Hongyao Ma
I am an assistant professor in the Decision Risk and Operations division at Columbia Business School. I was a Linde postdoctoral scholar at Caltech in June 2020, and a postdoctoral research scientist at Uber from 2019 to 2020.
I completed my PhD in Computer Science at Harvard University in 2019, advised by David C. Parkes. I received my MS in 2014 at Harvard, and BE in 2012 at Xi'an Jiaotong University, both in Electrical Engineering.
My research is broadly situated at the interface of computer science, economics, and operations. I am particularly interested in designing incentive-aligned systems to bring people together in useful ways, in the presence of uncertainty, self-interest, and autonomy. The ACM SIGecom Dissertation Award Talk at EC'20 provides a high-level introduction to my main research interests.
Curriculum vitae (updated October 2024).
Working Papers
Yu, C., Ma, H., Iterative Network Pricing for Ridesharing Platforms. [arXiv][pdf]
NBER Market Design Working Group Meeting, Fall 2024
Castro, F., Ma, H., Nazerzadeh, H. and Yan, C., Randomized FIFO Mechanisms. [arXiv][pdf][short talk]
Preliminary version in Proceedings of the 23rd ACM Conference on Economics and Computation (EC'22). pp.60-60. [EC22]
NBER Market Design Working Group Meeting, Fall 2021
Sirolly, A., Ma, H., Kanoria, Y., The Impact of Race-Blind and Test-Optional Admissions on Racial Diversity and Merit. [SSRN]
Preliminary version in Proceedings of the 25th ACM Conference on Economics and Computation (EC'24).
Castro, F., Frazier, P., Ma, H., Nazerzadeh, H. and Yan, C., Matching Queues, Flexibility and Incentives. [arXiv][pdf]
Berger, B., Ma, H., Parkes D.C., Sekar, S.. Optimal Subscription Pricing Design for Ridesharing Platforms. [pdf]
Publications
Yu, C., Ma, H., and Wierman, A., Price Cycles in Ridesharing Platforms. In Procedings of the 10th Conference on Web and Internet Economics (WINE 2023). pp. 618-636. [arXiv][pdf][WINE 2023]
Ma, H., Fang, F. & Parkes, D.C., Spatio-Temporal Pricing for Ridesharing Platforms. Operations Research, 2022. [arXiv] [pdf][EC19 Talk]
Preliminary version in Proceedings of the 20th ACM Conference on Economics and Computation (EC'19). pp.583-583. [EC19]
NBER Market Design Working Group Meeting, Fall 2018
Ma, H., Meir, R., Parkes D.C., & Wu-Yan, E., Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present-Bias. In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'20). pp. 807-815. [Publisher's Version][arXiv][pdf][AAMAS20][AAMAS20 Talk]
Ma, H., Meir, R., Parkes D.C., & Zou, J., Contingent Payment Mechanisms for Resource Utilization. In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'19). pp. 422-430. Best paper award nomination. [Publisher's Version][arXiv] [pdf][AAMAS19]
Rheingans-Yoo, D., Kominers S.D., Ma, H. & Parkes, D.C., 2019. Ridesharing with Driver Location Preferences. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI’19). pp. 557-564. [Publisher's Version][arXiv][pdf]
Ma, H., Meir, R. & Parkes, D.C., 2018. Social Choice with Non Quasi-linear Utilities. In Proceedings of the 2018 ACM Conference on Economics and Computation (EC'18). pp. 49-49. [Publisher's Version] [arXiv] [pdf] [EC18][EC18 Talk]
Meir, R., Ma, H. & Robu, V., 2017. Contract Design for Energy Demand Response. In Proceedings of The 26th International Joint Conference on Artificial Intelligence (IJCAI'17). pp. 1202-1208. [Publisher's Version] [pdf]
Ma, H., Parkes, D.C. & Robu, V., 2017. Generalizing Demand Response Through Reward Bidding. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'17). pp. 60-68. [Publisher's Version] [pdf]
Ma, H., Robu, V., Li, N. & Parkes, D.C., 2016. Incentivizing Reliability in Demand-Side Response. In Proceedings of The 25th International Joint Conference on Artificial Intelligence (IJCAI'16). pp. 352-358. [Publisher's Version] [pdf]
Ma, H., Meir, R. & Parkes, D.C., 2016. Social Choice for Agents with General Utilities. In Proceedings of The 25th International Joint Conference on Artificial Intelligence (IJCAI'16). pp. 345-351. [Publisher's Version] [pdf]
Aggarwal, V., Mahimkar, V., Ma, H., Zhang, Z., Aeron, S., & Walter Willlinger. Inferring Smartphone Service Quality using Tensor Methods. In Proceedings 12th International Conference on Network and Service Management (CNSM’16), pp. 263-267, 2016.
Contact
hongyao.ma@columbia.edu
655 W130 St, Kravis Hall 1113, New York, NY, 10027