Papers
1
Total Citations
13
H-Index
1
About
Dr. Qingyi Liu is a leading researcher in intelligent infrastructure inspection, specializing in the intersection of robotics and deep learning for urban maintenance. Her primary research areas include computer vision, lightweight neural networks, and autonomous robotic systems for critical infrastructure. Dr. Liu’s most notable contribution is the development of a lightweight sewer pipe crack detection method, which integrates an amphibious robot with an improved YOLOv8n architecture. This work directly addresses the hazardous and inefficient challenge of inspecting underground sewage pipelines, enabling rapid, automated crack identification. Her pioneering paper on this method, published in 2024, has already garnered 13 citations, demonstrating its immediate impact on the field. By designing a system that can navigate complex subterranean environments and perform real-time, accurate defect detection, Dr. Liu is advancing the safety and longevity of urban infrastructure. Her research offers a practical, deployable solution for smart city maintenance, making her a key figure in the future of automated civil engineering and robotic inspection.
Research Focus
Key Achievements
Top Papers
- 1