My name is Jean Pouget-Abadie, but non-French speakers can call me John. I am a research scientist at Google Research New York on the Algorithms & Optimization team, led by Vahab Mirrokni. Before joining Google, I was a PhD student in Computer Science at Harvard University, advised by Edoardo Airoldi and Salil Vadhan. Prior to that, I was an undergraduate at Ecole Polytechnique, Paris. My recent research interests focus on causal inference and experimental design, particularly when network interference is present. In the past, I looked into using neural networks to generate distributions. I was a 2017-2018 Siebel scholar.
Resume Google Scholar Google Research ProfileSenior Research Scientist at Google
with Vahab Mirrokni in the algorithms research group
Spotify summer internship
with the Discover Weekly team (music recommendation)
Facebook summer internship
with Udi Weinsberg on the Core Data Science Team
Harvard University
PhD program in Computer Science (2018)
MILA, Université de Montréal
with Yoshua Bengio in Deep Learning
École Polytechnique
Diplôme d'ingénieur (2014)
Design and analysis of bipartite experiments under a linear exposure-response model
Christopher Harshaw, Fredrik Savje, David Eisenstat, Vahab Mirrokni, Jean Pouget-Abadie. forthcoming [arXiv]
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls
Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sebastien Lahaie, Miles Lubin, Vahab Mirrokni, Jann Spiess, Guido Imbens. NeurIPS 2021 [NeurIPS]
Variance reduction of bipartite experiments through Correlation Clustering
Jean Pouget-Abadie, Kevin Aydin, Warren Schudy, Kay Brodersen, Vahab Mirrokni. NeurIPS 2019 [NeurIPS]
Randomized Experimental Design via Geographic Clustering
David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab Mirrokni, Amir Najmi. KDD 2019 [KDD]
Optimizing cluster-based randomized experiments under a monotonicity assumption
Jean Pouget-Abadie, David C. Parkes, Vahab Mirrokni, Edoardo M. Airoldi. KDD 2018. [arXiv, KDD, code]
Testing for arbitrary interference on experimentation platforms
Jean Pouget-Abadie, Martin Saveski, Guillaume Saint-Jacques, Weitao Duan, Ya Xu, Souvik Ghosh, and Edoardo M. Airoldi. Biometrika 2019. [arXiv, Biometrika]
Detecting Network Effects: Randomizing over Randomized Experiments
Martin Saveski, Jean Pouget-Abadie, Guillaume Saint-Jacques, Weitao Duan, Ya Xu, Souvik Ghosh, and Edoardo M. Airoldi. KDD 2017. [KDD]
Inferring Graphs from Cascades: A Sparse Recovery Framework
Jean Pouget-Abadie and Thibaut Horel. ICML 2015 [arXiv, ICML]
Generative Adversarial Networks
Ian Goodfellow, Jean Pouget-Abadie, Medhi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. NeurIPS 2014 [arXiv, NeurIPS]
Segmentation for Neural Machine Translation
Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merriënboer, Kyung Hyun Cho, and Yoshua Bengio. SSST-8 @ EMNLP 2014 [arXiv]