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 Management Science.

My research investigates how to design systems that match individuals based on their preferences, addressing a fundamental question with far-reaching societal implications. Using tools from optimization, game theory, and empirical analysis, I develop mathematical models that characterize the design space, identify provably near-optimal solutions, and provide actionable guidance even with limited data. My work spans two complementary streams: matchmaking systems for scarce public resources (school choice, affordable housing, organ allocation) and two-sided digital marketplaces (studying platforms like Amazon, Angi, Google, and Yelp). My ongoing research continues in these core areas, while I'm also beginning to explore newer directions including data-driven accountability tools for the home services industry and how artificial intelligence might transform matching markets.

I earned my Ph.D. in Operations Research from MIT in 2016 under Itai Ashlagi, with a thesis on "Prediction and Optimization in School Choice." During my PhD, I helped design Boston Public Schools' new student assignment system adopted in 2013 (see Boston Globe, NY Times). I spent one year at Microsoft Research New England as a post-doctoral researcher.

Since joining USC Marshall in 2017, I've received the 2024 INFORMS Frederick W. Lanchester Prize for contributions to matching market design. My work appears in Management Science, Operations Research, and Journal of Econometrics. I aim to develop research that not only advances theory but also informs the design of systems that govern access to critical goods, services, and opportunities—contributing meaningfully to both academic literature and the platforms and policies that impact people's lives.

Working Papers

Welfare-Optimal Policies for Sponsored Advertising in a Two-Sided Marketplace. Submitted. Updated 2025/02.

  • To appear in EC'25. Journal submission under preparation.

The Welfare Effects of Selling Leads in a Two-Sided Marketplace. Major Revision at Management Science. Updated 2025/05.

  • An earlier version appeared in EC'24.

Eliminating Waste in Cadaveric Organ Allocation. (with Junxiong Yin). Updated 2022/10.

Journal Publications

Click here for my Google Scholar page.

Optimal Match Recommendations in Two-sided Marketplaces with Endogenous Prices. Management Science, Forthcoming, 2024. (Click here for the preprint on SSRN.)

Optimal Matchmaking Strategy in Two-Sided Marketplaces. (Lead Article) Management Science 69(3): 1323-1340, 2022. (Click here for the preprint on SSRN.)

Optimal Priority-Based Allocation Mechanisms. Management Science 68(1): 171-188, 2021. (Click here for the preprint on SSRN.)

How Well Do Structural Demand Models Work? Counterfactual Predictions in School Choice (with Parag Pathak). Journal of Econometrics 222(1A): 161-195, 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): 2291-2307, 2020. (Click here for the preprint on SSRN.)

Clearing Matching Markets Efficiently: Informative Signals and Match Recommendations (with Itai Ashlagi, Mark Braverman, and Yash Kanoria). Management Science 66(5): 2163-2193, 2019. (Click here for the preprint on SSRN.)

  • Shared 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): 1078-1097, 2015. (Click here for the preprint on SSRN.)

  • Won the 2020 MSOM Responsible Research in Operations Management Award.
  • 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): 117-132, 2015.

Improving Community Cohesion in School Choice via Correlated-Lottery Implementation (with Itai Ashlagi). Operations Research 62(6): 1247-1264, 2014.

Approximation algorithms for restless bandit problems (with Kamesh Munagala and Sudipto Guha). Journal of the ACM (JACM) 58(1), Article 3, 1-50, 2010.

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

  • Jagdish Sheth Impact on Practice Award, USC Marshall (2025).
  • Shared 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."
  • Golden Apple Teaching Award, USC Marshall (2025 and 2021).
  • Robert R. Dockson Assistant Professor in Business Administration (2023).
  • Best Paper, Conference on Web and Internet Economics (WINE 2022).
  • Responsible Research in OM Award, MSOM Society (2020).
  • Excellence in Teaching Award, DSO Department (2019).
  • Service Management SIG Best Paper, MSOM Society (2017).
  • ACM SIGecom Doctoral Dissertation Award (2017).
  • Best Student Paper, MIT ORC (2014).
  • Public Sector OR Best Paper, INFORMS (2013).
  • Doing Good with Good OR Best Student Paper, INFORMS (2013).
  • Silver Medal in the 2006 International Olympiad of Informatics (IOI).
  • Silver Medals in the 2005 and 2006 International Mathematics Olympiad (IMO).
  • 3rd place in North America in the 2005 USA Mathematics Olympiad (USAMO).

Teaching

USC Marshall School of Business:

  • 2025-Present: Instructor for DSO-577 (Optimization Modeling for Prescriptive Analytics). Elective for the MSBA program.
  • 2025-Present: Instructor for DSO-576 (Algorithmic Thinking with Python). Core course in the MSBA program.
  • 2017-2024: Instructor for DSO-570 (The Analytics Edge: Data, Models, and Effective Decisions) for MSBA Students. See the most recent syllabus here.
  • 2019-2021: Instructor for DSO-599 (Introduction to Python for Business Analytics). Course introduces Python programming to MBA students.

MIT Sloan School of Management:

Duke University: