Mido Assran is a Research Scientist at Meta in Fundamental AI Research (FAIR). Previously, Mido obtained his PhD in Electrical and Computer Engineering from McGill University and Mila, the Quebec AI Institute, where he was primarily advised by Michael Rabbat. His current research focuses on advancing self-supervised representation learning and low-shot prediction. In the past, Mido worked on parallelizing deep reinforcement learning, and large-scale optimization.
His research on representation learning has been featured in several media outlets, including VentureBeat, TechCrunch, and SiliconANGLE. He was also fortunate to have a featured profile piece in the ICCV daily magazine.
Mido served as an expert reviewer for ICML and NeurIPS, and received Best Reviewer awards at NeurIPS'20, ICML'20, ICML'21, and AAAI'20.
