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Put AI to work
Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA
Cathy Wu

Cathy Wu
UC Berkeley

Website

Cathy Wu 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 computational tools for reliable and complex decision making in critical societal systems. Cathy will be joining MIT as an assistant professor in 2019. Cathy holds a PhD in EECS from UC Berkeley, where she was part of the Berkeley AI Research lab, DeepDrive, California PATH, and RISELab, and a BS and MEng in EECS from MIT.

Sessions

4:50pm-5:30pm Thursday, September 6, 2018
Reinforcement learning for mixed autonomy mobility
Implementing AI
 Location: Imperial B
Secondary topics:  Reinforcement Learning, Transportation and Logistics
Cathy Wu (UC Berkeley)
Using novel techniques in model-free deep reinforcement learning and control theory, Cathy Wu explores and quantifies the potential impact of a small fraction of automated vehicles on low-level traffic flow dynamics, such as congestion on a variety of important traffic contexts. Read more.