My name is Jean Pouget-Abadie, but non-French speakers can call me John. I am a staff research scientist at Google Research, and based in New York. I lead a small research group, which focuses primarily on causal inference and computational statistics. We are part of the larger 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, where I was a 2017-2018 Siebel scholar. Prior to that, I was an undergraduate at Ecole Polytechnique, Paris. At the time, I looked into using neural networks to generate new distributions from data.
Staff Research Scientist at Google
with Vahab Mirrokni in the algorithms research group (2018-)
Spotify summer internship
with the Discover Weekly team (music recommendation) (2017)
Facebook summer internship
with Udi Weinsberg on the Core Data Science Team (2015)
Harvard University
PhD program in Computer Science (2014-2018)
MILA, Université de Montréal
with Yoshua Bengio in Deep Learning (2014)
École Polytechnique
Diplôme d'ingénieur (2011-2014)
Design and analysis of bipartite experiments under a linear exposure-response model. Christopher Harshaw, Fredrik Savje, David Eisenstat, Vahab Mirrokni, Jean Pouget-Abadie. [arXiv, EJS'23]
Cluster Randomized Designs for One-Sided Bipartite Experiments. Jennifer Brennan, Vahab Mirrokni, Jean Pouget-Abadie. [arXiv, NeurIPS'22]
Variance reduction of bipartite experiments through Correlation Clustering. Jean Pouget-Abadie, Kevin Aydin, Warren Schudy, Kay Brodersen, Vahab Mirrokni. [NeurIPS'19]
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'21]
Randomized Experimental Design via Geographic Clustering. David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab Mirrokni, Amir Najmi. [KDD'19]
Modeling Interference Using Experiment Roll-Out. Ariel Boyarsky, Hongseok Namkoong, Jean Pouget-Abadie. [arXiv, EC'23]
Testing for Arbitrary Interference on Experimentation Platforms. Jean Pouget-Abadie, Guillaume Saint-Jacques, Martin Saveski, Weitao Duan, Ya Xu, Souvik Ghosh, and Edoardo M. Airoldi. [arXiv, Biometrika'19]
Dealing with Interference on Experimentation Platforms. Jean Pouget-Abadie. Harvard 2018. [Dissertation]
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'17]
Generative Adversarial Networks. Ian Goodfellow, Jean Pouget-Abadie, Medhi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. [arXiv, NeurIPS'14]
Segmentation for Neural Machine Translation. Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merriënboer, Kyung Hyun Cho, and Yoshua Bengio. SSST-8 @ EMNLP 2014 [arXiv]
I've had the privilege of mentoring some incredible Googlers, interns, and AI residents over the years: Khashayar Khosravi, Nick Doudchenko, Chris Harshaw, Jennifer Brennan (now full time @ Google), Evan Munro, and Ian Waudby-Smith.