Jennifer Chayes

Jennifer Chayes is Dean of the College of Computing, Data Science, and Society and a Professor at the University of California, Berkeley, with appointments in Electrical Engineering and Computer Sciences, Mathematics, Statistics, and Information. She co-founded Microsoft Research New England, New York City, and Montreal, leading interdisciplinary research for 23 years before joining Berkeley in 2020. Previously, she was a Professor of Mathematics at UCLA, where she received the Distinguished Teaching Award.

• Education
  • PhD in Mathematical Physics (1983), Princeton University
  • BA in Biology and Physics (1979), Wesleyan University

Her research spans network science, machine learning, and theoretical computer science, focusing on phase transitions in networks, graphons for large-scale network modeling, and applications in cancer immunotherapy, ethical AI, and climate change. Her work on graph limits and exchangeable graphs has foundational implications for network analysis.

Recent publications highlight trends in sparse graph theory, privacy-preserving algorithms, and fairness in AI. Awards include the Anita Borg Institute Women of Vision Leadership Award (2012), SIAM John von Neumann Lecture Prize (2015), and ACM Distinguished Service Award (2020). She is a member of the National Academy of Sciences and a Fellow of multiple academic societies.

Chayes actively promotes Diversity in STEM and serves on advisory boards for institutions like MIT’s Schwarzman College of Computing, the Howard Hughes Medical Institute, and the National Science Foundation’s Institute for AI and Fundamental Interactions.