Nandi Leslie
Papers
1
Total Citations
2
H-Index
1
About
Nandi Leslie is a leading researcher in adversarial machine learning, cybersecurity, and autonomous systems, with a focus on the intersection of game theory and formal methods. Her work addresses critical challenges in securing AI-driven systems against sophisticated attacks, particularly in sensor networks and autonomous robotics. In her highly cited 2021 paper, "Qualitative Planning in Imperfect Information Games with Active Sensing and Reactive Sensor Attacks: Cost of Unawareness," Leslie models adversarial interactions between a robot and an attacker using a formal game-theoretic framework. This work demonstrates how an autonomous agent can jointly plan control actions and sensor queries while anticipating reactive sensor attacks, revealing the hidden costs of being unaware of adversarial strategies. Her research has profound implications for the safety and resilience of autonomous systems in contested environments, from military applications to critical infrastructure. With over 2 citations on this work alone and growing recognition in the cybersecurity community, Leslie's contributions are shaping how we design robust AI systems that can operate securely under adversarial conditions.
Research Focus
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Top Papers
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