Dr. Xiang Xu is currently working as a TRAIN@Ed Research Fellow (UN Marie-Sklodowska Curie Cofund Program) in School of Engineering, University of Edinburgh. He was working as a postdoc in Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University. He received the B.S. degree in Road and Bridge Engineering from Southeast University, China, and the Ph.D. degree in Bridge Engineering from Southeast University, China. His research interests include smart structures, structural health monitoring, big data, data mining, maintenance strategy, and inspection policy.
MD-Ph.D. in Bridge & Tunnel Engineering Southeast University 09/2013-06/2019
Bachelor in Highway & Bridge Engineering Southeast University 08/2009-06/2013
Structural condition assessment algorithm
Structural health monitoring (SHM)
Finite Element Model (MIDAS, ANSYS, ABQUS)
Coding (MATLAB, PYTHON)
Bridge Design Codes
Xu, X., Ren, Y., Huang, Q., Fan, Z. Y., Tong, Z. J., Chang, W. J., & Liu, B. (2020). Anomaly detection for large span bridges during operational phase using structural health monitoring data. Smart Materials and Structures.
Xu, X., Ren, Y., Huang, Q., Zhao, D. Y., Tong, Z. J., & Chang, W. J. (2020). Thermal response separation for bridge long‑term monitoring systems using multi‑resolution wavelet‑based methodologies. Journal of Civil Structural Health Monitoring.
Xu, X., Huang*, Q., Ren, Y., Zhao, D., Yang, J., & Zhang, D. (2019) Modelling and separation of thermal effects from cable-stayed bridge response. ASCE Journal of Bridge Engineering.
Xu, X., Huang*, Q., Ren, Y., Zhao, D., & Yang, J. (2019) Sensor fault diagnosis for bridge structural health monitoring system based on similarity of symmetric structure responses. Smart Structures & Systems.
Xu, X., Huang*, Q., Ren, Y., Zhao, D., Zhang, D., & Sun, H. (2019) Condition evaluation of suspension bridges for maintenance, repair and rehabilitation: a comprehensive framework. Structure & Infrastructure Engineering.
Xu, X., Huang*, Q., Ren, Y., & Sun, H. B. (2018) Condition assessment of suspension bridges using local variable weight and normal cloud model. KSCE Journal of Civil Engineering.