Quanyan Zhu
Papers
14
Total Citations
180
H-Index
8
About
Quanyan Zhu is a prominent researcher at the intersection of game theory, cybersecurity, and autonomous robotic systems. His work fundamentally advances how multi-agent and multi-layer networked systems can be made resilient, secure, and strategically intelligent in adversarial environments. Zhu's most influential contributions include developing game-theoretic frameworks for decentralized control of mobile autonomous systems, where his "games-in-games" approach addresses network connectivity challenges across heterogeneous layers — work that has garnered over 70 combined citations. His research on rational and persistent robot deception, applying dynamic game theory to pursuit-evasion scenarios, has opened new frontiers in robot autonomy and operational security. Zhu has also made significant strides in robotics cybersecurity, producing widely referenced work quantifying vulnerabilities in Robot Operating Systems and contemporary robotic platforms. More recently, he has pioneered Stackelberg meta-learning and Koopman operator methods to enable strategic guidance in multi-robot trajectory planning under incomplete information. His physics-informed reinforcement learning approach to wireless indoor navigation further demonstrates his breadth of innovation. Collectively, Zhu's research provides essential theoretical and practical tools for building secure, cooperative, and adaptive autonomous systems in complex, contested environments.
Research Focus
Key Achievements
Top Papers
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- 4Cybersecurity in Robotics: Challenges, Quantitative Modeling, and Practice18 citations · 2021
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- 8Stackelberg Strategic Guidance for Heterogeneous Robots Collaboration9 citations · 2022
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