Personal Information

Xiang Zhengliang, Doctor of Engineering, is currently a postdoctoral fellow and assistant researcher at Central South University. He received a bachelor's degree in civil engineering (bridge engineering) from Central South University in 2014, a master's degree in civil engineering (disaster prevention and mitigation engineering and protection engineering) from Central South University in 2017, and a doctorate in mechanics (engineering mechanics) from Harbin Institute of Technology in 2021. His current research interest is wind reliability evaluation method of bridge structures based on deep learning. Currently, he has published more than 10 SCI papers in international authoritative journals such as Mechanical Systems and Signal Processing, Reliability Engineering & System Safety, Engineering with Computers, and Structural Health Monitoring, and obtained 2 national invention patents and 3 software copyrights. He has won a youth fund project of the National Natural Science Foundation of China, one youth fund project of the Hunan Provincial Natural Science Foundation of China, and one general project of the China Postdoctoral Science Foundation. He was awarded the Excellent Master’s Thesis Award of Hunan Province, a winning prize of the First Hunan Postdoctoral Innovation and Entrepreneurship Competition, the Excellent Master’s Thesis Award of Central South University, the Outstanding Graduate of Central South University, and the OVM Scholarship of Harbin Institute of Technology.

Educational Background

2017/09-2021/09: Harbin Institute of Technology, Mechanics, Ph.D.

2014/09-2017/06: Central South University, Civil Engineering, Master

2010/09-2014/06: Central South University, Civil Engineering, Bachelor

Work Experience

2018/02-Now Cental South University, School of Civil Engineering, Postdoctor

Research Projects

[1] Youth Fund Project of National Natural Science Foundation of China (52208223): Fusion method for buffeting reliability analysis of long-span high-speed railway bridges based on deep generative network and deep reinforcement learning, 300,000 RMB, 2023-2025, leader: Zhengliang Xiang.

[2] Youth Fund Project Hunan Provincial Natural Science Foundation (2023JJ40754): Research on Buffeting Reliability Analysis Method of Long-span High-speed Railway Bridge under Mixed Uncertainty Based on Deep Learning, 2023-2025, 50,000 RMB, leader: Zhengliang Xiang.

[3] General Project of China Postdoctoral Science Foundation (2022M713545) Research on fusion analysis method of buffeting reliability of long-span high-speed railway bridges based on deep learning, 80,000 RMB, 2022-2023, leader: Zhengliang Xiang.

Research publication

[1] Xiang Zhengliang, He Xuhui, Zou Yunfeng, Jing Haiquan. An importance sampling method for structural reliability analysis based on interpretable deep generative network[J]. Engineering with Computers, 2023: 1-14. (SCI, JCR Q1, IF=8.7)

[2] Xiang Zhengliang, He Xuhui*, Zou Yunfeng, Jing Haiquan. An active learning method for crack detection based on subset searching and weighted sampling[J]. Structural Health Monitoring. 2023;0(0). doi:10.1177/14759217231183661. (SCI, JCR Q1, IF=6.6)

[3] Xiang Zhengliang, Chen Jiahui, Bao Yuequan*, Li Hui. An active learning method combining deep neural network and weighted sampling for structural reliability analysis[J]. Mechanical Systems and Signal Processing, 2020, 140: 106684. (SCI, JCR Q1, IF=8.4)

[4] Xiang Zhengliang, Bao Yuequan*, Tang Zhiyi, Li Hui. Deep reinforcement learning-based sampling method for structural reliability assessment[J]. Reliability Engineering & System Safety, 2020, 199: 106901. (SCI, JCR Q1, IF=8.1)

[5] Bao Yuequan*, Xiang Zhengliang, Li Hui. Adaptive subset searching-based deep neural network method for structural reliability analysis[J]. Reliability Engineering & System Safety, 2021, 213: 107778. (SCI, JCR Q1, IF=8.1)

Contact

Email： xiangzl@csu.edu.cn