Peng Shi

Assistant Professor of Data Sciences and Operations
Room / Office
Peng is interested in developing quantitative methodologies for the betterment of society. His current research focuses on optimization in matching markets, with applications in school choice, public housing, and two-sided marketplaces. His research on school choice has won multiple awards, including the MSOM Responsible Research in OM Award, ACM SIGecom Doctoral Dissertation Award, the INFORMS Public Sector Operations Best Paper Competition, and the INFORMS Doing Good with Good Operations OR Student Paper Competition. Prior to joining USC, he completed a PhD in operations research at MIT, and was a post-doctoral researcher at Microsoft Research.
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Parag Pathak, Peng Shi () "How well do structural demand models Work? Counterfactual predictions in school choice ,"  Journal of Econometrics  222, 161-195.
Peng Shi () "Optimal Priority-Based Allocation Mechanisms ,"  Management Science,
Nick Arnosti, Peng Shi () "Design of Lotteries and Waitlists for Affordable Housing Allocation ,"  Management Science  66, 2291-2799.
Itai Ashlagi, Mark Braverman, Yash Kanoria, Peng Shi () "Clearing Matching Markets Efficiently: Informative Signals and Match Recommendations ,"  Management Science  66, 1783-2290, iii-iv.
Peng Shi () "Guiding school-choice reform through novel applications of operations research ,"  Interfaces  45, 117--132.
Itai Ashlagi, Peng Shi () "Optimal allocation without money: An engineering approach ,"  Management Science  62, 1078--1097.
Itai Ashlagi, Peng Shi () "Improving community cohesion in school choice via correlated-lottery implementation ,"  Operations Research  62, 1247--1264.
Sudipto Guha, Kamesh Munagala, Peng Shi () "Approximation algorithms for restless bandit problems ,"  Journal of the ACM (JACM)  58, 3.
Peng Shi, Vincent Conitzer, Mingyu Guo () "Prediction mechanisms that do not incentivize undesirable actions ,"  International Workshop on Internet and Network Economics, 89--100.
Kamesh Munagala, Peng Shi () "The stochastic machine replenishment problem ,"  International Conference on Integer Programming and Combinatorial Optimization, 169--183.