Stanford
Stanford Center for Computational Market Design

Research

The nature of markets has been fundamentally transformed by information technology. The path from demand for exchanges to creating a marketplace is now shorter than ever. At the same time, there is growing demand for marketplaces that address complex transactions, building on computational power. This technological evolution offers unprecedented control over market design, implementation, and operations.

The Stanford Center for Computational Market Design brings together an interdisciplinary team with expertise spanning algorithm design, economics, machine learning, and operations research, focused on tackling timely market challenges. It emphasizes an interdisciplinary approach, combining algorithms, economic theory, and empirical tools towards insightful market designs that consider operational intricacies and technological constraints. This includes understanding the source of market frictions and designing the rules of the market to increase efficiency, as well as simplifying and enhancing strategic considerations for different stakeholders.

Scholars of this center seek to address timely market design challenges. They bring extensive experience in shaping the design of marketplaces and platforms in various domains, including (among others) education, environment, health, labor, spectrum, and transportation.

Selected Recent Papers

  1. K. Leyton-Brown, P. Milgrom, N. Newman, I. Segal, Artificial Intelligence and Market Design: Lessons Learned from Radio Spectrum Reallocation, in New Directions in Market Design (Univ. of Chicago Press), 2026.
  2. A. E. Roth, Market Design and Maintenance, in New Directions in Market Design (Univ. of Chicago Press), 2026.
  3. B. A. Ferguson, P. Milgrom, Market Design for Surface Water, in New Directions in Market Design (Univ. of Chicago Press), 2026.
  4. A. AmaniHamedani, A. Aouad, A. Saberi, Adaptive Approximation Schemes for Matching Queues, ACM Symposium on Theory of Computing (STOC), 2025.
  5. M. Allman, I. Ashlagi, A. Saberi, S. H. Yu, From Signaling to Interviews in Random Matching Markets, ACM Symposium on Theory of Computing (STOC), 2025.
  6. M. Braverman, M. Derakhshan, T. Pollner, A. Saberi, D. Wajc, New Philosopher Inequalities for Online Bayesian Matching, via Pivotal Sampling, ACM-SIAM Symposium on Discrete Algorithms (SODA), 2025.
  7. A. Rubinstein, Z. Zhou, Quantum Communication Complexity of Classical Auctions, Innovations in Theoretical Computer Science Conference (ITCS), 2025.
  8. I. Ashlagi, J. Chen, M. Roghani, A. Saberi, Stable Matching with Interviews, Innovations in Theoretical Computer Science (ITCS), 2025.
  9. O. Barrientos, D. Freund, D. Saban, Online Matching and Market Imbalance, arXiv preprint, 2025.
  10. M.-F. Balcan, T. Sandholm, E. Vitercik, Generalization Guarantees for Multi-item Profit Maximization: Pricing, Auctions, and Randomized Mechanisms, Operations Research, 2025.
  11. N. Agarwal, C. Hodgson, P. Somaini, Choices and Outcomes in Assignment Mechanisms: The Allocation of Deceased Donor Kidneys, Econometrica, 2025.
  12. Z. Y. Kang, S. Vasserman, Robustness Measures for Welfare Analysis, American Economic Review, 2025.
  13. W. Guo, N. Haghtalab, K. Kandasamy, E. Vitercik, Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty, ACM Conference on Economics and Computation (EC), 2024.
  14. R. Gao, M. Roghani, A. Rubinstein, A. Saberi, Hardness of Approximate Sperner and Applications to Envy-Free Cake Cutting, IEEE Symposium on Foundations of Computer Science (FOCS), 2024.
  15. A. Hayderi, A. Saberi, E. Vitercik, A. Wikum, MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation, International Conference on Machine Learning (ICML), 2024.
  16. Y. Feng, R. Niazadeh, A. Saberi, Two-Stage Stochastic Matching and Pricing with Applications to Ride Hailing, Operations Research, 2024.
  17. Y. Feng, R. Niazadeh, A. Saberi, Near-Optimal Bayesian Online Assortment of Reusable Resources, Operations Research, 2024.
  18. T. Pollner, M. Roghani, A. Saberi, D. Wajc, Improved Online Contention Resolution for Matchings and Applications to the Gig Economy, Mathematics of Operations Research, 2024.
  19. C. H. Papadimitriou, T. Pollner, A. Saberi, D. Wajc, Online Stochastic Max-Weight Bipartite Matching: Beyond Prophet Inequalities, Mathematics of Operations Research, 2024.
  20. R. Jagadeesan, K. Vocke, Stability in Large Markets, Review of Economic Studies, 2024.
  21. G. Ramseyer, M. Goyal, A. Goel, D. Mazières, Augmenting Batch Exchanges with Constant Function Market Makers, ACM Conference on Economics and Computation (EC), 2024.
  22. R. Johari, H. Li, A. Murthy, G. Y. Weintraub, When Does Interference Matter? Decision-Making in Platform Experiments, arXiv preprint, 2024.
  23. Y. Wu, R. Johari, V. Syrgkanis, G. Y. Weintraub, Switchback Price Experiments with Forward-Looking Demand, arXiv preprint, 2024.
  24. A. Rubinstein, J. Zhao, Strategizing against No-Regret Learners in First-Price Auctions, ACM Conference on Economics and Computation (EC), 2024.
  25. N. Newman, K. Leyton-Brown, P. Milgrom, I. Segal, Incentive Auction Design Alternatives: A Simulation Study, Management Science, 2024.
  26. M. Olivares, D. Saban, G. Y. Weintraub, E. Lara, P. Zanocco, P. Moreno, Saving Millions in Government Procurement Through Data Science, INFORMS Journal on Applied Analytics, 2024.
  27. P. Agte, C. Allende, A. Kapor, C. Neilson, F. Ochoa, Search and Biased Beliefs in Education Markets, NBER Working Paper 32670, 2024.
  28. C. Allende, J. P. Atal, R. Carril, J. I. Cuesta, A. González-Lira, Drivers of Public Procurement Prices: Evidence from Pharmaceutical Markets, International Journal of Industrial Organization, 2024.
  29. J. S. Huh, E. Vitercik, K. Kandasamy, Bandit Profit-Maximization for Targeted Marketing, ACM Conference on Economics and Computation (EC), 2024.
  30. A. Graur, I. Lo, K. Mentzer, Overbooking with Priority-Respecting Reassignment, ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2023.
  31. N. Immorlica, J. D. Leshno, I. Lo, B. Lucier, Information Acquisition in Matching Markets: The Role of Price Discovery, Working Paper, 2023.
  32. M. Goyal, G. Ramseyer, A. Goel, D. Mazières, Finding the Right Curve: Optimal Design of Constant Function Market Makers, ACM Conference on Economics and Computation (EC), 2023.
  33. G. Ramseyer, A. Goel, D. Mazières, SPEEDEX: A Scalable, Parallelizable, and Economically Efficient Decentralized Exchange, USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2023.
  34. W. Dhaouadi, R. Johari, O. B. Page, G. Y. Weintraub, Price Experimentation and Interference, arXiv preprint arXiv:2310.17165, 2023.
  35. J. Choi, D. Saban, G. Y. Weintraub, The Design of Optimal Pay-as-Bid Procurement Mechanisms, Manufacturing & Service Operations Management, 2023.
  36. V. Manshadi, S. Rodilitz, D. Saban, A. Suresh, Redesigning VolunteerMatch’s Search Algorithm, SSRN Working Paper, 2023.