Haewon Jeong

CRML Affiliated Faculty

Assistant Professor, Electrical and Computer Engineering




Dr. Jeong’s research focuses on building provably reliable machine learning (ML) systems using tools from information theory and coding theory. As ML systems are getting bigger, faster, and impacting more people, their reliability is challenged on many fronts. My research adapts and reinvents information-theoretic concepts for the context of reliable large-scale ML. To build reliability in machine metrics (e.g., computation time, accuracy), she marries coding theory and systems research to develop large-scale distributed algorithms that are resilient to unreliable or malicious nodes. To build reliability in human metrics (e.g., fairness, accountability), she closely collaborates with social scientists to investigate the fundamental limits of fairness of ML algorithms and develop discrimination mitigation strategies that can be used in practical ML pipelines.


Haewon Jeong is an assistant professor of Electrical and Computer Engineering at the University of California Santa Barbara. She received the B.S. degree ('14) in Electrical Engineering from KAIST and the M.Sc. ('13) and Ph.D. ('14) degrees in Electrical and Computer Engineering from Carnegie Mellon University. From 2020 to 2022, she was a postdoctoral scholar at Harvard University. Her research interests include information theory, distributed computing, machine learning, and ethics of AI systems.