Xueji Wang

Papers

Total Citations

123

H-Index

About

Xueji Wang is a pioneering researcher in computational imaging and autonomous perception, whose work bridges thermal sensing and machine learning to overcome fundamental limitations in low-visibility environments. His landmark paper "Heat-assisted detection and ranging" (2023, 120 citations) introduced a novel framework that leverages thermal infrared signals for active ranging, effectively enabling "heat-based LiDAR" that functions in complete darkness, fog, or smoke where conventional optical systems fail. This breakthrough has significant implications for autonomous navigation, defense, and search-and-rescue operations. In his comparative study "Thermal Voyager" (2024), Wang systematically evaluated RGB versus thermal cameras for night-time autonomous navigation, providing critical insights into sensor fusion strategies for robotics operating in challenging lighting conditions. His work addresses the persistent obstacle of reliable nighttime autonomy, offering alternatives to expensive LiDAR and RADAR systems. Wang's research uniquely combines thermal physics with deep learning architectures, creating practical solutions that push the boundaries of what machines can perceive. With growing citation impact and applications spanning autonomous vehicles to surveillance, Xueji Wang is establishing himself as a leading voice in thermal computer vision and all-weather perception systems.