About me
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 team within the larger Algorithms & Optimization group, 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.
Mini-CV
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)
Selected Publications
GenAI
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]
Bipartite Experiments
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]
Small-samples and Geographical Experiments
Causal Bootstrap for General Randomized Designs. Jennifer Brennan, Sébastien Lahaie, Adel Javanmard, Nick Doudchenko, Jean Pouget-Abadie [arXiv]
Randomized Experimental Design via Geographic Clustering. David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab Mirrokni, Amir Najmi. [KDD'19]
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls. Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sébastien 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]
Dealing with Interference
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]
Mentorship
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, Roshni Sahoo.