WANG Dong

WANG Dong is a Faculty member in the Department of Industrial Engineering and Management at the School of Mechanical Engineering, Shanghai Jiao Tong University. His research interests include Machine Learning and Statistical Learning, Interpretable Data Fusion Methodology, and Intelligent Decision Making and Operations Research. He has contributed to the fields of Machine Condition Monitoring, Fault Diagnosis, and Prognostics. WANG has published over 200 SCI papers in international journals and authored two English academic monographs. His work has been cited over 14,600 times with an H-index of 66. He is affiliated with the Department of Statistics, School of Mathematical Sciences, Shanghai Jiao Tong University, and serves as a Cooperative Tutor at the SJTU–Paris Elite Institute of Technology (SPEIT).

Dong WANG is a tenured associate professor at Shanghai Jiao Tong University, specializing in Condition monitoring, Fault diagnosis, and Prognostics and Health Management. His research focuses on developing advanced techniques for vibration-based health indicators, fault diagnosis of rolling element bearings, and prognostics of lithium-ion batteries. He has contributed to the design of deep learning models, such as CNN-LSTM networks and stacked sparse autoencoders, for fault diagnosis and state-of-charge estimation. His work also includes the development of novel signal processing methods, such as sparsity-guided empirical wavelet transforms and enhanced Kurtogram techniques, to improve the accuracy and robustness of fault detection and remaining useful life prediction in rotating machinery and energy storage systems.