Fabio Pierazzi

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About

Fabio Pierazzi is a leading researcher at the intersection of cybersecurity, artificial intelligence, and robotics, with a primary focus on adversarial machine learning and the security of autonomous systems. His work investigates how intelligent systems—from deep learning models to physical robots—can be manipulated by adversaries, and how to design robust defenses against such threats. Among his most impactful contributions is the characterization of physical adversarial attacks on robot motion planners, a pioneering study that exposed vulnerabilities in autonomous navigation algorithms, demonstrating how subtle environmental perturbations can cause robots to deviate from safe paths. This work, published in 2024, has already garnered significant attention with over 5 citations, underscoring its timely relevance. Pierazzi’s research is notable for bridging the gap between theoretical adversarial examples and real-world, physical-domain attacks, influencing both the security and robotics communities. His achievements include advancing the understanding of how to secure cyber-physical systems against stealthy, targeted manipulation, making his work essential reading for students and researchers tackling the safety and resilience of next-generation autonomous technologies.