Yongpan Liu
Papers
3
Total Citations
7
H-Index
2
About
Yongpan Liu is a leading researcher in energy-efficient edge computing, with a focus on hardware-software co-design for autonomous systems, robotics, and intelligent sensing. His work bridges the gap between advanced machine learning algorithms and resource-constrained hardware, enabling real-time, low-power AI at the edge. A major contribution is the development of a 28nm scalable vision/point cloud deep fusion processor, achieving 5.27 TOPS/W for BEVFusion applications—critical for autonomous driving and robot navigation. He also pioneered an energy-efficient flexible capacitive pressure sensing system for healthcare and IoT, addressing power challenges in large sensing arrays. Most recently, Liu introduced a 94Hz inference edge SoC for diffusion-based robot manipulation, featuring speculative parallel inference and disturbance enhancement for on-device fine-tuning. His work has garnered citations in top venues like ISSCC and JSSC, reflecting its impact on both academic research and practical deployment. Liu’s innovations are shaping the future of intelligent, low-power edge devices, making him a key figure in the evolution of autonomous and interactive systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2An Energy-Efficient Flexible Capacitive Pressure Sensing System2 citations · 2020
- 3