Manxi Wu

Name: 

Manxi Wu

Department: 

Institute of Data System and Society
Graduate Student

Bio: 

PhD of Social and Engineering System, MIT, 2017 June - Present
Master of Science in Transportation, MIT, 2015 Aug. - 2017 June
Bachelor of Science in Applied Mathematics, Peking University, 2011-2015

Research: 

My research interests are in the applications of game theory and network optimization to large-scale infrastructure networks that are prone to inefficiencies such as congestion and reliability failures. Currently, I am working on the design and analysis of game-theoretic algorithms for analyzing the welfare of commuters in transportation networks, when they face asymmetric (incomplete) information about the network state and travel demand. My work builds on the rigorous theory of optimal traffic assignment in transportation networks under symmetric information settings, and extends it to include the effects of heterogeneous information on commuters’ equilibrium route choices. I expect that my research will contribute to a class of learning algorithms in network games with incomplete information structure and can be used to generate useful predictions about network congestion when the network is prone to shocks.

Publications: 

Wu, Manxi, Jeffrey Liu, and Saurabh Amin. "Informational aspects in a class of Bayesian congestion games." American Control Conference (ACC), 2017. IEEE, 2017.
Xu, Xiaoyun, Yaping Zhao, Manxi Wu, Zihuan Zhou, Ying Ma, and Yanni Liu. "Stochastic customer order scheduling to minimize long-run expected order cycle time." Annals of Operations Research (2016): 1-24.
Xu, Xiaoyun, Yaping Zhao, Haidong Li, and Manxi Wu. "Stochastic customer order scheduling to maximize throughput." In 2015 IEEE International Conference on Automation Science and Engineering (CASE), pp. 665-670. IEEE, 2015.