Mohamed is a Machine Learning Research Team Lead at Borealis AI, focusing on Bayesian Deep Learning and Asynchronous Time Series. The goal of his research is to develop machine learning models that have better performance and better uncertainty estimates.
Prior to joining Borealis, Mohamed received his Ph.D. in Computer Science from the University of British Columbia with a thesis on optimization for machine learning advised by Prof. Mark Schmidt. Formerly, he received a MASc. in Electrical Engineering from the University of British Columbia, a M.Sc. in Engineering Physics from Cairo University, and a BSc in Electrical Engineering from Cairo University.