About

Ruoxiang Li is a robotics and real-time systems researcher whose work bridges the gap between bio-inspired sensing, autonomous systems, and the formal timing analysis of robotic software frameworks. His early research demonstrated a flair for computer vision, most notably with FA-Harris (2019, 56 citations), a fast and asynchronous corner detection algorithm designed for event cameras — bio-inspired sensors with significant promise for dynamic robotic environments. Li subsequently pivoted toward a sustained and highly impactful body of work on the Robot Operating System (ROS 2), addressing one of the field's most pressing practical challenges: guaranteeing real-time performance in safety-critical autonomous systems. His analyses of processing chain scheduling, message synchronization timing, worst-case latency, and GPU resource management in ROS 2 have collectively accumulated over 70 citations, establishing him as a leading voice in real-time robotic middleware research. His more recent work extends these concerns to edge-assisted autonomous driving, tackling sensor fusion challenges in connected vehicle systems. With contributions spanning UAV collaborative SLAM, event-based vision, and rigorous formal system analysis, Li's research portfolio reflects a remarkably broad yet cohesive commitment to making autonomous robotic systems faster, safer, and more reliable.

Research Focus

Key Achievements

5
H-Index
9
Papers
142
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
FA-Harris: A Fast and Asynchronous Corner Detector for Event Cameras
56 citations · 2019
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 27
🏛 Institutions: National University of Defense Technology, City University of Hong Kong, City University of Hong Kong, Shenzhen Research Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago