Ji Dang

Papers

Total Citations

H-Index

About

Ji Dang is a leading researcher in structural health monitoring and infrastructure resilience, with a focus on integrating advanced sensing and autonomous technologies for bridge and underwater inspections. His key research areas include unmanned aerial vehicle (UAV)-based inspection, artificial intelligence (AI) for damage detection, and remote measurement technology. Dang’s major contributions lie in developing innovative, non-destructive methods to assess structural integrity, addressing critical safety concerns in aging infrastructure. His most-cited work, "Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections" (2020, 44 citations), proposes a transformative framework that combines UAVs and AI to enhance the accuracy and efficiency of bridge evaluations, reducing risks associated with traditional visual inspections. Additionally, his pioneering development of "Tactile Imaging for Underwater Structural Damage Detection" (2019, 25 citations) introduces a novel tactile sensing system for autonomous underwater inspections, moving beyond diver-based methods and remotely operated vehicles to enable robotic damage detection in challenging environments. Dang’s work has significant implications for infrastructure safety and maintenance, earning recognition for its practical applications in civil engineering and robotics. His research continues to shape the future of automated, data-driven structural assessment.