Mido Assran

VISITING RESEARCHER | MONTREAL, CANADA

Mido is a researcher at Facebook AI Research (FAIR) and Mila – Quebec AI Institute. He is an NSERC Vanier Scholar and holds a Vadasz Doctoral Fellowship in Engineering at McGill University. His research focuses on developing machine learning algorithms, with an emphasis on the data-/time-/energy-efficiency of learning. He is interested in optimization, distributed computing, and self-/semi-/weakly-supervised learning. His previous work has spanned both large-scale empirical analyses and theoretical studies.

Research Areas

Mido's Work

Mido's Publications

February 15, 2024

CORE MACHINE LEARNING

Revisiting Feature Prediction for Learning Visual Representations from Video

Adrien Bardes, Quentin Garrido, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas, Jean Ponce

February 15, 2024

June 18, 2023

CORE MACHINE LEARNING

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

Mido Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Mike Rabbat, Yann LeCun, Nicolas Ballas

June 18, 2023

September 16, 2020

Advances in Asynchronous Parallel and Distributed Optimization

Mike Rabbat, Mido Assran, Arda Aytekin, Hamid Feyzmahdavian, Mikael Johansson

September 16, 2020