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About

Saman Zonouz is a prominent cybersecurity researcher whose work sits at the critical intersection of cyber-physical systems security, embedded systems, and autonomous robotics. His research focuses on securing industrial control systems, robotic aerial vehicles (RAVs), and IoT devices against sophisticated cyber-physical attacks — domains where software vulnerabilities carry real-world physical consequences. Zonouz has made significant contributions to the field through innovative approaches including physics-based attestation of programmable logic controllers, as demonstrated in his influential "PAtt" framework, which ensures the integrity of embedded control systems in safety-critical industrial environments. His work on drone security leverages deep neural networks and approximate computing to defend against cyber-physical attacks on unmanned aerial vehicles, while his reverse engineering research enables deeper understanding of closed-source embedded firmware — crucial for vulnerability assessment and security retrofitting. His exploration of neural network-based robot motion planning and multi-agent reinforcement learning for disaster situational awareness further illustrates his interdisciplinary reach. With papers accumulating citations across security, robotics, and IoT domains, and contributions spanning from 2017 through 2023, Zonouz has established himself as a leading voice in securing the increasingly connected and autonomous systems shaping our physical world.