Beery, Farina, Ghassemi, Kim named AI2050 Early Career Fellows

Four members of the Department of EECS were named to the 2024 cohort of AI2050 Fellows: Sara Beery, Gabriele Farina, Marzyeh Ghassemi, and Yoon Kim. The honor is announced annually by Schmidt Sciences, Eric and Wendy Schmidt’s philanthropic initiative that aims to accelerate scientific innovation.

Sara Beery is an Assistant Professor in EECS and a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL). 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 is an Assistant Professor in EECS and a principal investigator in the Laboratory for Information and Decision Systems (LIDS). 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 is an Associate Professor in the Department of EECS and the Institute for Medical Engineering and Science (IMES), and principal investigator at CSAIL and LIDS. She is also affiliated with the Jameel Clinic and with the Institute for Data, Systems, and Society (IDSS). 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 Tech 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 non-profit 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 is an Assistant Professor in EECS and a principal investigator in CSAIL. 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.

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?”