Qingmei Sui

Shandong University

Papers

1

Total Citations

2

H-Index

1

About

Dr. Qingmei Sui is a leading figure in nondestructive testing and infrastructure inspection, with a primary focus on advancing ground-penetrating radar (GPR) technologies through robotics and artificial intelligence. Their most impactful work, "Robotic subsurface defect inspection system and an unsupervised deep neural network-based abnormal traces reconstruction method for ground penetrating radar data autonomous collection" (2025), introduces a pioneering framework that integrates autonomous robotic control with deep learning to overcome critical limitations in GPR data collection. By developing an unsupervised neural network for reconstructing abnormal signal traces, Dr. Sui enables more reliable, high-quality subsurface defect detection without the need for extensive labeled training data. This contribution addresses a long-standing challenge in automated infrastructure monitoring, significantly improving the efficiency and accuracy of detecting internal structural flaws in roads, bridges, and buildings. With 2 citations already in its first year, this work is gaining rapid recognition for its practical impact. Dr. Sui’s research sits at the intersection of robotics, signal processing, and civil engineering, offering transformative tools for smart infrastructure maintenance and safety assessment. Their innovative approach positions them as a key contributor to the future of autonomous inspection systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Robotic subsurface defect inspection system and an unsupervised deep neural network-based abnormal traces reconstruction method for ground penetrating radar data autonomous collection
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Shandong University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago