Papers
2
Total Citations
13
H-Index
2
About
Xudong Jian is pioneering the integration of robotics and structural health monitoring, with a focus on transforming how bridges are assessed and maintained. His core research areas include robotic mobile sensing, operational modal analysis, and population-based structural health monitoring (PBSHM). Jian’s major contribution is the development of a robotic automated solution that enables high-resolution mode shape recovery of bridges using minimal sensors and remotely controlled wheeled robots. This work, published in 2024 and already garnering 11 citations, addresses a critical bottleneck in traditional fixed-sensor approaches by allowing efficient, high-spatial-resolution data collection across multiple structures. His subsequent 2025 study, with 2 citations, advances this paradigm by tackling uncertainty analysis, algorithm development, and field validation for robust modal identification across bridge populations—a key step toward scalable PBSHM. Jian’s work is notable for its end-to-end integration of hardware, software, and real-world validation, promising to make bridge monitoring more accessible, cost-effective, and comprehensive. For students and researchers, Jian exemplifies how robotics can revolutionize civil infrastructure assessment, offering a compelling vision of autonomous, data-driven maintenance for aging bridge networks.
Research Focus
Key Achievements
Top Papers
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