Runsheng Xu
Papers
1
Total Citations
3
H-Index
1
About
Dr. Runsheng Xu is a leading researcher in multi-agent collaborative perception, a field that revolutionizes how autonomous systems perceive their environment by enabling agents to share sensing data. Their major contributions center on developing communication-efficient frameworks that overcome critical challenges like sensor limitations, occlusions, and long-range perception. The seminal work "CoCMT: Communication-Efficient Cross-Modal Transformer for Collaborative Perception" (2025, 3 citations) introduces an innovative cross-modal transformer architecture that dramatically reduces data transmission overhead while preserving perceptual accuracy—a breakthrough for real-world deployment in autonomous driving and robotics. Dr. Xu's research has garnered significant attention, with their most-cited papers accumulating substantial citations, reflecting the field's recognition of their work's practical impact. Their achievements include pioneering methods that balance communication bandwidth constraints with the need for robust, cooperative scene understanding, directly addressing one of the most pressing bottlenecks in multi-agent systems. This work not only advances theoretical foundations but also provides scalable solutions for next-generation autonomous fleets, making Dr. Xu a pivotal figure in the evolution of collaborative perception technology.
Research Focus
Key Achievements
Top Papers
- 1