Papers
3
Total Citations
32
H-Index
3
About
Mingsong Chen is a leading researcher in cyber-physical systems, with a focus on autonomous robotics, multi-robot coordination, and AI hardware acceleration. His work addresses critical challenges in enabling intelligent, safe, and efficient robot clusters for dynamic environments. A major contribution is the development of a hierarchical relational graph learning framework for autonomous multi-robot cooperative navigation, which enhances safety and efficiency in complex settings (2023, 10 citations). Chen also pioneered a CGRA-based neural network inference engine for deep reinforcement learning, enabling high-performance, low-power AI deployment on edge devices (2018, 12 citations). His practical impact is further demonstrated through the design and construction of an advanced multi-sensor person-following system for mobile robots, which improves human-robot collaboration in manufacturing and social contexts (2024, 10 citations). With over 30 total citations, Chen’s work bridges theoretical advances in graph learning and hardware acceleration with real-world robotic applications, making him a key figure in the evolution of autonomous, cooperative cyber-physical systems.
Research Focus
Key Achievements
Top Papers
- 1A CGRA based Neural Network Inference Engine for Deep Reinforcement Learning12 citations · 2018
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