Omar Montasser

Omar Montasser is a PhD student at TTI-Chicago advised by Nathan Srebro. His main research interest is the theory of machine learning. Recently, his research focused on understanding and characterizing adversarially robust learning, and designing algorithms with provable robustness guarantees under different settings. His work has been recognized by a best student paper award at COLT.