Lei Pan

China University of Mining and Technology

Papers

Total Citations

H-Index

About

Lei Pan is an emerging researcher working at the intersection of computer vision, robotics, and neural representation learning. His work focuses on the application of Neural Radiance Fields (NeRFs) and neural implicit representations to robotic systems — a rapidly evolving area that promises to transform how machines perceive and interact with three-dimensional environments. Pan's most notable contribution is a comprehensive survey on NeRFs in robotics, which examines how these powerful neural rendering techniques enable robots to construct detailed, realistic 3D environment models for tasks such as navigation, manipulation, and scene understanding. Published across 2024 and 2025, this survey has already garnered early citations, reflecting growing community interest in a field that sits at the frontier of modern AI-driven robotics. By synthesizing advances in neural implicit representations and their practical robotic applications, Pan's work serves as an important reference point for researchers seeking to understand both the state of the art and future directions in this domain. His contributions position him as a thoughtful synthesizer of knowledge in one of today's most dynamic research areas.