Michael Rabbat
RESEARCH SCIENTIST | MONTREAL, CANADA
Mike is a founding member of the Facebook AI Research (FAIR) team in Montreal. He holds a B.Eng. from the University of Illinois at Urbana-Champaign, a M.Eng from Rice University, and a Ph.D. in electrical engineering from the University of Wisconsin-Madison. Prior to Facebook, Mike was a professor at McGill University in the Department of Electrical and Computer Engineering. His research interests include optimization, distributed algorithms and signal processing.
Michael's Publications
June 11, 2025
RESEARCH
COMPUTER VISION
IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments
Adina Williams, Emmanuel Dupoux, Florian Bordes, Justine Kao, Mike Rabbat, Quentin Garrido
June 11, 2025
June 11, 2025
ROBOTICS
RESEARCH
V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
Mojtaba Komeili, Sarath Chandar, Abha Gejji, Ada Martin, Adrien Bardes, Ammar Rizvi, Artem Zholus, Claire Roberts, Daniel Dugas, David Fan, Francisco Massa, Francois Robert Hogan, Franziska Meier, Kapil Krishnakumar, Koustuv Sinha, Marc Szafraniec, Matthew Muckley, Mido Assran, Michael Rabbat, Nicolas Ballas, Patrick Labatut, Piotr Bojanowski, Quentin Garrido, Russell Howes, Sergio Arnaud, Vasil Khalidov, Xiaodong Ma, Yann LeCun, Yong Li
June 11, 2025
April 17, 2025
ROBOTICS
RESEARCH
Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Ruslan Partsey, Ayush Jain, Ang Cao, Ishita Prasad, Aravind Rajeswaran, Abha Gejji, Ada Martin, Arjun Majumdar, Daniel Dugas, Franziska Meier, Krishna Murthy Jatavallabhula, Mido Assran, Mikael Henaff, Mike Rabbat, Mrinal Kalakrishnan, Nicolas Ballas, Oleksandr Maksymets, Paul McVay, Phillip Thomas, Alexander Sax, Sergio Arnaud, Vincent-Pierre Berges
April 17, 2025
December 12, 2024
COMPUTER VISION
EvalGIM: A Library for Evaluating Generative Image Models
Melissa Hall, Abhishek Charnalia, Adriana Romero Soriano, Candace Ross, Carolina Braga, Jakob Verbeek, Karen Ullrich, Maeve Ryan, Mark Ibrahim, Marton Havasi, Michal Drozdzal, Mike Rabbat, Oscar Mañas, Pietro Astolfi, Reyhane Askari, Tariq Berrada Ifriqi, Yohann Benchetrit
December 12, 2024
April 04, 2024
CORE MACHINE LEARNING
DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning
Chuan Guo, Adriana Romero Soriano, Jonathan Lebensold, Kamalika Chaudhuri, Maziar Sanjabi, Mike Rabbat, Pietro Astolfi
April 04, 2024
February 15, 2024
CORE MACHINE LEARNING
Revisiting Feature Prediction for Learning Visual Representations from Video
Nicolas Ballas, Adrien Bardes, Mido Assran, Michael Rabbat, Quentin Garrido, Xinlei Chen, Yann LeCun, Jean Ponce
February 15, 2024
June 18, 2023
CORE MACHINE LEARNING
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
Nicolas Ballas, Ishan Misra, Mido Assran, Mike Rabbat, Pascal Vincent, Piotr Bojanowski, Quentin Duval, Yann LeCun
June 18, 2023
April 26, 2023
CORE MACHINE LEARNING
SYSTEMS RESEARCH
Green Federated Learning
Kiwan Maeng, Ashkan Yousefpour, Ashish Shenoy, Carole-Jean Wu, Ilya Mironov, Mike Rabbat, Pierre Stock, Sayan Ghosh, Schalk Krüger, Shen Guo
April 26, 2023
July 13, 2022
Federated Learning with Partial Model Personalization
Lin Xiao, Abdelrahman Mohamed, Kshitiz Malik, Maziar Sanjabi, Mike Rabbat, Krishna Pilllutla
July 13, 2022
April 26, 2022
PAPAYA: PRACTICAL, PRIVATE, AND SCALABLE FEDERATED LEARNING
John Nguyen, Anthony Shoumikhin, Ashkan Yousefpour, Carole-Jean Wu, Dzmitry Huba, Harish Srinivas, Hongyuan Zhan, Jesik Min, Kaikai Wang, Kshitiz Malik, Mani Malek, Mike Rabbat, Pavel Ustinov, Ruiyu Zhu
April 26, 2022
September 14, 2021
Federated Learning with Buffered Asynchronous Aggregation
Kshitiz Malik, Ashkan Yousefpour, Dzmitry Huba, Hongyuan Zhan, John Nguyen, Mani Malek, Mike Rabbat
September 14, 2021
December 14, 2020
Stability of Decentralized Gradient Descent in Open Multi-Agent Systems
Mike Rabbat, Julien Hendrickx
December 14, 2020
September 16, 2020
Advances in Asynchronous Parallel and Distributed Optimization
Mike Rabbat, Mido Assran, Arda Aytekin, Hamid Feyzmahdavian, Mikael Johansson
September 16, 2020
February 25, 2020
RESEARCH
Lookahead converges to stationary points of smooth non-convex functions
Mike Rabbat, Jianyu Wang, Nicolas Ballas, Vinayak Tantia
February 25, 2020
February 25, 2020
RESEARCH
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
Mike Rabbat, Nicolas Ballas, Vinayak Tantia, Jianyu Wang
February 25, 2020
February 11, 2019
RESEARCH
Provably Accelerated Randomized Gossip Algorithms
Mike Rabbat, Nicolas Loizou, Peter Richtarik
February 11, 2019
Our approach
Latest news
Foundational models
Meta © 2026