Nansha Li
Papers
2
Total Citations
104
H-Index
2
About
Nansha Li is a leading researcher in the field of non-destructive evaluation and infrastructure health monitoring, with a primary focus on automated subsurface defect detection for airport runways. Her work centers on integrating Ground Penetrating Radar (GPR) technology with advanced deep learning architectures to solve critical challenges in civil infrastructure inspection. Li’s major contributions include the development of GPR-RCNN (2021, 80 citations), a pioneering algorithm that combines GPR data with a region-based convolutional neural network to autonomously detect subsurface defects, enabling robotic inspection systems to replace manual, error-prone processes. She further advanced this domain with MV-GPRNet (2022, 24 citations), a multi-view network that significantly improves the interpretation of complex GPR data by leveraging spatial and contextual information from multiple perspectives. Her research directly addresses the difficulty of GPR data interpretation, offering robust, automated solutions that enhance runway structural reliability and safety. Li’s work is notable for its practical impact on airport maintenance, reducing inspection time and human error, and her algorithms have set a benchmark for integrating robotics and AI in civil engineering. With a growing citation record, Li is recognized as a key innovator in applying computer vision to infrastructure diagnostics.
Research Focus
Key Achievements
Top Papers
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- 2