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Manxi Wu is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of California, Berkeley. His research focuses on developing methods in game theory and multi-agent learning for optimization applications in urban systems. His work explores dynamic mechanisms for information market design, with studies on ride-hailing platforms and incentive mechanisms for efficient resource sharing in networks. He employs learning strategies in static Markov games and investigates decentralized multi-agent reinforcement learning algorithms that facilitate cooperative resource allocation. His expertise includes scalable algorithm development for electric vehicle deployment and game-theoretic analyses pertaining to tolling systems in California's transportation landscape. He has published multiple articles in reputable journals including Operations Research and IEEE Transactions on Automatic Control, contributing significantly to the fields of operations research and game theory applications.
University of California, Berkeley • Berkeley, CA
Previously held positions at Cornell University as Assistant Professor and at Google Research as a Visiting Research Scientist.
Cornell University • Ithaca, NY
Conducted research on operational designs in transportation systems.
The Mathematics Subject GRE is required for the Fall 2026 admissions cycle. General GRE is optional.