Yiqin Deng
Papers
1
Total Citations
17
H-Index
1
About
Yiqin Deng is a leading researcher in collaborative perception and task-oriented communications for multi-robot and vehicular networks. Their work addresses critical challenges in real-time adaptive systems, particularly the fusion of sensory data across agents to enhance perception accuracy and extend sensing range. Deng’s most cited paper, "R-ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications" (2025, 17 citations), introduces a novel framework that tackles extrinsic calibration errors caused by mobility and non-rigid sensor mounts. By enabling online calibration and robust communication, this work significantly improves the reliability of collaborative perception in dynamic environments. Deng’s contributions are pivotal for advancing autonomous systems, from self-driving cars to drone swarms, where precise, real-time data sharing is essential. Their research has already garnered attention for its practical impact on multi-agent coordination, with potential applications in smart cities and disaster response. Deng continues to push the boundaries of task-oriented communications, making them a rising figure in the field of networked robotics and intelligent transportation systems.
Research Focus
Key Achievements
Top Papers
- 1