Fangjian Li
Papers
3
Total Citations
36
H-Index
3
About
Fangjian Li is a researcher at the forefront of human-robot interaction (HRI) and autonomous systems, with a focus on trust, safety, and resilience. His work bridges the critical gap between human cognition and robotic autonomy, particularly in high-stakes environments like autonomous driving and multi-vehicle coordination. Li’s major contributions include developing a comprehensive survey on human trust in robots, which synthesizes trust models from organizational studies and human factors to guide HRI and human-autonomy teaming—a foundational resource that has garnered 18 citations since 2023. He also proposed a novel HRI framework for unmanned ground vehicle (UGV) platooning under cyber attacks, integrating observer-based resilient control to mitigate vehicle-to-vehicle (V2V) threats, earning 15 citations. Additionally, Li advanced safety in autonomous driving by introducing a safety-aware adversarial inverse reinforcement learning (IRL) method, addressing the vulnerability of IRL to unsafe behaviors. With over 36 citations across his top works, Li’s research is shaping how robots earn and maintain human trust while operating securely in adversarial and dynamic settings. His work is essential reading for those exploring the intersection of trust, security, and autonomy in robotics.
Research Focus
Key Achievements
Top Papers
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