notice that.

The most powerful mechanisms that steer our focus are … I’m just going to say this … not always designed for our best interests, or the best interests of our world. Social content platforms are great at steering our curiosities and they are, often, designed to make us afraid, to keep us oriented toward impossible problems, or toward the hottest rifts in society.

Meanwhile, the capitalist impulse is very good at keeping us oriented toward the problems that can be most easily monetized, and that means an over-weighting toward the problems that the most powerful and wealthy people are interested in solving.

If we let ourselves be oriented only by those forces, guess what problems we will not pay any attention to. All of the everyday solvable problems of normal people.

I desperately hope that you remain curious about our world’s intensely diverse and massive problem space. Solveable problems! That are not being addressed because our world does not orient us toward them. If you can control your obsessions, you will not just be unstoppable, you will leave this world a much better place than you found it.

This is not about choosing between financial stability and your ideals. No. There is money to be made in these spaces. This is simply about who you include in your problem space, about what you choose to be curious about.

So with that in mind, here’s my advice, from my heart and from my experience.

First, don’t eat grass.

Second, more importantly, one of the problems you will solve is how to find joy in an imperfect world. And you might struggle with not feeling productive unless and until you accept that your own joy can be one of the things you produce.

Third, ideas do not belong in your head. They can’t help anyone in there. I sometimes see people become addicted to their good idea. They love it so much, they can’t bring themselves to expose it to the imperfection of reality. Stop waiting. Get the ideas out. You may fail, but while you fail, you will build new tools.

And fourth, because people are so complex and messy, some of you may be tempted to build around them and not for them. But remember to ask yourself where value and meaning come from, because they don’t come from banks or tech or cap tables. They come from people.

People things are the hardest work, but also often the most important work. Orient yourself not just toward the construction and acquisition of new tools, but to the needs of people, and that include you, it includes your friends and your family. I think we can sometimes feel so powerful and like the world is so big that throwing a birthday party or making a playlist for a friend can seem too insignificant when placed against the enormity of AI and climate change and the erosion of democracy. But those thoughts alienate you from the reality of human existence, from your place as a builder not just of tools, but of meaning. And that’s not just about impact and productivity and problem solving, it is about living a life.

Do. Not. Forget. how special and bizarre it is to get to live a human life. It took 3 billion years for the Earth to go from single-celled life forms to you. That’s more than a quarter of the life of the entire universe. Something very special and strange is happening on this planet and it is you.

The greatest thing you build in your life will be yourself, and trust me on this you are not done yet, I know I’m not. But what you will be building is not just a toolkit. You will be building a person, and you will be doing it for people.

When I asked you what you did at MIT, you said you built, but when I asked you what was giving you hope, you did not say “buildings” you said “people.” So, to the graduating Class of 2025, go forth, for yourself, for others, and for this beautiful, bizarre world.

Thank you.

The MIT Corporation — the Institute’s board of trustees — has elected 10 full-term members, who will serve three- or five-year terms, and three life members. Corporation Chair Mark P. Gorenberg ’76 announced the election results today.

The full-term members are: Wes Bush, Ruby R. Chandy, Hala Fadel, Jacques Frederic Kerrest, Michelle K. Lee, Bianca Lepe, Natalie M. Lorenz Anderson, Sebastian S. Man, Hyun-A C. Park, and Thomas Tull. The three life members are: Orit Gadiesh, Jeff Halis, and Alan Leventhal. Gorenberg was also re-elected as Corporation chair.

Stephen P. DeFalco ’83, SM ’88, the 2025-2026 president of the Association of Alumni and Alumnae of MIT, will also join the Corporation as an ex officio member. He succeeds Natalie Lorenz-Anderson ’84.

As of July 1, the Corporation will consist of 80 distinguished leaders in education, science, engineering, and industry. Of those, 24 are life members and eight are ex officio. An additional 31 individuals are life members emeritus.

The 10 term members are:

Wes Bush, former chair and chief executive officer, Northrop Grumman Corporation

Bush has worked in the aerospace and defense industry since starting at COMSAT Labs under MIT’s co-op program. After graduation, he first worked at The Aerospace Corporation, then became a systems engineer at TRW’s Space Park facility in 1987. Prior to Northrop Grumman’s acquisition of TRW in 2002, he led numerous space program activities, served as vice president of TRW Ventures, and was the president and chief executive officer of TRW’s U.K.-based Aeronautical Systems business. At Northrop Grumman, Bush served as the president of the company’s space technology sector, then as its chief financial officer. He became president of the company in 2006, served as chief executive officer from 2010 through 2018, and became chairman in 2011.

Ruby R. Chandy ’82, SM ’89, CEO, Luminas Advisory Services

With 20 years of public company board experience, Chandy currently serves on the boards of Dupont, Thermo Fisher Scientific, and Flowserve. She is on the advisory board of Pritzker Private Capital and serves on boards of its portfolio companies. She was formerly president of the industrial division and a corporate officer at Pall Corporation, which was acquired by Danaher Corporation. Prior to Pall, she served as chief marketing officer at Dow Chemical, Rohm and Haas, and Thermo Fisher Scientific. She has extensive general management experience at Dow Chemical, Thermo Fisher Scientific, Boston Scientific, and Millipore. Chandy also currently serves on the Board of the NACD Philadelphia Chapter, the Board of Trustees for Cristo Rey Philadelphia High School, and the MIT Sloan Executive Board.

Hala Fadel MBA ’01, managing partner, Eurazeo

Fadel is a member of the management committee of Eurazeo and leads the investment committee of the growth equity team. Prior to joining Eurazeo in 2022, she built Comgest’s inaugural private growth equity program. She also spent nearly 15 years at Comgest as a portfolio manager within the European growth equities team, leading investments in technology, as well as in health care and consumer goods. From 2014 to 2022, she served as co-founder and managing partner of Leap Ventures, an early-stage technology venture capital firm that invests in Europe and the Middle East. While there, Fadel led several early-stage tech investments in France, Sweden, and the U.K. She started her career as an investment banker in mergers and acquisitions at Merrill Lynch in London.

Jacques Frederic Kerrest MBA ’09, vice chair and co-founder, Okta; managing partner and founder, Windproof Partners; senior advisor to Blackstone

As Okta’s chief operating officer from 2009 to 2023, Kerrest was responsible for Okta’s day-to-day operations, drove Okta’s corporate priorities, accelerated innovation across the company, worked closely with customers, partners and prospects, and served as a key liaison with the investor community. He oversaw corporate strategy, corporate development, strategic partnerships, and Okta’s social impact arm, Okta for Good. Previously, he worked in sales and business development at Salesforce.com, and in venture capital at Hummer Winblad Venture Partners. Kerrest also served as the chair and co-founder of Herophilus, a neurotherapeutics drug development company acquired by Genentech Roche. He is the author of “Zero to IPO,” a guidebook to building startups.

Michelle K. Lee ’88, SM ’89, CEO and founder, Obsidian Strategies, Inc.

Prior to founding Obsidian Strategies, Lee was vice president of the Machine Learning Solutions Lab at Amazon Web Services. She also served as the U.S. under secretary of commerce for intellectual property and director of the U.S. Patent and Trademark Office from 2015 to 2017 and was the first woman to serve in this role in the country’s history. Before entering public service, she served as an executive for eight years at Google. Lee also held the appointment of the Herman Phleger Visiting Professor of Law at Stanford University from 2017 to 2018. She began her career as a computer scientist at the MIT Artificial Intelligence Laboratory and Hewlett-Packard Research Laboratories.

Bianca Lepe PhD ’24, data scientist, City of Boston

Lepe’s PhD research focused on computationally guided vaccine design for tuberculosis and the development of a surface functionalization platform for M. tuberculosis to study host-pathogen interactions. As a Graduate Student Union member and REFS conflict coach, she supported fellow researchers, helped resolve conflicts, and represented student concerns. She also served as a student leader on the Graduate Student Council and the Corporation Joint Advisory Committee, where she facilitated dialogue on critical issues and advocated for people-centered solutions. Lepe has professional experience in technology policy consulting, venture capital, and biotech strategy. She recently joined the City of Boston’s analytics team as a data scientist, where she collaborates on projects to improve the city’s decision-making and operations.

Natalie M. Lorenz Anderson ’84, chief operations officer and board director, 247Solar, Inc.

Before joining 247Solar, an MIT startup commercializing a modular, scalable thermal energy solution, Lorenz Anderson was a partner at Booz Allen Hamilton, where she was a senior vice president and subject matter expert in cybersecurity, privacy, risk management, IT, and advanced technologies in the defense, national security, and civilian agency domains. She has served on several advisory and corporate boards with MIT roots, including Gigavation, Embr Labs, and Lutron, and is a former board member and current advisory board member for Ocean Power Technologies. Lorenz Anderson has also been a limited partner of Safar Partners LLC and is a former board director and vice president of the Girl Scouts Nations Capital Board.

Sebastian S. Man ’79, SM ’80, chair and chief executive officer, Chung Mei International Holdings Limited

Since 1990, Sebastian S. Man has helmed Chung Mei International Holdings Limited, which was co-founded in 1963 by his family and is a leading manufacturer of domestic kitchen electrics and air treatment products for major international brands. He is affiliated with several trade organizations, including as honorary vice president of the Hong Kong Electrical Appliance Manufacturers Association and a board director of the Pacific Basin Economic Council. He is also a council member with the Better Hong Kong Foundation and a member of the Vision 2047 Foundation. Man has been an executive committee member of the International Chamber of Commerce and the Hong Kong China Business Council. He is also an executive committee member of the Young Presidents’ Organization Gold HK and the North Asia Chair of the Chief Executive Organization.

Hyun-A C. Park ’83, MCP ’85, president, Spy Pond Partners, LLC

Park started her career working for MIT professor Tunney Lee at the Massachusetts Division of Capital Planning and Operations, and then worked on the Central Artery (“Big Dig”) project. From there, she went to Cambridge Systematics, where she was in charge of a business line focused on transportation asset management. Park recently chaired the Technical Activities Council of the Transportation Research Board, where she led a group of chairs that oversaw more than 200 committees and 6,000 volunteers on research activities related to all modes of transportation and a wide range of transportation topics. She also served as co-chair of the Women’s Transportation Seminar’s Public Art Project that resulted in the installation of a new public art piece at Boston’s South Station.  

Thomas Tull, co-chair, TWG Global

In addition to his role at TWG Global, Tull founded and chairs the United States Innovative Technology Fund, and is the founder, chair, and CEO of the private holding company Tulco, LLC. Previously, he founded and served as CEO of the media company Legendary Entertainment, which produced films like “The Dark Knight” trilogy, “Inception,” and “Jurassic World.” Tull is part of the ownership groups of the Pittsburgh Steelers and the New York Yankees, and he is deeply committed to philanthropy and advancing innovative solutions to global challenges through the Tull Family Foundation. He serves as an advisor to the chief innovation and strategy officer at MIT, is a member of the MIT School of Engineering Dean’s Advisory Council, and recently served as a Visiting Innovation Scholar at MIT.

The three new life members are:

Orit Gadiesh, partner and chair emeritus, Bain and Company Inc.

Gadiesh joined Bain and Company in 1977 and served as chair from 1993 to 2025. She is currently based at the group’s London headquarters and remains active in client and advisory work in North America, Europe, and Asia. She has counseled top-level management in structuring and managing portfolios, developing and implementing global strategy, designing both cost reduction and growth programs, embedding technologies in organizations, and more. Gadiesh currently serves on the World Economic Forum board of trustees, the International Business Leaders Advisory Council to the Mayor of Shanghai, and the board of governors at Tel Aviv University, as well as on the advisory boards of the James Martin 21st Century School of Oxford University and the Peres Institute for Peace and Innovation.

Jeff Halis ’76, SM ’76, president and CEO, Tyndall Management, LLC

Halis founded Tyndall Management, an investment firm specializing in publicly traded securities, in 1991. Prior to that, he held positions in the finance and investment industry working for Citibank, Merrill Lynch, and Sabre Associates. He is a former director of several publicly traded companies, including Enstar USA, Inc., KinderCare Learning Centers, and PriceSmart. His civic involvement included his membership on the state of New York’s financial control board, the investment committee of the New York State Common Retirement Fund, and the Citizen’s Budget Commission. He has also been on the boards of WNET, CaringKind, and Bridge Over Troubled Waters.

Alan Leventhal, former U.S. ambassador to the Kingdom of Denmark

Prior to his appointment as a United States ambassador from 2022 to 2025, Leventhal was the chair and chief executive officer of Beacon Capital Partners. He previously served as president and chief executive officer of Beacon Properties Corporation, a publicly traded real estate investment company that merged with Equity Office Properties in 1997. He is the former chair of the board of the Damon Runyon Cancer Research Foundation and also served on the executive committee. Leventhal is a trustee emeritus of Boston University, where he served as chair from 2004 to 2008. He also served as a life trustee of Northwestern University and on the boards of the Friends of Post Office Square and the Norman B. Leventhal Map and Education Center at the Boston Public Library.

Hank Green, prolific content creator and YouTuber whose work has often focused on science and STEM-oriented topics, is delivering today’s OneMIT Commencement address. Green, along with his brother John, has built the educational media company Complexly, racking up over 2 billion views for the their content, including the channels SciShow and CrashCourse. MIT News talked with Green in advance of his commencement remarks.

Q: MIT’s president, Sally Kornbluth, often talks about the value of curiosity. How much of curiosity do you think is natural, or alternately, how do you keep cultivating your sense of curiosity?

A: There’s a line in my talk today, something like, if I could attribute my success to anything besides luck, it is always believing that there is no better use of a day than learning something new. And I don’t know where that came from. I feel like everybody is like that. I have an 8-year-old son and he’s like that. My wife texted me last night and said, “He wants to know what dark matter is.” Well, wouldn’t we all?

I don’t know exactly know how to cultivate that, but I do have strategies for orienting [toward] that. … The reality is that it’s very easy to orient my curiosity toward what would make me the most money or what makes me feel better than other people. I’m very aware of this as founder and host of SciShow, that people might watch because they want to feel superior to people who don’t know stuff. And that’s a motivation, and at least it’s oriented toward knowing more stuff, but it’s not the best motivation. I think one of the great powers people can have is being able to orient your curiosity around what your values are, and how you’d like to see the world change. And that’s something that I have worked a lot on.

Q: It seems like you’re not just learning about new things, but also, in the process, aren’t there a lot of new challenges in figuring out how to communicate things best?

A: Tons! I mean the thing about it is that the communications landscape changes very fast. Five years ago, TikTok wasn’t really a thing. When I heard about it, I thought, “You can’t do science communication in a minute. That’s impossible. All you can do is dance videos.” And then I saw people doing it and said, “Well, you can.”

I’m also working on a book-length science communication project right now. When I say book-length, it’s a book about the biology of cancer. And that process, it doesn’t end there, but for me that’s the largest, longest communication you can do.

[But alternately] my friend Charlie made one of the first science TikToks I saw. It’s a skit about how vaccines work, where one character was a vaccine and one was an immune cell. That was probably 30 seconds long and it’s probably better than any way I would have communicated about vaccines in the midst of the Covid epidemic on the new platform, pre-bunking fear about vaccines from the very beginning, very simply explaining what they are in a way that’s very accessible and not going to turn anybody off.

Q: What are you talking about in your remarks today?

A: Yeah, I mean we are in a super-weird moment with regard to the amount of power humanity has. We’ve been in moments like this before, where the amount of power at our fingertips increases exponentially very quickly. The nuclear age is the big one in terms of the speed of that change. But it feels like biotechnology and AI and communications are all adding up to being a really big deal.

The thing I kept coming back to was — I didn’t put this in the talk, but it inspired the talk: Okay, so we had a period of time where humans powered the world through muscle. And now human muscle is not the [most] important part of how we build. Intelligence and dexterity are important, but in terms of calories expended, [that’s done] by machines. If we end up in a world where that [also] becomes more the case for intelligence, what do we still have a monopoly on? A lot of people would still answer that question with “Nothing,” I guess.

I think that’s really wrong. I think we’ll still have a near-monopoly on meaning, and what we mean to each other. So, what I wanted to get at is, all the stuff that we do, all the things that we build, at the root, the base, we do it for people in some way. It might be a playlist for your friend, or the Human Genome Project, but all of that, we’re doing for people. And so keeping [ourselves] oriented toward people, and not building around them as an obstacle but building for them, is the thing I’ve wanted to be focused on. 

Scientists at the McGovern Institute for Brain Research at MIT and the Broad Institute of MIT and Harvard have re-engineered a compact RNA-guided enzyme they found in bacteria into an efficient, programmable editor of human DNA. 

The protein they created, called NovaIscB, can be adapted to make precise changes to the genetic code, modulate the activity of specific genes, or carry out other editing tasks. Because its small size simplifies delivery to cells, NovaIscB’s developers say it is a promising candidate for developing gene therapies to treat or prevent disease.

The study was led by Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT who is also an investigator at the McGovern Institute and the Howard Hughes Medical Institute, and a core member of the Broad Institute. Zhang and his team reported their open-access work this month in the journal Nature Biotechnology.

NovaIscB is derived from a bacterial DNA cutter that belongs to a family of proteins called IscBs, which Zhang’s lab discovered in 2021. IscBs are a type of OMEGA system, the evolutionary ancestors to Cas9, which is part of the bacterial CRISPR system that Zhang and others have developed into powerful genome-editing tools. Like Cas9, IscB enzymes cut DNA at sites specified by an RNA guide. By reprogramming that guide, researchers can redirect the enzymes to target sequences of their choosing.

IscBs had caught the team’s attention not only because they share key features of CRISPR’s DNA-cutting Cas9, but also because they are a third of its size. That would be an advantage for potential gene therapies: compact tools are easier to deliver to cells, and with a small enzyme, researchers would have more flexibility to tinker, potentially adding new functionalities without creating tools that were too bulky for clinical use.

From their initial studies of IscBs, researchers in Zhang’s lab knew that some members of the family could cut DNA targets in human cells. None of the bacterial proteins worked well enough to be deployed therapeutically, however: the team would have to modify an IscB to ensure it could edit targets in human cells efficiently without disturbing the rest of the genome.

To begin that engineering process, Soumya Kannan, a graduate student in Zhang’s lab who is now a junior fellow at the Harvard Society of Fellows, and postdoc Shiyou Zhu first searched for an IscB that would make good starting point. They tested nearly 400 different IscB enzymes that can be found in bacteria. Ten were capable of editing DNA in human cells.

Even the most active of those would need to be enhanced to make it a useful genome editing tool. The challenge would be increasing the enzyme’s activity, but only at the sequences specified by its RNA guide. If the enzyme became more active, but indiscriminately so, it would cut DNA in unintended places. “The key is to balance the improvement of both activity and specificity at the same time,” explains Zhu.

Zhu notes that bacterial IscBs are directed to their target sequences by relatively short RNA guides, which makes it difficult to restrict the enzyme’s activity to a specific part of the genome. If an IscB could be engineered to accommodate a longer guide, it would be less likely to act on sequences beyond its intended target.

To optimize IscB for human genome editing, the team leveraged information that graduate student Han Altae-Tran, who is now a postdoc at the University of Washington, had learned about the diversity of bacterial IscBs and how they evolved. For instance, the researchers noted that IscBs that worked in human cells included a segment they called REC, which was absent in other IscBs. They suspected the enzyme might need that segment to interact with the DNA in human cells. When they took a closer look at the region, structural modeling suggested that by slightly expanding part of the protein, REC might also enable IscBs to recognize longer RNA guides.

Based on these observations, the team experimented with swapping in parts of REC domains from different IscBs and Cas9s, evaluating how each change impacted the protein’s function. Guided by their understanding of how IscBs and Cas9s interact with both DNA and their RNA guides, the researchers made additional changes, aiming to optimize both efficiency and specificity.

In the end, they generated a protein they called NovaIscB, which was over 100 times more active in human cells than the IscB they had started with, and that had demonstrated good specificity for its targets.

Kannan and Zhu constructed and screened hundreds of new IscBs before arriving at NovaIscB — and every change they made to the original protein was strategic. Their efforts were guided by their team’s knowledge of IscBs’s natural evolution, as well as predictions of how each alteration would impact the protein’s structure, made using an artificial intelligence tool called AlphaFold2. Compared to traditional methods of introducing random changes into a protein and screening for their effects, this rational engineering approach greatly accelerated the team’s ability to identify a protein with the features they were looking for.

The team demonstrated that NovaIscB is a good scaffold for a variety of genome editing tools. “It biochemically functions very similarly to Cas9, and that makes it easy to port over tools that were already optimized with the Cas9 scaffold,” Kannan says. With different modifications, the researchers used NovaIscB to replace specific letters of the DNA code in human cells and to change the activity of targeted genes.

Importantly, the NovaIscB-based tools are compact enough to be easily packaged inside a single adeno-associated virus (AAV) — the vector most commonly used to safely deliver gene therapy to patients. Because they are bulkier, tools developed using Cas9 can require a more complicated delivery strategy.

Demonstrating NovaIscB’s potential for therapeutic use, Zhang’s team created a tool called OMEGAoff that adds chemical markers to DNA to dial down the activity of specific genes. They programmed OMEGAoff to repress a gene involved in cholesterol regulation, then used AAV to deliver the system to the livers of mice, leading to lasting reductions in cholesterol levels in the animals’ blood.

The team expects that NovaIscB can be used to target genome editing tools to most human genes, and look forward to seeing how other labs deploy the new technology. They also hope others will adopt their evolution-guided approach to rational protein engineering. “Nature has such diversity, and its systems have different advantages and disadvantages,” Zhu says. “By learning about that natural diversity, we can make the systems we are trying to engineer better and better.”

This study was funded, in part, by the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT, Broad Institute Programmable Therapeutics Gift Donors, Pershing Square Foundation, William Ackman, Neri Oxman, the Phillips family, and J. and P. Poitras.

Sarah Alnegheimish’s research interests reside at the intersection of machine learning and systems engineering. Her objective: to make machine learning systems more accessible, transparent, and trustworthy.

Alnegheimish is a PhD student in Principal Research Scientist Kalyan Veeramachaneni’s Data-to-AI group in MIT’s Laboratory for Information and Decision Systems (LIDS). Here, she commits most of her energy to developing Orion, an open-source, user-friendly machine learning framework and time series library that is capable of detecting anomalies without supervision in large-scale industrial and operational settings.

Early influence 

The daughter of a university professor and a teacher educator, she learned from an early age that knowledge was meant to be shared freely. “I think growing up in a home where education was highly valued is part of why I want to make machine learning tools accessible.” Alnegheimish’s own personal experience with open-source resources only increased her motivation. “I learned to view accessibility as the key to adoption. To strive for impact, new technology needs to be accessed and assessed by those who need it. That’s the whole purpose of doing open-source development.”

Alnegheimish earned her bachelor’s degree at King Saud University (KSU). “I was in the first cohort of computer science majors. Before this program was created, the only other available major in computing was IT [information technology].” Being a part of the first cohort was exciting, but it brought its own unique challenges. “All of the faculty were teaching new material. Succeeding required an independent learning experience. That’s when I first time came across MIT OpenCourseWare: as a resource to teach myself.”

Shortly after graduating, Alnegheimish became a researcher at the King Abdulaziz City for Science and Technology (KACST), Saudi Arabia’s national lab. Through the Center for Complex Engineering Systems (CCES) at KACST and MIT, she began conducting research with Veeramachaneni. When she applied to MIT for graduate school, his research group was her top choice.

Creating Orion

Alnegheimish’s master thesis focused on time series anomaly detection — the identification of unexpected behaviors or patterns in data, which can provide users crucial information. For example, unusual patterns in network traffic data can be a sign of cybersecurity threats, abnormal sensor readings in heavy machinery can predict potential future failures, and monitoring patient vital signs can help reduce health complications. It was through her master’s research that Alnegheimish first began designing Orion.

Orion uses statistical and machine learning-based models that are continuously logged and maintained. Users do not need to be machine learning experts to utilize the code. They can analyze signals, compare anomaly detection methods, and investigate anomalies in an end-to-end program. The framework, code, and datasets are all open-sourced.

“With open source, accessibility and transparency are directly achieved. You have unrestricted access to the code, where you can investigate how the model works through understanding the code. We have increased transparency with Orion: We label every step in the model and present it to the user.” Alnegheimish says that this transparency helps enable users to begin trusting the model before they ultimately see for themselves how reliable it is.

“We’re trying to take all these machine learning algorithms and put them in one place so anyone can use our models off-the-shelf,” she says. “It’s not just for the sponsors that we work with at MIT. It’s being used by a lot of public users. They come to the library, install it, and run it on their data. It’s proving itself to be a great source for people to find some of the latest methods for anomaly detection.”

Repurposing models for anomaly detection

In her PhD, Alnegheimish is further exploring innovative ways to do anomaly detection using Orion. “When I first started my research, all machine-learning models needed to be trained from scratch on your data. Now we’re in a time where we can use pre-trained models,” she says. Working with pre-trained models saves time and computational costs. The challenge, though, is that time series anomaly detection is a brand-new task for them. “In their original sense, these models have been trained to forecast, but not to find anomalies,” Alnegheimish says. “We’re pushing their boundaries through prompt-engineering, without any additional training.”

Because these models already capture the patterns of time-series data, Alnegheimish believes they already have everything they need to enable them to detect anomalies. So far, her current results support this theory. They don’t surpass the success rate of models that are independently trained on specific data, but she believes they will one day.

Accessible design

Alnegheimish talks at length about the efforts she’s gone through to make Orion more accessible. “Before I came to MIT, I used to think that the crucial part of research was to develop the machine learning model itself or improve on its current state. With time, I realized that the only way you can make your research accessible and adaptable for others is to develop systems that make them accessible. During my graduate studies, I’ve taken the approach of developing my models and systems in tandem.”

The key element to her system development was finding the right abstractions to work with her models. These abstractions provide universal representation for all models with simplified components. “Any model will have a sequence of steps to go from raw input to desired output.  We’ve standardized the input and output, which allows the middle to be flexible and fluid. So far, all the models we’ve run have been able to retrofit into our abstractions.” The abstractions she uses have been stable and reliable for the last six years.

The value of simultaneously building systems and models can be seen in Alnegheimish’s work as a mentor. She had the opportunity to work with two master’s students earning their engineering degrees. “All I showed them was the system itself and the documentation of how to use it. Both students were able to develop their own models with the abstractions we’re conforming to. It reaffirmed that we’re taking the right path.”

Alnegheimish also investigated whether a large language model (LLM) could be used as a mediator between users and a system. The LLM agent she has implemented is able to connect to Orion without users needing to know the small details of how Orion works. “Think of ChatGPT. You have no idea what the model is behind it, but it’s very accessible to everyone.” For her software, users only know two commands: Fit and Detect. Fit allows users to train their model, while Detect enables them to detect anomalies.

“The ultimate goal of what I’ve tried to do is make AI more accessible to everyone,” she says. So far, Orion has reached over 120,000 downloads, and over a thousand users have marked the repository as one of their favorites on Github. “Traditionally, you used to measure the impact of research through citations and paper publications. Now you get real-time adoption through open source.”