MIT affiliates named 2024 Schmidt Sciences AI2050 Fellows

Five MIT faculty members and two additional alumni were recently named to the 2024 cohort of AI2050 Fellows. The honor is announced annually by Schmidt Sciences, Eric and Wendy Schmidt’s philanthropic initiative that aims to accelerate scientific innovation. 

Conceived and co-chaired by Eric Schmidt and James Manyika, AI2050 is a philanthropic initiative aimed at helping to solve hard problems in AI. Within their research, each fellow will contend with the central motivating question of AI2050: “It’s 2050. AI has turned out to be hugely beneficial to society. What happened? What are the most important problems we solved and the opportunities and possibilities we realized to ensure this outcome?”

This year’s MIT-affiliated AI2050 Fellows include:

David Autor, the Daniel (1972) and Gail Rubinfeld Professor in the MIT Department of Economics, and co-director of the MIT Shaping the Future of Work Initiative and the National Bureau of Economic Research’s Labor Studies Program, has been named a 2024 AI2050 senior fellow. His scholarship explores the labor-market impacts of technological change and globalization on job polarization, skill demands, earnings levels and inequality, and electoral outcomes. Autor’s AI2050 project will leverage real-time data on AI adoption to clarify how new tools interact with human capabilities in shaping employment and earnings. The work will provide an accessible framework for entrepreneurs, technologists, and policymakers seeking to understand, tangibly, how AI can complement human expertise. Autor has received numerous awards and honors, including a National Science Foundation CAREER Award, an Alfred P. Sloan Foundation Fellowship, an Andrew Carnegie Fellowship, and the Heinz 25th Special Recognition Award from the Heinz Family Foundation for his work “transforming our understanding of how globalization and technological change are impacting jobs and earning prospects for American workers.” In 2023, Autor was one of two researchers across all scientific fields selected as a NOMIS Distinguished Scientist.

Sara Beery, an assistant professor in the Department of Electronic Engineering and Computer Science (EECS) and a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL), has been named an early career fellow. Beery’s work focuses on building computer vision methods that enable global-scale environmental and biodiversity monitoring across data modalities and tackling real-world challenges, including strong spatiotemporal correlations, imperfect data quality, fine-grained categories, and long-tailed distributions. She collaborates with nongovernmental organizations and government agencies to deploy her methods worldwide and works toward increasing the diversity and accessibility of academic research in artificial intelligence through interdisciplinary capacity-building and education. Beery earned a BS in electrical engineering and mathematics from Seattle University and a PhD in computing and mathematical sciences from Caltech, where she was honored with the Amori Prize for her outstanding dissertation.

Gabriele Farina, an assistant professor in EECS and a principal investigator in the Laboratory for Information and Decision Systems (LIDS), has been named an early career fellow. Farina’s work lies at the intersection of artificial intelligence, computer science, operations research, and economics. Specifically, he focuses on learning and optimization methods for sequential decisio­­­n-making and convex-concave saddle point problems, with applications to equilibrium finding in games. Farina also studies computational game theory and recently served as co-author on a Science study about combining language models with strategic reasoning. He is a recipient of a NeurIPS Best Paper Award and was a Facebook Fellow in economics and computer science. His dissertation was recognized with the 2023 ACM SIGecom Doctoral Dissertation Award and one of the two 2023 ACM Dissertation Award Honorable Mentions, among others.

Marzyeh Ghassemi PhD ’17, an associate professor in EECS and the Institute for Medical Engineering and Science, principal investigator at CSAIL and LIDS, and affiliate of the Abdul Latif Jameel Clinic for Machine Learning in Health and the Institute for Data, Systems, and Society, has been named an early career fellow. Ghassemi’s research in the Healthy ML Group creates a rigorous quantitative framework in which to design, develop, and place ML models in a way that is robust and fair, focusing on health settings. Her contributions range from socially aware model construction to improving subgroup- and shift-robust learning methods to identifying important insights in model deployment scenarios that have implications in policy, health practice, and equity. Among other awards, Ghassemi has been named one of MIT Technology Review’s 35 Innovators Under 35; and has been awarded the 2018 Seth J. Teller Award, the 2023 MIT Prize for Open Data, a 2024 NSF CAREER Award, and the Google Research Scholar Award. She founded the nonprofit Association for Health, Inference and Learning (AHLI) and her work has been featured in popular press such as Forbes, Fortune, MIT News, and The Huffington Post.

Yoon Kim, an assistant professor in EECS and a principal investigator in CSAIL, has been named an early career fellow. Kim’s work straddles the intersection between natural language processing and machine learning, and touches upon efficient training and deployment of large-scale models, learning from small data, neuro-symbolic approaches, grounded language learning, and connections between computational and human language processing. Affiliated with CSAIL, Kim earned his PhD in computer science at Harvard University; his MS in data science from New York University; his MA in statistics from Columbia University; and his BA in both math and economics from Cornell University. 

Additional alumni Roger Grosse PhD ’14, a computer science associate professor at the University of Toronto, and David Rolnick ’12, PhD ’18, assistant professor at Mila-Quebec AI Institute, were also named senior and early career fellows, respectively.