Zili Li
Papers
3
Total Citations
76
H-Index
3
About
Zili Li is a leading researcher in the fields of underground infrastructure inspection, structural health monitoring, and automated defect detection. Their major contributions center on developing advanced, unmanned aerial vehicle (UAV)-based navigation systems and pixel-level computer vision techniques for assessing the condition of aging tunnels and large-scale underground structures. Li’s work is particularly notable for its practical impact, as demonstrated by a landmark case study at CERN, where they implemented an automated, pixel-level crack monitoring system to track structural degradation with high precision. This research has garnered significant attention, with their most-cited paper, “Unmanned aerial vehicle navigation in underground structure inspection: A review,” accumulating 41 citations since 2023, while their CERN case study has received 31 citations. By enabling early detection of cracks, deformations, and water leakage, Li’s innovations provide critical tools for extending the service life of vital infrastructure and preventing catastrophic failures. Their achievements highlight a unique blend of robotics, computer vision, and civil engineering, making them a key figure in the push toward autonomous, data-driven maintenance of the built environment.
Research Focus
Key Achievements
Top Papers
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