Haozhe Lei
Papers
1
Total Citations
7
H-Index
1
About
Haozhe Lei is a rising researcher at the forefront of artificial intelligence and wireless systems, with a primary focus on physics-informed reinforcement learning for autonomous navigation. His most impactful work, "Zero-Shot Wireless Indoor Navigation through Physics-Informed Reinforcement Learning" (2024), has already garnered 7 citations—a strong early indicator of its significance. In this pioneering study, Lei addresses a critical challenge in indoor robotics: enabling zero-shot navigation using wireless signals without requiring site-specific training. By integrating RF propagation physics directly into the reinforcement learning framework, his approach achieves remarkable generalizability across diverse environments, overcoming the limitations of prior heuristic methods. This work bridges the gap between theoretical RF models and practical, data-driven AI, offering a scalable solution for real-world deployment. Lei’s contributions are particularly notable for their potential to transform logistics, search-and-rescue, and smart building automation, where reliable indoor navigation remains a persistent bottleneck. As an emerging voice in the intersection of wireless sensing and embodied AI, Haozhe Lei is poised to shape the next generation of intelligent, signal-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1