My name is Peng Shi and I am the Robert R. Dockson Assistant Professor in Business Administration at the USC Marshall School of Business, in the Department of Data Science and Operations. I also serve as an Associate Editor for the journal Management Science, in the department of Revenue Management and Market Analytics.
I am interested in developing mathematical models and techniques that can significantly benefit society. My current focus is prediction and optimization in matching markets, which include systems that match students to schools, applicants to subsidized housing, and customers to service providers. Characteristics of these systems include heterogeneous supply and demand, potential strategic behavior of agents, and the inability of obtaining the desired allocation by only setting prices. My PhD thesis, "Prediction and optimization in school choice", was motivated by school choice in Boston, for which I proposed an assignment plans that was adopted in March 2013 (for news coverage, see Boston Globe 2012/10/27, NY Times 2013/3/13, and NY Times 2013/3/15). I am currently working on applying optimization to other matching markets, with applications in subsidized housing allocation, organ allocation, and online platforms.
Working Papers
The Welfare Effects of Selling Leads in a Two-Sided Marketplace. Updated 2024/08.
- An earlier version appeared in EC'24.
Eliminating Waste in Cadaveric Organ Allocation. (with Junxiong Yin). Updated 2022/11.
- An earlier version appeared in WINE 2022 and won the Best Paper Award.
- See Junxiong's PhD thesis "Patient Choice and Wastage in Cadaveric Kidney Allocation" for additional data analyses and simulations.
Journal Publications
Optimal Match Recommendations in Two-sided Marketplaces with Endogenous Prices. Management Science, Forthcoming. (Click here for the preprint on SSRN.)
- An earlier version appeared in EC'22.
- Download supplementary Python code here.
Optimal Matchmaking Strategy in Two-Sided Marketplaces. (Lead Article) Management Science, 69(3), 2023. (Click here for the preprint on SSRN.)
- Click here for a blog article at Management Science Review discussing the work along with commentaries by Fuhito Kojima, Federico Echenique and Peter Doe.
- An earlier version was titled "Efficient Matchmaking in Assignment Games with Application to Online Platforms," and appeared in EC'20.
Optimal Priority-Based Allocation Mechanisms. Management Science, 68(1), 2022. (Click here for the preprint on SSRN.)
- An earlier version was titled "Assortment Planning in School Choice."
- Download code and data here.
- Click here for a 26-minute presentation prepared for GCEC'20.
How Well Do Structural Demand Models Work? Counterfactual Predictions in School Choice (with Parag Pathak). Journal of Econometrics, 222(1A), 2021. (Click here for the preprint on SSRN. Click here for the Part I report.)
Design of Lotteries and Waitlists for Affordable Housing Allocation (with Nick Arnosti). (Lead Article) Management Science, 66(6), 2020. (Click here for the preprint on SSRN.)
- Click here for a blog article at Management Science Review discussing the work along with commentaries by Paul Milgrom, Mitchell Watt, and Martin Lariviere.
- Click here for an ORMS article highlighting the paper and summarizing the insights to a broader audience.
- An earlier version appeared in EC'17.
Clearing Matching Markets Efficiently: Informative Signals and Match Recommendations (with Itai Ashlagi, Mark Braverman, and Yash Kanoria). Management Science, 66(5), 2020. (Click here for the preprint on SSRN.)
- Part of a group of papers on matching markets that received the 2024 INFORMS Lanchester Prize for "the best contribution to operations research and the management sciences published in English in the past five years."
- An earlier version appeared in EC'17.
Optimal Allocation without Money: an Engineering Approach (with Itai Ashlagi). Management Science, 62(4), 2016. (Click here for the preprint on SSRN.)
- Won the 2017 MSOM SIG Best Paper Award.
- Won the 2014 MIT Operations Research Center Best Student Paper Competition.
- Won the 2013 INFORMS Public Sector OR Best Paper Competition.
- An earlier version appeared in EC'14.
Guiding School-Choice Reform through Novel Applications of Operations Research. Interfaces, 45(2), 2015.
- Won the 2013 INFORMS Doing Good with Good OR Best Paper Competition.
Improving Community Cohesion in School Choice via Correlated-Lottery Implementation (with Itai Ashlagi). Operations Research , 62(6), 2014.
Approximation algorithms for restless bandit problems (with Kamesh Munagala and Sudipto Guha). Journal of the ACM (JACM) , 58(1), 2010.
- An earlier version appeared in SODA'09.
Refereed Conference Proceedings
Prediction Mechanisms that Do Not Incentivize Undesirable Actions (with Vincent Conitzer and Mingyu Guo). Appeared in WINE'09.
The Stochastic Machine Replenishment Problem (with Kamesh Munagala). Appeared in IPCO'08.
Awards
- Part of a winning team for the 2024 INFORMS Frederick W. Lanchester Prize for "the best contribution to operations research and the management sciences published in English in the past five years."
- Robert R. Dockson Assistant Professor in Business Administration (2023).
- WINE 2022 Best Paper Award (18th Conference on Web and Internet Economics).
- 2021 Golden Apple Teaching Award for Best MSBA Core Instructor.
- 2020 MSOM Responsible Research in OM Award.
- 2019 DSO Department Excellence in Teaching Award.
- 2017 MSOM SIG Best Paper Award.
- 2017 ACM SIGecom Doctoral Dissertation Award.
- 1st place in the 2014 MIT ORC Best Student Paper Competition.
- 1st place in the 2013 INFORMS Public Sector Operations Research Best Paper Competition.
- 1st place in the 2013 INFORMS Doing Good with Good Operations Research Best Student Paper Competition.
- Silver Medals in the 2005 and 2006 International Mathematics Olympiad (IMO).
- Silver Medal in the 2006 International Olympiad of Informatics (IOI).
- 3rd place in North America in the 2005 USA Mathematics Olympiad (USAMO).
Teaching
USC Marshall School of Business:
- 2018-Present: Instructor for DSO 570 (The Analytics Edge: Data, Models, and Effective Decisions) for MSBA Students. See the most recent syllabus here.
MIT Sloan School of Management:
- Fall, 2013: Teaching assistant for 15.060 (Data, Models, and Decisions).
Duke University:
- Fall, 2009: Co-Instructor for Math149S (Problem Solving Seminar). See here for course materials I created.