Guangyao Li

Papers

1

Total Citations

2

H-Index

1

About

Dr. Guangyao Li is a leading researcher in energy-efficient hardware acceleration for autonomous systems, with a primary focus on embedded computer vision and robotics. His most cited work introduces a groundbreaking low-hardware-overhead, high-energy-efficiency, and end-to-end CNN-based feature extraction accelerator designed specifically for mobile visual SLAM (Simultaneous Localization and Mapping). This contribution directly addresses the critical challenge of deploying computationally intensive deep learning methods—such as the SuperPoint feature extractor—on resource-constrained platforms. By enabling real-time, accurate feature extraction with dramatically reduced power consumption, Dr. Li’s accelerator bridges the gap between state-of-the-art AI accuracy and practical mobile deployment. His work has garnered early recognition, with 2 citations already reflecting its emerging impact in the fields of embedded AI and robotics. Dr. Li’s research is pivotal for advancing autonomous navigation in drones, AR/VR devices, and mobile robots, where efficient on-device processing is essential. His achievements position him as a key innovator in the intersection of hardware design, deep learning, and real-time robotic perception.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A low-hardware-overhead, high-energy-efficiency, and end-to-end CNN-based feature extraction accelerator for mobile visual SLAM
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago