Jean Pouget-Abadie
Jean Pouget-Abadie is a research scientist at Google NYC on the Algorithms and Optimization team led by Vahab Mirrokni. He holds a PhD in Computer Science from Harvard University, advised by Edoardo Airoldi and Salil Vadhan. Prior to that, he was an undergraduate at Ecole Polytechnique, Paris. His recent research interests include algorithms and statistics, with a particular focus on causal inference. More information can be found at his personal homepage.
Authored Publications
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Design and analysis of bipartite experiments under a linear exposure-response model
Christopher Harshaw
Fredrik Savje
Proceedings of the 23rd ACM Conference on Economics and Computation (2022), pp. 606
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)
Randomized Experimental Design via Geographic Clustering
David Rolnick
Amir Najmi
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (2019)
Variance Reduction in Bipartite Experiments through Correlation Clustering
Warren Schudy
Thirty-third Conference on Neural Information Processing Systems (2019) (to appear)
