Professor Emeritus Stanley Fischer, a towering figure in academic macroeconomics and global economic policymaking, dies at 81

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.

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Study shows making hydrogen with soda cans and seawater is scalable and sustainable

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.

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Teaching AI models what they don’t know

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.”

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Teaching AI models the broad strokes to sketch more like humans do

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.

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Eight with MIT ties win 2025 Hertz Foundation Fellowships

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.

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3 Questions: How to help students recognize potential bias in their AI datasets

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.

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Chancellor Melissa Nobles’ address to MIT’s undergraduate Class of 2025

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!

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Mary Robinson urges MIT School of Architecture and Planning graduates to “find a way to lead”

“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.”

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Hank Green urges the Class of 2025 to work on “everyday solvable problems of normal people”

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.” 

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Commencement address by Hank Green

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.

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3 Questions: Hank Green on science, communication, and curiosity

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. 

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MIT mechanical engineering course invites students to “build with biology”

MIT course 2.797/2.798 (Molecular Cellular and Tissue Biomechanics) teaches students about the role that mechanics plays in biology, with a focus on biomechanics and mechanobiology: “Two words that sound similar, but are actually very different,” says Ritu Raman, the Eugene Bell Career Development Professor of Tissue Engineering in the MIT Department of Mechanical Engineering.

Biomechanics, Raman explains, conveys the mechanical properties of biological materials, where mechanobiology teaches students how cells feel and respond to forces in their environment. “When students take this class, they're getting a really unique fusion of not only fundamentals of mechanics, but also emerging research in biomechanics and mechanobiology,” says Raman.

Raman and Peter So, professor of mechanical engineering, co-teach the course, which So says offers a concrete application of some of the basic theory. “We talk about some of the applications and why the fundamental concept is important.”

The pair recently revamped the curriculum to incorporate hands-on lab-learning through the campus BioMakers space and the Safety, Health, Environmental Discovery Lab (SHED) bioprinting makerspace. This updated approach invites students to “build with biology” and see how cells respond to forces in their environment in real time, and it was a change that was seemingly welcomed from the start, with the first offering yielding the course’s largest-ever enrollment.

“Many concepts in biomechanics and mechanobiology can be hard to conceptualize because they happen at length scales that we can't typically visualize,” Raman explains. “In the past, we've done our best to convey these ideas via pictures, videos, and equations. The lab component adds another dimension to our teaching methods. We hope that students seeing firsthand how living cells sense and respond to their environment helps the concepts sink in deeper and last longer in their memories.”

Makerspaces, which are located throughout the campus, offer tools and workspace for MIT community members to invent, prototype, and bring ideas to life. The Institute has over 40 design/build/project spaces that include facilities for 3D printing, glassblowing, wood and metal working, and more. The BioMakers space welcomes students engaged in hands-on bioengineering projects. SHED similarly leverages cutting-edge technologies across disciplines, including a new space focused on 3D bio-printing.

Kamakshi Subramanian, a cross-registered Wellesley College student, says she encountered a polymer model in a prior thermodynamics class, but wondered how she’d apply it. Taking this course gave her a new frame of reference. “I was like, ‘Why are we doing this?’ … and then I came here and I was like, ‘OK, thinking about entropy in this way is actually useful.’”

Raman says there’s a special kind of energy and excitement associated with being in a lab versus staying in the classroom. “It reminds me of going on a field trip when I was in elementary school,” she says, adding that seeing that energy in students during the course’s first run inspired the instructors to expand lab offerings even further in the second offering.  

“[In addition to] one main lab on the biomechanics of muscle contraction, we have added a second lab where students visit the SHED makerspace to learn about 3D bio-printing,” she says. “We have also incorporated an optional hands-on component into the final project, [and] most students in the class are taking advantage of this extra lab time to try exciting curiosity-driven experiments at the intersection of biology and mechanics.”

Raman and So, who were joined in teaching the second iteration of the course this semester by professor of biological engineering Mark Bathe, say they hope to continue to build the amount of hands-on time incorporated into the class in the coming years.

Ayi Agboglo, a Harvard-MIT Health Sciences and Technology graduate student who is studying the physical properties of red blood cells relevant to sickle cell disease (SCD), says taking the course introduced him to studies where mathematical models extracted mechanical properties of red blood cell (RBC) membranes in the context of SCD.

“In SCD, deoxygenation causes rigid protein fibers to form within cells, altering their mechanical and physical properties,” he explains. “This field of work has largely informed my research which focuses on measuring the physical properties of RBCs (mass, volume, and density) in both oxygenated and deoxygenated states. These measurements aim to reveal patient-specific differences in fiber formation — the primary pathological event in SCD — potentially uncovering new therapeutic opportunities.”

Agboglo, who works in Professor Cullen Buie’s lab at MIT and John Higgins’ lab at MGH, says, “I left [the class] not only understanding more about molecular mechanics, but also understanding just fundamentals about thermodynamics and energy and things that I think will be useful as a scientist in general.”

In addition to lab and lecture time, 2.797/2.798 students also had the opportunity to work with the Museum of Science, Boston and generate open-source educational resources about the interplay between mechanics and biology. These resources are now available on the museum's website. 

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A high-fat diet sets off metabolic dysfunction in cells, leading to weight gain

Consuming a high-fat diet can lead to a variety of health problems — not only weight gain but also an increased risk of diabetes and other chronic diseases.

At the cellular level, hundreds of changes take place in response to a high-fat diet. MIT researchers have now mapped out some of those changes, with a focus on metabolic enzyme dysregulation that is associated with weight gain.

Their study, conducted in mice, revealed that hundreds of enzymes involved in sugar, lipid, and protein metabolism are affected by a high-fat diet, and that these disruptions lead to an increase in insulin resistance and an accumulation of damaging molecules called reactive oxygen species. These effects were more pronounced in males than females.

The researchers also showed that most of the damage could be reversed by giving the mice an antioxidant along with their high-fat diet.

“Under metabolic stress conditions, enzymes can be affected to produce a more harmful state than what was initially there,” says Tigist Tamir, a former MIT postdoc. “Then what we’ve shown with the antioxidant study is that you can bring them to a different state that is less dysfunctional.”

Tamir, who is now an assistant professor of biochemistry and biophysics at the University of North Carolina at Chapel Hill School of Medicine, is the lead author of the new study, which appears today in Molecular Cell. Forest White, the Ned C. and Janet C. Rice Professor of Biological Engineering and a member of the Koch Institute for Integrative Cancer Research at MIT, is the senior author of the paper.

Metabolic networks

In previous work, White’s lab has found that a high-fat diet stimulates cells to turn on many of the same signaling pathways that are linked to chronic stress. In the new study, the researchers wanted to explore the role of enzyme phosphorylation in those responses.

Phosphorylation, or the addition of a phosphate group, can turn enzyme activity on or off. This process, which is controlled by enzymes called kinases, gives cells a way to quickly respond to environmental conditions by fine-tuning the activity of existing enzymes within the cell.

Many enzymes involved in metabolism — the conversion of food into the building blocks of key molecules such as proteins, lipids, and nucleic acids — are known to undergo phosphorylation.

The researchers began by analyzing databases of human enzymes that can be phosphorylated, focusing on enzymes involved in metabolism. They found that many of the metabolic enzymes that undergo phosphorylation belong to a class called oxidoreductases, which transfer electrons from one molecule to another. Such enzymes are key to metabolic reactions such as glycolysis — the breakdown of glucose into a smaller molecule known as pyruvate.

Among the hundreds of enzymes the researchers identified are IDH1, which is involved in breaking down sugar to generate energy, and AKR1C1, which is required for metabolizing fatty acids. The researchers also found that many phosphorylated enzymes are important for the management of reactive oxygen species, which are necessary for many cell functions but can be harmful if too many of them accumulate in a cell.

Phosphorylation of these enzymes can lead them to become either more or less active, as they work together to respond to the intake of food. Most of the metabolic enzymes identified in this study are phosphorylated on sites found in regions of the enzyme that are important for binding to the molecules that they act upon or for forming dimers — pairs of proteins that join together to form a functional enzyme.

“Tigist’s work has really shown categorically the importance of phosphorylation in controlling the flux through metabolic networks. It’s fundamental knowledge that emerges from this systemic study that she’s done, and it’s something that is not classically captured in the biochemistry textbooks,” White says.

Out of balance

To explore these effects in an animal model, the researchers compared two groups of mice, one that received a high-fat diet and one that consumed a normal diet. They found that overall, phosphorylation of metabolic enzymes led to a dysfunctional state in which cells were in redox imbalance, meaning that their cells were producing more reactive oxygen species than they could neutralize. These mice also became overweight and developed insulin resistance.

“In the context of continued high fat diet, what we see is a gradual drift away from redox homeostasis towards a more disease-like setting,” White says.

These effects were much more pronounced in male mice than female mice. Female mice were better able to compensate for the high fat diet by activating pathways involved in processing fat and metabolizing it for other uses, the researchers found.

“One of the things we learned is that the overall systemic effect of these phosphorylation events led to, especially in males, an increased imbalance in redox homeostasis. They were expressing a lot more stress and a lot more of the metabolic dysfunction phenotype compared to females,” Tamir says.

The researchers also found that if they gave mice who were on a high-fat diet an antioxidant called BHA, many of these effects were reversed. These mice showed a significant decrease in weight gain and did not become prediabetic, unlike the other mice fed a high-fat diet.

It appears that the antioxidant treatment leads cells back into a more balanced state, with fewer reactive oxygen species, the researchers say. Additionally, metabolic enzymes showed a systemic rewiring and changed state of phosphorylation in those mice.

“They’re experiencing a lot of metabolic dysfunction, but if you co-administer something that counters that, then they have enough reserve to maintain some sort of normalcy,” Tamir says. “The study suggests that there is something biochemically happening in cells to bring them to a different state — not a normal state, just a different state in which now, at the tissue and organism levels, the mice are healthier.”

In her new lab at the University of North Carolina, Tamir now plans to further explore whether antioxidant treatment could be an effective way to prevent or treat obesity-associated metabolic dysfunction, and what the optimal timing of such a treatment would be.

The research was funded in part by the Burroughs Wellcome Fund, the National Cancer Institute, the National Institutes of Health, the Ludwig Center at MIT, and the MIT Center for Precision Cancer Medicine.

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$20 million gift supports theoretical physics research and education at MIT

A $20 million gift from the Leinweber Foundation, in addition to a $5 million commitment from the MIT School of Science, will support theoretical physics research and education at MIT.

Leinweber Foundation gifts to five institutions, totaling $90 million, will establish the newly renamed MIT Center for Theoretical Physics – A Leinweber Institute within the Department of Physics, affiliated with the Laboratory for Nuclear Science at the School of Science, as well as Leinweber Institutes for Theoretical Physics at three other top research universities: the University of Michigan, the University of California at Berkeley, and the University of Chicago, as well as a Leinweber Forum for Theoretical and Quantum Physics at the Institute for Advanced Study.

“MIT has one of the strongest and broadest theory groups in the world,” says Professor Washington Taylor, the director of the newly funded center and a leading researcher in string theory and its connection to observable particle physics and cosmology.

“This landmark endowment from the Leinweber Foundation will enable us to support the best graduate students and postdoctoral researchers to develop their own independent research programs and to connect with other researchers in the Leinweber Institute network. By pledging to support this network and fundamental curiosity-driven science, Larry Leinweber and his family foundation have made a huge contribution to maintaining a thriving scientific enterprise in the United States in perpetuity.”

The Leinweber Foundation’s investment across five institutions — constituting the largest philanthropic commitment ever for theoretical physics research, according to the Science Philanthropy Alliance, a nonprofit organization that supports philanthropic support for science — will strengthen existing programs at each institution and foster collaboration across the universities. Recipient institutions will work both independently and collaboratively to explore foundational questions in theoretical physics. Each institute will continue to shape its own research focus and programs, while also committing to big-picture cross-institutional convenings around topics of shared interest. Moreover, each institute will have significantly more funding for graduate students and postdocs, including fellowship support for three to eight fully endowed Leinweber Physics Fellows at each institute.

“This gift is a commitment to America’s scientific future,” says Larry Leinweber, founder and president of the Leinweber Foundation. “Theoretical physics may seem abstract to many, but it is the tip of the spear for innovation. It fuels our understanding of how the world works and opens the door to new technologies that can shape society for generations. As someone who has had a lifelong fascination with theoretical physics, I hope this investment not only strengthens U.S. leadership in basic science, but also inspires curiosity, creativity, and groundbreaking discoveries for generations to come.”

The gift to MIT will create a postdoc program that, once fully funded, will initially provide support for up to six postdocs, with two selected per year for a three-year program. In addition, the gift will provide student financial support, including fellowship support, for up to six graduate students per year studying theoretical physics. The goal is to attract the top talent to the MIT Center for Theoretical Physics – A Leinweber Institute and support the ongoing research programs in a more robust way.

A portion of the funding will also provide support for visitors, seminars, and other scholarly activities of current postdocs, faculty, and students in theoretical physics, as well as helping with administrative support.

“Graduate students are the heart of our country’s scientific research programs. Support for their education to become the future leaders of the field is essential for the advancement of the discipline,” says Nergis Mavalvala, dean of the MIT School of Science and the Curtis (1963) and Kathleen Marble Professor of Astrophysics.

The Leinweber Foundation gift is the second significant gift for the center. “We are always grateful to Virgil Elings, whose generous gift helped make possible the space that houses the center,” says Deepto Chakrabarty, head of the Department of Physics. Elings PhD ’66, co-founder of Digital Instruments, which designed and sold scanning probe microscopes, made his gift more than 20 years ago to support a space for theoretical physicists to collaborate.

“Gifts like those from Larry Leinweber and Virgil Elings are critical, especially now in this time of uncertain funding from the federal government for support of fundamental scientific research carried out by our nation’s leading postdocs, research scientists, faculty and students,” adds Mavalvala.

Professor Tracy Slatyer, whose work is motivated by questions of fundamental particle physics — particularly the nature and interactions of dark matter — will be the subsequent director of the MIT Center for Theoretical Physics – A Leinweber Institute beginning this fall. Slatyer will join Mavalvala, Taylor, Chakrabarty, and the entirety of the theoretical physics community for a dedication ceremony planned for the near future.

The Leinweber Foundation was founded in 2015 by software entrepreneur Larry Leinweber, and has worked with the Science Philanthropy Alliance since 2021 to shape its philanthropic strategy. “It’s been a true pleasure to work with Larry and the Leinweber family over the past four years and to see their vision take shape,” says France Córdova, president of the Science Philanthropy Alliance. “Throughout his life, Larry has exemplified curiosity, intellectual openness, and a deep commitment to learning. This gift reflects those values, ensuring that generations of scientists will have the freedom to explore, to question, and to pursue ideas that could change how we understand the universe.”

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MIT D-Lab students design global energy solutions through collaboration

This semester, MIT D-Lab students built prototype solutions to help farmers in Afghanistan, people living in informal settlements in Argentina, and rural poultry farmers in Cameroon. The projects span continents and collectively stand to improve thousands of lives — and they all trace back to two longstanding MIT D-Lab classes.

For nearly two decades, 2.651 / EC.711 (Introduction to Energy in Global Development) and 2.652 / EC.712 (Applications of Energy in Global Development) have paired students with international organizations and communities to learn D-Lab’s participatory approach to design and study energy technologies in low-resource environments. Hundreds of students from across MIT have taken the courses, which feature visits from partners and trips to the communities after the semester. They often discover a passion for helping people in low-resource settings that lasts a lifetime.

“Through the trips, students often gain an appreciation for what they have at home, and they can’t forget about what they see,” says D-Lab instructor Josh Maldonado ’23, who took both courses as a student. “For me, it changed my entire career. Students maintain relationships with the people they work with. They stay on the group chats with community members and meet up with them when they travel. They come back and want to mentor for the class. You can just see it has a lasting effect.”

The introductory course takes place each spring and is followed by summer trips for students. The applications class, which is more focused on specific projects, is held in the fall and followed by student travel over winter break.

“MIT has always advocated for going out and impacting the world,” Maldonado says. “The fact that we can use what we learn here in such a meaningful way while still a student is awesome. It gets back to MIT’s motto, ‘mens et manus’ (‘mind and hand’).”

Curriculum for impact

Introduction to Energy in Global Development has been taught since around 2008, with past projects focusing on mitigating the effects of aquatic weeds for fisherman in Ghana, making charcoal for cookstoves in Uganda, and creating brick evaporative coolers to extend the shelf life of fruits and vegetables in Mali.

The class follows MIT D-Lab’s participatory design philosophy in which students design solutions in close collaboration with local communities. Along the way, students learn about different energy technologies and how they might be implemented cheaply in rural communities that lack basic infrastructure.

“In product design, the idea is to get out and meet your customer where they are,” Maldonado explains. “The problem is our partners are often in remote, low-resource regions of the world. We put a big emphasis on designing with the local communities and increasing their creative capacity building to show them they can build solutions themselves.”

Students from across MIT, including graduates and undergraduates, along with students from Harvard University and Wellesley College, can enroll in both courses. MIT senior Kanokwan Tungkitkancharoen took the introductory class this spring.

“There are students from chemistry, computer science, civil engineering, policy, and more,” says Tungkitkancharoen. “I think that convergence models how things get done in real life. The class also taught me how to communicate the same information in different ways to cater to different people. It helped me distill my approach to what is this person trying to learn and how can I convey that information.”

Tungkitkancharoen’s team worked with a nonprofit called Weatherizers Without Borders to implement weatherization strategies that enhance housing conditions and environmental resilience for people in the southern Argentinian community of Bariloche.

The team built model homes and used heat sensing cameras to show the impact of weatherization strategies to locals and policymakers in the region.

“Our partners live in self-built homes, but the region is notorious for being very cold in the winter and very hot in the summer,” Tungkitkancharoen says. “We’re helping our partners retrofit homes so they can withstand the weather better. Before the semester, I was interested in working directly with people impacted by these technologies and the current climate situation. D-Lab helped me work with people on the ground, and I’ve been super grateful to our community partners.”

The project to design micro-irrigation systems to support agricultural productivity and water conservation in Afghanistan is in partnership with the Ecology and Conservation Organization of Afghanistan and a team from a local university in Afghanistan.

“I love the process of coming into class with a practical question you need to solve and working closely with community partners,” says MIT master’s student Khadija Ghanizada, who has served as a teacher’s assistant for both the introductory and applications courses. “All of these projects will have a huge impact, but being from Afghanistan, I know this will make a difference because it’s a land-locked country, it’s dealing with droughts, and 80 percent of our economy depends on agriculture. We also make sure students are thinking about scalability of their solutions, whether scaling worldwide or just nationally. Every project has its own impact story.”

Meeting community partners

Now that the spring semester is over, many students from the introductory class will travel to the regions they studied with instructors and local guides over the summer.

“The traveling and implementation are things students always look forward to,” Maldonado says. “Students do a lot of prep work, thinking about the tools they need, the local resources they need, and working with partners to acquire those resources.”

Following travel, students write a report on how the trip went, which helps D-Lab refine the course for next semester.

“Oftentimes instructors are also doing research in these regions while they teach the class,” Maldonado says. “To be taught by people who were just in the field two weeks before the class started, and to see pictures of what they’re doing, is really powerful.”

Students who have taken the class have gone on to careers in international development, nonprofits, and to start companies that grow the impact of their class projects. But the most immediate impact can be seen in the communities that students work with.

“These solutions should be able to be built locally, sourced locally, and potentially also lead to the creation of localized markets based around the technology,” Maldonado says. “Almost everything the D-Lab does is open-sourced, so when we go to these communities, we don’t just teach people how to use these solutions, we teach them how to make them. Technology, if implemented correctly by mindful engineers and scientists, can be highly adopted and can grow a community of makers and fabricators and local businesses.”

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