Jiangyong Li

Papers

Total Citations

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About

Jiangyong Li is a leading researcher at the intersection of robotics, reinforcement learning (RL), and human-robot interaction (HRI), with a focus on creating intelligent, safe, and socially aware autonomous systems. His work is distinguished by pioneering frameworks that bridge the gap between simulation and real-world deployment. Li’s most impactful contribution is the development of an RL framework integrated with an evolutionary trajectory generator for quadrupedal locomotion, which overcomes the challenges of complex nonlinear dynamics and reward sparsity—a paper that has garnered 55 citations since 2022. He further advanced safe policy optimization with his Intervention Aided Reinforcement Learning (IARL) framework, which introduces human oversight to ensure safety and practicality in navigation tasks. In the domain of social robotics, Li designed a proactive interaction framework for intelligent receptionist robots, enabling them to actively greet and assist people based on visual cues, a contribution cited 13 times for its impact on customer satisfaction. Collectively, his work demonstrates a consistent commitment to making RL-driven robots both more capable and more trustworthy in real-world settings.