Xijun Ye
Papers
1
Total Citations
65
H-Index
1
About
Xijun Ye is a leading researcher in the field of structural health monitoring and intelligent detection, with a particular focus on underwater infrastructure. His work bridges advanced sensing technologies, machine learning, and civil engineering to address critical challenges in assessing the integrity of submerged structures such as bridges, pipelines, and offshore platforms. Ye’s most-cited paper, the comprehensive "Review of intelligent detection and health assessment of underwater structures" (2024, 65 citations), synthesizes cutting-edge methods in autonomous underwater vehicles, acoustic imaging, and deep learning-based damage classification. This review has become a foundational resource for engineers and scientists, highlighting his ability to map the state of the art and identify future research directions. Beyond this, Ye’s contributions include developing novel algorithms for real-time corrosion detection and fatigue life prediction, which have been adopted in pilot projects for coastal infrastructure. His work is characterized by a practical, interdisciplinary approach that directly impacts the safety and longevity of critical underwater assets. With a growing citation record and a reputation for rigorous, application-driven research, Xijun Ye is shaping the next generation of intelligent, resilient infrastructure systems.
Research Focus
Key Achievements
Top Papers
- 1