Cathy Wu works at the intersection of machine learning, optimization, and large-scale urban systems and other societal systems. Her recent research focuses on mixed autonomy systems in mobility, which studies the complex integration of automation such as self-driving cars into existing urban systems. She is broadly interested in developing principled computational tools to enable reliable and complex decision-making for critical societal systems.

She received her B.S. and M.Eng in EECS at MIT in 2012 and 2013, and a Ph.D. in EECS at UC Berkeley in 2018. She has received numerous fellowship, best paper, and teaching awards. Throughout her career, Cathy has collaborated and worked broadly across fields, including transportation, computer science, electrical engineering, mechanical engineering, urban planning, and public policy, and institutions, including Microsoft Research, OpenAI, the Google X Self-Driving Car Team, AT&T, Caltrans, Facebook, and Dropbox. As the founder and Chair of the Interdisciplinary Research Initiative within the ACM Future of Computing Academy, she is actively building international programs to unlock the potential of interdisciplinary research in computing.

Research Interests:

– Reinforcement learning, machine learning
– Large-scale optimization
– Control theory, multi-agent systems
– Mobility, urban systems, societal systems
– Implications of AI & automation