Cathy Wu

Cathy Wu is the Class of 1954 Career Development Professor in the Department of Civil and Environmental Engineering (CE) at the Massachusetts Institute of Technology (MIT). Her research focuses on advancing machine learning and optimization for large-scale societal systems, with an emphasis on urban mobility and trustworthy decision-making in critical infrastructure. Wu's work explores the integration of automation into urban systems and develops computational tools for reliable decision-making. She is affiliated with the MIT Laboratory for Information and Decision Systems and the MIT Institute for Data, Systems, and Society. Her research spans interdisciplinary collaboration across transportation, computer science, and public policy.

Cathy Wu is a researcher specializing in machine learning, control, optimization, multi-agent systems, and intelligent transportation systems. Her work focuses on developing learning frameworks for mixed autonomy traffic, such as Flow, and applying reinforcement learning to stabilize traffic and reduce stop-and-go waves. She also explores eco-driving strategies, vehicular control, and combinatorial optimization through deep reinforcement learning. Wu's research includes benchmarking reinforcement learning in traffic scenarios and addressing challenges in mixed autonomy intersections. Her contributions span both theoretical and applied aspects of intelligent transportation systems, emphasizing the integration of control theory and machine learning for real-world impact.