Amr Mohamed

Amr S. Mohamed (BASc 2017, MASc 2020, PhD 2024; University of Toronto) leads multiple projects focusing on applying AI to enhance cyber-physical systems’ cybersecurity. His work includes leveraging deep reinforcement learning for intelligent cyberattack generation and modeling, applying machine and deep learning for attack detection, and developing safety-critical control algorithms and safe reinforcement learning techniques for cyber-resilient control systems and within industrial honeypots. His research also explores explainable AI for trustworthy integration of cyber-resilient AI in safety-critical industries. The research’s applications span various sectors, such as smart grids and autonomous vehicles. In industry, he has experience as an electricity market data analyst at Ontario’s Independent Electricity System Operator (IESO) and as an engineering consultant at Hatch Ltd.

amr (dot) mohamed (at) mail (dot) utoronto (dot) ca
LinkedIn
Google Scholar
GitHub