- UC Berkeley, EECS, Ph.D., 2018
- MIT, EECS, M.Eng., 2013
- MIT, EECS, B.S., 2012
Cathy works at the intersection of machine learning, optimization, and large-scale 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 interested in developing principled computational tools to enable reliable and complex decision-making for critical societal systems.
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.
Awards and Honors
- National Science Foundation (NSF) Faculty Early Career Development (CAREER) Award (2023)
- CUTC Milton Pikarsky Memorial Dissertation Award (2018)
- Outstanding Graduate Student Instructor Award, UC Berkeley (2018)
- ACM Future of Computing Academy, Interdisciplinary Research Initiative, Chair (2017)
- ITS Outstanding Graduate Student Award, UC Berkeley (2017)
- IEEE Best Paper Award, Intelligent Transportation Systems Conference (ITSC) (2016)
- Rising Stars Workshop (2016)
- Dwight David Eisenhower Graduate Fellowship (2015)
- National Defense Science and Engineering (NDSEG) Graduate Fellowship (2013)
- National Science Foundation (NSF) Graduate Fellowship, Fellow (2013)
- Chancellor’s Fellowship for Graduate Study, UC Berkeley (2013)
- C. Wu, A. Rajeswaran, Y. Duan, V. Kumar, A. Bayen, S. Kakade, I. Mordatch, P. Abbeel. “Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines.” International Conference on Learning Representations (ICLR), 2018. Oral (2%).
- C. Wu, A. Kreidieh, K. Parvate, E. Vinitsky, A. Bayen. “Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control.” arXiv 1710.05465, 2017.
- C. Wu, A. Kreidieh, E. Vinitsky, A. Bayen “Emergent Behaviors in Mixed-Autonomy Traffic.” Proceedings of the 1st Annual Conference on Robot Learning (CoRL), 2017.
- C. Wu, E. Kamar, E. Horvitz. “Clustering for Set Partitioning with a Case Study in Ridesharing.” IEEE Intelligent Transportation Systems Conference (ITSC), 2016. Best paper award.
- C. Wu, J. Thai, S. Yadlowsky, A. Pozdnoukhov, A. Bayen. “Cellpath: Fusion of Cellular and Traffic Sensor Data for Route Flow Estimation via Convex Optimization.” Transportation Research Part C: Methodological and 21st International Symposium on Transportation and Traffic Theory (ISTTT), 2015. Oral (14%).