Sébastien Lahaie
Sébastien Lahaie is a research scientist in the Market Algorithms group at Google Research, NYC. He received his PhD in Computer Science from Harvard in 2007 and was previously a researcher at Yahoo and Microsoft Research. His research focuses on computational aspects of market design, with applications to sponsored search and display advertising. He is interested in designing market algorithms that scale well and properly anticipate user behavior. Other interests include preference modeling and elicitation, combinatorial auctions, and prediction markets.
Research Areas
Authored Publications
Sort By
Google
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls
Guido Imbens
Jann Spiess
Khashayar Khosravi
Miles Lubin
Nick Doudchenko
35th Conference on Neural Information Processing Systems (NeurIPS 2021) (2021)
Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing
International Conference on Machine Learning (2021), pp. 2601-2610
A Data-Driven Metric of Incentive Compatibility
Proceedings of The Web Conference (2020), pp. 1796-1806
Robust Pricing in Dynamic Mechanism Design
International Conference on Machine Learning (2020), pp. 2494-2503
A Robust Non-Clairvoyant Dynamic Mechanism for Contextual Auctions
Advances in Neural Information Processing Systems (2019), pp. 8657-8667
Testing Dynamic Incentive Compatibility in Display Ad Auctions
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (2019), pp. 1616-1624
Preferred Deals in General Environments
Proceedings of the 28th International Joint Conference on Artificial Intelligence (2019), pp. 231-237
Testing Incentive Compatibility in Display Ad Auctions
Proceedings of the 2018 World Wide Web Conference on World Wide Web, WWW 2018
A Decomposition of Forecast Error in Prediction Markets
Jenn Wortman Vaughan
Miroslav Dudik
Ryan Rogers
Advances in Neural Information Processing Systems (NIPS) (2017)
