Genda Chen

Missouri University of Science and Technology

Papers

5

Total Citations

35

H-Index

2

About

Dr. Genda Chen is a leading figure in structural health monitoring and intelligent infrastructure systems, with a career dedicated to revolutionizing how we inspect and preserve aging bridges and steel structures. His research masterfully integrates robotics, deep learning, and advanced sensing technologies to create safer, more efficient inspection methods. A cornerstone of his work is the development of assistive artificial intelligence for bridge inspection, exemplified by his highly cited 2021 paper on a semi-supervised self-training method for segmenting multiclass bridge elements from inspection videos (25 citations). This work addresses the critical challenge of rapidly analyzing vast amounts of visual data collected by mobile robots. Dr. Chen also pioneers the use of distributed fiber optic sensors for quantifying thermal strain in steel structures at high temperatures, a significant contribution to measurement science. His forward-looking research extends to aerial nondestructive testing and evaluation (aNDT&E), exploring how drones can overcome the limitations of manual inspections for long-span bridges. Through these innovations, Dr. Chen is not only advancing academic knowledge but also providing practical, cost-effective solutions that enhance the safety and longevity of critical transportation infrastructure.

Research Focus

Key Achievements

2
H-Index
5
Papers
35
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
A semi-supervised self-training method to develop assistive intelligence for segmenting multiclass bridge elements from inspection videos
25 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Missouri University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago