2012.01～2015.07, Ph.D. in Systems Engineering and Engineering Management, City University of Hong Kong (Prof. Peter W. Tse and Chair Prof. Kwok Leung Tsui)
2007.09～2010.06, M.Phil. in Mechatronics Engineering, University of Electronic Science and Technology of China (Prof. Qiang Miao)
2003.09～2007.07, Bachelor in Mechanical Design, Manufacturing and Automation, University of Electronic Science and Technology of China

2025.02~Now, Tenured Associate Professor, Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University
2018.10～2025.01 Tenure Track Associate Professor, Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University
2018.10～Now, Affilited Associate Professor, Department of Statistics, School of Mathematical Sciences, Shanghai Jiao Tong University
2018.10～Now, Cooperative Tutor, The SJTU – Paris Elite Institute of Technology (SPEIT), Shanghai Jiao Tong University
2018.07~2018.09, Research Fellow, School of Data Science, City University of Hong Kong
2018.04~2018.06, Research Fellow, Department of Systems Engineering and Management, City University of Hong Kong
2015.10~2018.03, Postdoctoral Fellow, Department of Systems Engineering and Management, City University of Hong Kong
2015.06~2015.09, Senior Research Assistant, Department of Systems Engineering and Management, City University of Hong Kong
2015.02~2015.06, Research Associate, Smart Engineering Asset Management Laboratory, City University of Hong Kong
2011.01~2011.07, Research Associate, Croucher Optical Nondestructive Testing & Quality Inspection laboratory, City University of Hong Kong
2010.07~2011.01 Research Assistant, Smart Engineering Asset Management Laboratory, City University of Hong Kong

*School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, Australia
*Department of Industrial Engineering, Hanyang University
*Department of Industrial Engineering, Korea University
*School of Data Science, City University of Hong Kong


Plenary keynotes, invited talks and discussions:
*2nd Complex Equipment Reliability Engineering and Science Symposium
*High end equipment intelligent operation and maintenance young scientist salon
*3rd World Congress on Condition Monitoring
*Twentieth International Conference of Condition Monitoring and Machinery Failure Prevention Technologies (CM2024)
*2024 Academic Annual Meeting of the Dynamic Testing Professional Committee of the Chinese Society of Vibration Engineering
*5th Youth Forum of the Fault Diagnosis Professional Committee of the Chinese Society of Vibration Engineering in 2024
*7th International Conference on Mechanical, Electric, and Industrial Engineering (MEIE2024)
*16th National Conference on Rotor Dynamics (ROTDYN2024) and the Young Scholars Forum of the Chinese Society of Vibration Engineering (2024-1)
*International Workshop on Fault Diagnostics and Prognostics (TEPEN2024-IWFDP)
*2024 Annual Conference of the Reliability Branch of the Chinese Operations Research Society
*2023 Nanjing University of Science and Technology High end Equipment Young Scholars Forum
*2023 Jiangsu Province Graduate High end Equipment and Intelligent Manufacturing (Condition Monitoring and Intelligent Diagnosis) Academic Innovation Forum
*4th Youth Forum of the Fault Diagnosis Professional Committee of the Chinese Society of Vibration Engineering in 2023
*2023 Academic Annual Meeting of the Dynamic Signal Analysis Professional Committee of the Chinese Society of Vibration Engineering
*15th National Conference on Vibration Theory and Applications
*Youth Academic Forum of the School of Aeronautics, Northwestern Polytechnical University
*1st International Conference on Aerospace Structural Dynamics
*2023 International Conference on Equipment Intelligent Operation and Maintenance && 5th International Conference on Reliability Systems Engineering
*Summer Institute on Quality Reliability and Data Science
*12th Wu Wenjun AI Science and Technology Award Ceremony and 2022 China AI Industry Annual Conference
*First National Youth Academic Forum on Intelligent Equipment Operation and Maintenance
*15th National Conference on Rotor Dynamics and the Young Scholars Forum of the Chinese Society of Vibration Engineering
*3rd Youth Forum of the Fault Diagnosis Professional Committee of the Chinese Society of Vibration Engineering in 2023
*2022 World Youth Scientists Summit Academic Seminar on High end Equipment System Dynamics and Intelligent Diagnosis and Maintenance
*AI Empowered Equipment Intelligent Operation and Maintenance Online Sharing Conference
*19th National Conference on Space and Sports Control Technology
*33rd National Conference on Reliability Technology in the Machinery Industry

*Machine Learning and Data Mining
*Sparsity Measure and Complexity measure
*Interpretable Data Fusion Methodology
*Probability Models
*Advanced Signal Processing and Statistical Learning
*Intelligent Decision Making and Operations Research
*Machine Condition Monitoring, Fault Diagnosis, Prognostics

~~~Hosting intelligent operation and big data analysis projects~~~
Hosted National Key R&D Program projects, National Natural Science Foundation General Projects, National Overseas High Level Talent Projects, China Nuclear Power Design Institute projects, China Shipbuilding Industry Corporation, Huawei Technologies Co., Ltd. projects, Lenovo (Beijing) Co., Ltd. projects, Western Digital Corporation projects, Aerospace Fifth Institute projects, Shanghai Nuclear Engineering Design Institute projects, Shanghai Jiao Tong University Overseas First Class University Academic Exchange Fund (Shanghai Jiao Tong University - University of New South Wales), General Research Fund (GRF, Co-PI), CityU Strategic Research Grant (Co-PI)

~~~Participation in intelligent operation and big data analysis projects~~~
Technical backbone participated in the National Natural Science Foundation of China Innovation Group, Ministry of Education China Mobile Research Fund R&D project, Shanghai Electric project, Nuclear Power Operation Research (Shanghai) Co., Ltd. project, Changzhou damper project, Theme based Research Scheme, Hong Kong: Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems

Published over 150 SCI papers in international journals such as Mechanical Systems and Signal Processing, IEEE and ASME Transactions (e.g., IEEE Transactions on Reliability, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Neural Networks and Learning Systems, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, ASME Transactions on Journal of Vibration and Acoustics), Journal of Sound and Vibration, Journal of Power Sources, Information Fusion, Reliability Engineering and System Safety, Signal Processing, Advanced Engineering Informatics, Knowledge-Based Systems, Structural Health Monitoring, ISA Transactions, Renewable and Sustainable Energy Reviews, Energy, Applied Energy, Measurement, Engineering Applications of Artificial Intelligence, etc. (including over 40 first-authored SCI papers), authored 2 English academic monographs, published 2 review papers in Chinese Journal of Mechanical Engineering, and 1 review paper in Chinese Journal of Vibration Engineering. The research findings have been cited over 13,000 times in Google Scholar with an H-index of 63.
Research Contributions:
A) Fundamental Research on Sparsity Measures and Complexity Measures: The commonalities of quantifying fault signals through sparsity measures are unclear, making it difficult to design new sparsity measures. A generalized framework for classical sparsity measures was proposed to address the common challenges of sparsity measures across multiple fields. New sparsity measures were designed and theoretically proven, solving the problem of designing new sparsity measures. The "bilateral effect" of complexity measures was discovered, resolving the identification challenges between sparsity and complexity measures. Further development was made in designing adaptive sparsity measures through data-driven approaches. An optimized weight spectrum theory was proposed, using positive and negative optimized weights to identify fault and reference frequencies. The optimization weight distribution pattern can be solved using FFT and convex optimization to reveal fault characteristics, highlighting the uniqueness of FFT in the field of fault diagnosis and facilitating the implementation of monitoring and diagnosis in engineering.
B) Interpretable Performance Degradation Assessment Data Fusion Methodology Research: Current degradation assessment methods do not consider degradation properties, leading to significant model output uncertainty. The full-life degradation process of equipment was described using degradation properties such as state separability, degradation monotonicity, inter-class distance and intra-class distance, shape, and trend, and a health index signal-to-noise ratio was defined. The weighted sum of spectral amplitudes (e.g., amplitude in the frequency domain or envelope spectral domain) was defined as the generalized health index. Based on the degradation characteristics and the sparsity of fault features, a related generalized health index weight convex optimization model was derived. The weight optimization model and optimized spectral amplitude weights are physically interpretable, capable of identifying degradation features and revealing the dynamic evolution process of fault features, achieving the triple purpose of monitoring, diagnosis, and degradation assessment simultaneously.
C) Lifetime Prediction Statistical Probability Model Research: A generalized Brownian motion lifetime prediction theory and a multi-state Brownian motion state space model were proposed, overcoming the challenges of classical lifetime prediction assumptions. The essential differences between Bayesian prediction models and state space prediction models were discovered, revealing the unique nature of state noise in state space prediction models. A discrete reciprocating jump state lifetime prediction model and its online Bayesian parameter update technology were developed. Without the need for regression functions, individual online lifetime prediction can be realized using online degradation data.
D) Signal Processing and Statistical Learning Integration Methodology Research: Current signal processing models such as wavelet transform, variational mode decomposition, empirical mode decomposition, and sparse decomposition are essentially band-pass filters, which cannot remove in-band noise or separate reference and fault cross-frequency components. Differential mode decomposition was proposed to reconstruct reference, fault, and noise signals using spectral lines, addressing the limitations of band-pass filtering and providing new ideas for the development of original decomposition algorithms in the field of fault diagnosis. Pulse mode decomposition was proposed to distinguish single pulses and cyclic pulses from the time domain alone, solving the problem of identifying single and cyclic pulses.
English Academic Monographs:
Dong Wang and Bingchang Hou, Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring, Book, Elsevier, 2025, ISBN 978-0-443-33486-3: https://doi.org/10.1016/C2023-0-52917-9.
Dong Wang and Tongtong Yan, Machine Performance Degradation Assessment: Convex Optimization Models and Their Interpretable Data Fusion Applications, Book, Elsevier, to be published in Nov. 2025.

~~~Selected Publications~~~
A********Sparsity Measures and Complexity Measures********A
Dong Wang*, Zhike Peng, Lifeng Xi, The Sum of Weighted Normalized Square Envelope: A Unified Framework for Kurtosis, Negative Entropy, Gini Index and Smoothness Index for Machine Health Monitoring, Mechanical Systems and Signal Processing, 140 (2020), 106725.
Bingchang Hou, Dong Wang*, Jin-Zhen Kong, Jie Liu, Zhike Peng, Kwok-Leung Tsui, Understanding importance of positive and negative signs of optimized weights used in the sum of weighted normalized Fourier spectrum/envelope spectrum for machine condition monitoring, Mechanical Systems and Signal Processing, 174 (2022) 109094.
Dong Wang*, et al. Correlation Dimension and Approximate Entropy for System Health Monitoring: Revisited, Mechanical Systems and Signal Processing, 152 (2021) 107497.
Dong Wang*, Zhike Peng, Lifeng Xi, Theoretical and Experimental Investigations on Spectral Lp/Lq Norm Ratio and Spectral Gini Index for Rotating Machine Health Monitoring, IEEE Transactions on Automation Science and Engineering, 18 (2021) 1074 - 1086.
Dong Wang*, et al. Box-Cox Sparse Measures: A New Family of Sparse Measures Constructed from Kurtosis and Negative Entropy, Mechanical Systems and Signal Processing, 160 (2021) 107930.
Tongtong Yan, Dong Wang*, Tangbin Xia, Zhike Peng, Lifeng Xi，Investigations on Generalized Hjorth's Parameters for Machine Performance Degradation Assessment, Mechanical Systems and Signal Processing, Volume 168 (2022) 108720.
Dong Wang*, Some further thoughts about spectral kurtosis, spectral L2/L1 norm, spectral smoothness index and spectral Gini index for characterizing repetitive transients, Mechanical Systems and Signal Processing, 108C (2018) pp. 360-368. 
Dong Wang*, Spectral L2/L1 norm: A new perspective for spectral kurtosis for characterizing non-stationary signals, Mechanical Systems and Signal Processing, 104 (2018) 290-293. 
Bingchang Hou, Dong Wang*, Tangbin Xia, Yi Wang, Yang Zhao, Kwok-Leung Tsui, Investigations on Quasi-arithmetic Means for Machine Condition Monitoring, Mechanical Systems and Signal Processing, 151 (2021), 107451. 
Bingchang Hou, Dong Wang*, Member, IEEE, Tongtong Yan, Yi Wang, Zhike Peng, Kwok-Leung Tsui, Gini Indices Ⅱ and Ⅲ: Two New Sparsity Measures and Their Applications for Machine Condition Monitoring, IEEE/ASME Transactions on Mechatronics, 27 (2022) 1211-1222.
Bingchang Hou, Dong Wang*, Tangbin Xia, Lifeng Xi, Zhike Peng, Kwok-LeungTsui, Generalized Gini indices: Complementary sparsity measures to Box-Cox sparsity measures for machine condition monitoring, Mechanical Systems and Signal Processing,169 (2022) 108751.
Dong Wang*, Jie Liu, Shilong Sun, Changqing Shen, Bingchang Hou, Tongtong Yan, Zhike Peng, Investigations on the Sensitivity of Sparsity Measures to the Sparsity of Impulsive Signals, Mechanical Systems and Signal Processing, 178 (2022) 109315.
YuTing Wang, Dong Wang*, Investigations on Sample Entropy and Fuzzy Entropy for Machine Condition Monitoring：Revisited, Measurement Science and Technology, 34 (2023) 125104.
Lan Wei, Dong Wang*, Yu Wang, Generalized relative entropy: New look at Rényi entropy and its exploration from complexity measures to sparsity measures with applications in machine condition monitoring, Mechanical Systems and Signal Processing, 223, (2025) 111917.


B********Interpretable Degradation Modeling and Data Fusion********B
Dong Wang* , Bingchang Hou, Tongtong Yan, Changqing Shen, Zhike Peng, New Statistical Learning Perspective for Design of a Physically Interpretable Prototypical Neural Network for Machine Condition Monitoring, Mechanical Systems and Signal Processing, 188 (2023) 110041.
Dong Wang*, Yikai Chen, Changqing Shen, Jingjing Zhong, Zhike Peng, Chuan Li,, Fully Interpretable Neural Networks for Machine Health Monitoring,Mechanical Systems and Signal Processing, 168 (2022) 108673.
Bingchang Hou, Dong Wang*, Yikai Chen, Hong Wang, Zhike Peng, Kwok Leung Tsui, Interpretable Online Updated Weights: Optimized Square Envelope Spectrum for Machine Condition Monitoring and Fault diagnosis, Mechanical Systems and Signal Processing, 169 (2022) 108779.
Tongtong Yan, Dong Wang*, Tangbin Xia, Lifeng Xi, A Generic Framework for Degradation Modeling Based on Fusion of Spectrum Amplitudes, IEEE Transactions on Automation Science and Engineering, 19 (2021), 308 - 319.
Tongtong Yan, Dong Wang*, Jinzhen Kong, Tangbin Xia, Zhike Peng, Lifeng Xi, Definition of Signal-to-Noise Ratio of Health Indicators and Its Analytic Optimization for Machine Performance Degradation Assessment, IEEE Transactions on Instrumentation and Measurement, 70 (2021).
Tongtong Yan, Dong Wang*, Bingchang Hou, Zhike Peng, Generic Framework for Integration of First Prediction Time Detection with Machine Degradation Modelling from Frequency Domain, IEEE Transactions on Reliability, 71 (2022) 464 - 1476.
Tongtong Yan, Yuting Wang, Tangbin Xia, Bingchang Hou, Lifeng Xi, Dong Wang*, Sparse and Flexible Convex-hull Representation for Machine Degradation Modeling, IEEE Transactions on Reliability, 72 (2022) 27 - 36.
Tongtong Yan, Dong Wang*, Meimei Zheng, Tangbin Xia, Ershun Pan, Lifeng Xi, Fisher' s Discriminant Ratio Based Health Indicator for Locating Informative Frequency Bands for Machine Performance Degradation Assessment, Mechanical Systems and Signal Processing, 162 (2022) 108053.
Tongtong Yan, Dong Wang*, Shilong Sun, Changqing Shen, Zhike Peng, Novel Sparse Representation Degradation Modeling for Locating Informative Frequency Bands for Machine Performance Degradation Assessment, Mechanical Systems and Signal Processing, 179 (2022) 109372.
Tongtong Yan, Dong Wang*, Tangbin Xia, Ershun Pan, Zhike Peng, Lifeng Xi, Online Piecewise Convex-optimization Interpretable Weight Learning for Machine Life Cycle Performance Assessment, IEEE Transactions on Neural Networks and Learning Systems, (2022) Early Access.
Tongtong Yan, Dong Wang*, Tangbin Xia, Jie Liu, Zhike Peng, Lifeng Xi, Investigation on Optimal Discriminant Directions of Linear Discriminant Analysis for Locating Informative Frequency Bands for Machine Health Monitoring, Mechanical Systems and Signal Processing, 180 (2022): 109424.
Tongtong Yan, Dong Wang*, Tangbin Xia, Ershun Pan, Zhike Peng and Lifeng Xi, New Shapeness Property and Its Convex Optimization Model for Interpretable Machine Degradation Modeling, IEEE Transactions on Reliability, 72 (2022), 703 - 715.
Tongtong Yan, Yichu Fu, Ming Lu, Zhinong Li, Changqing Shen, Dong Wang*, Integration of a Novel Knowledge-guided Loss Function with an Architecturally Explainable Network for Machine Degradation Modeling, IEEE Transactions on Instrumentation and Measurement 71 (2022): 1-12.
Tongtong Yan, Dong Wang*, Tangbin Xia, Meimei Zheng, Zhike Peng, Lifeng Xi, Entropy-maximization oriented interpretable health indicators for locating informative fault frequencies for machine health monitoring, Mechanical Systems and Signal Processing, 198 (2023) 110461.
Yikai Chen, Dong Wang*, Bingchang Hou, Tangbin Xia, Gaussian assumptions-free interpretable linear discriminant analysis for locating informative frequency bands for machine condition monitoring, Mechanical Systems and Signal Processing, 199 (2023) 110492.
Tongtong Yan, Dong Wang*, Tangbin Xia, Zhike Peng, Lifeng Xi, Sparsity preserving projection aided baselined hyperdisk modeling for interpretable machine health monitoring, Mechanical Systems and Signal Processing, 200 (2023) 110509.
Yu Wang, Dong Wang*, Tongtong Yan, Optimal Squared Wald Statistics based Methodology for On-line Machine Condition Monitoring and Degradation Assessment, IEEE Transactions on Instrumentation and Measurement, 72 (2023), 3522112.
Xiao Feng, Dong Wang*, Bingchang Hou, Tongtong Yan, Interpretable federated learning for machine condition monitoring: Interpretable average global model as a fault feature library, Engineering Applications of Artificial Intelligence, 124 (2023) 106632.
Tongtong Yan, Dong Wang*, Meimei Zheng, Changqing Shen, Tangbin Xia, Zhike Peng, retable sparse learned weights and their entropy based quantification for online machine health monitoring, 199 (2023) 110493.
Tongtong Yan, Dong Wang*, Jin-zhen Kong, Zhongxiao Peng, Large Margin-learning Methodology from Time-Frequency Maps and Its Physically Interpretable Weights for Simultaneous Machine Health Monitoring and Fault Diagnosis, Mechanical Systems and Signal Processing, 200 (2023) 110615.
Yichu Fu, Yikai Chen, Dong Wang*, Zhike Peng, Interpretable Fusion Methodology of Health Indices with an Application to Industrial Turbine Cavitation Condition Monitoring, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, (2023) accepted and to appear.
Tongtong Yan, Dong Wang*, Tangbin Xia, Lifeng Xi, Novel Anchor Discrimination Learning for Physics-Informed Machine Degradation Modeling, IEEE Transactions on Reliability, (2023) accepted and to appear.
Bingchang Hou, Jie Liu, Dong Wang*, Easier Computation Approach of Optimized Weights and Its Extensions for Learning Interpretable Machine Fault Features, IEEE Transactions on Instrumentation and Measurement, (2023), in press.
Tongtong Yan, Dong Wang*, Yu Wang, Discrimination and Sparsity Driven Weight-oriented Optimization Model for Interpretable Initial Fault Detection and Fault Diagnosis, IEEE Transactions on Instrumentation and Measurement, (2023), in press.
Yu Wang, Dong Wang*, Bingchang Hou, Siliang Lu, Zhike Peng, Robust optimized weights spectrum: Enhanced interpretable fault feature extraction method by solving frequency fluctuation problem, Mechanical Systems and Signal Processing, 222 (2025) 111798.
Tongtong Yan, Dong Wang*, Tangbin Xia, Lifeng Xi, Min Xia, Two-dimensional Optimization Framework of Online Interpretable Time-frequency Feature Learning for Practical Machine, IEEE Transactions on Reliability, (2025) accepted and to appear.
Tongtong Yan, Dong Wang*, Tangbin Xia, Zhike Peng, Lifeng Xi, Theoretical Investigation of Convex Representation based Interpretable Time-frequency Weight Optimization for Machine Health Monitoring, Mechanical Systems and Signal Processing, 230 (2025) 112625.
Tongtong Yan, Xueqi Xing, Dong Wang, Kwok-Leung Tsui, Min Xia, Interpretable degradation tensor modeling through multi-scale and multi-level time-frequency feature fusion for machine health monitoring, Information Fusion, 117 (2025) 102935.
Tongtong Yan, Dong Wang*, Tangbin Xia, Zhike Peng, Lifeng Xi, Theoretical Investigation of Convex Representation based Interpretable Time-frequency Weight Optimization for Machine Health Monitoring, Mechanical Systems and Signal Processing, 230 (2025) 112625.
Xiaoqiang Liao, Dong Wang, Siqi Qiu, Xinguo Ming, ReDBN: An Interpretable Deep Belief Network for Fan Fault Diagnosis in Iron and Steel Production Lines, IEEE/ASME Transactions on Mechatronics, 30 (2025) 1646 - 1657.
Xiaoqiang Liao, Dong Wang, Xinguo Ming, Min Xia, DLCNN: A Deep Logic Convolutional Network for Interpretable Fault Diagnosis of Hoist Mechanism on Ship-to-Shore Cranes, IEEE Transactions on Neural Networks and Learning Systems, (2025), in press.
Xiaoqiang Liao, Dong Wang, Xinguo Ming, Siqi Qiu, Zuhua Jiang, Min Xia, DLBN: A Deep Logic Belief Network for Fault Diagnosis of Dust Removal Fans, Information Fusion, (2025) 103627



C********Remaining Useful Life Prediction********C
Dong Wang*, Kwok-Leung Tsui, Statistical modeling of bearing degradation signals, IEEE Transactions on Reliability, 66 (2017) 1331 - 1344.
Dong Wang*, Kwok-Leung Tsui, Brownian motion with adaptive drift for remaining useful life prediction: revisited, Mechanical Systems and Signal Processing, 99 (2018) 691-701.
Dong Wang*, Kwok-Leung Tsui, Two novel mixed effects models for prognostics of rolling element bearings, Mechanical Systems and Signal Processing, 99 (2018) 1-13.
Jin-Zhen Kong, Dong Wang*, Tongtong Yan, Jingzhe Zhu, Xi Zhang, Accelerated Stress Factors based Nonlinear Wiener Process Model for Lithium-ion Battery Prognostics, IEEE Transactions on Industrial Electronics, 69 (2021), 11665-11674.
Jin-Zhen Kong, Di Cui, Bingchang Hou, Xingchen Liu, Dong Wang*, New Short-Long-Term Degradation Model for Precise Battery Health Prognostics, IEEE Transactions on Industrial Electronics, 70 (2023) 9527 - 9537.
Jie Liu, Dong Wang,* Jin-Zhen Kong, Zhike Peng, Kwok-Leung Tsui, Similarities and Differences between Batch and Recursive Bayesian Prognostic Methods and State-Space Models based Prognostic Methods with an Emphasis on Additive Gaussian and Brownian Motion Errors , Mechanical Systems and Signal Processing, (2023) accepted and to appear.
Jie Liu, Bingchang Hou, Ming Lu, Dong Wang*, Box-Cox transformation based state-space modeling as a unified prognostic framework for degradation linearization and RUL prediction enhancement, Reliability Engineering & System Safety, 244 (2024) 109952.
Jinzhen Kong, Jie Liu, Jingzhe Zhu, Xi Zhang, Kwok-Leung Tsui, Zhike Peng & Dong Wang*, Review on Lithium-ion Battery PHM from the Perspective of Key PHM Steps, Chinese Journal of Mechanical Engineering, 37, (2024): 71. （cover paper）
Jie Liu, Dong Wang*, Yujie Mou, Zikang Chen, and Ming Lu. Adaptive Generalized Time Interval Cumulative Methodology for Optical Port Degradation Modeling in Cloud Computing Service, IEEE Transactions on Instrumentation and Measurement, (2025) early access.
Jie Liu, Dong Wang*, Jin-Zhen Kong, Naipeng Li, Zhike Peng, Kwok-Leung Tsui, New Look at Bayesian Prognostic Methods, IEEE Transactions on Automation Science and Engineering, (2025) early access.
Yujie Mou, Dong Wang, Jie Liu, Wang Shi, Shiyu Hu, Ming Lu, Adaptive On-Line Discrete Degradation State Distribution Prediction Methodology for Cloud Computing Optical Fiber Ports, IEEE Transactions on Instrumentation and Measurement, (2025) in press.

D********Mechanical Signal Processing********D
Dong Wang*, Kwok-Leung Tsui, Dynamic Bayesian Wavelet Transform: New Methodology for Extraction of Repetitive Transients, Mechanical Systems and Signal Processing, 88 (2017) 137-144.
Sha Wei, Dong Wang, Zhike Peng, Zhipeng Feng, Variational Nonlinear Component Decomposition for Fault Diagnosis of Planetary Gearboxes under Variable Speed Conditions, Mechanical Systems and Signal Processing, 162 (2022) 108016.
Bingchang Hou, Dong Wang*, Yi Wang, Tongtong Yan, Zhike Peng, Kwok Leung Tsui, Adaptive Weighted Signal Preprocessing Technique for Machine Health Monitoring, IEEE Transactions on Instrumentation and Measurement, 70 (2021).
Sha Wei, Dong Wang, Hong Wang, Zhike Peng, Time-varying Envelope Filtering for Exhibiting Space Bearing Cage Fault Features, IEEE Transactions on Instrumentation and Measurement, 70 (2021).
Cristian López, Dong Wang*, Ángel Naranjo, Keegan J. Moore, Box-Cox-Sparse-Measures-Based Blind Filtering: Understanding the Difference between the Maximum Kurtosis Deconvolution and the Minimum Entropy Deconvolution, Mechanical Systems and Signal Processing, 165 (2022) 108376.
Bingchang Hou, Yikai Chen, Hong Wang, Zhike Peng, Kwok-Leung Tsui, Dong Wang*, OSESgram: Data Aided Method for Selection of Informative Frequency Bands for Bearing Fault Diagnosis, IEEE Transactions on Instrumentation and Measurement, 71 (2022) 3513310.
Bingchang Hou, Dong Wang*, Zhike Peng, Kwok-Leung Tsui, Adaptive Fault Components Extraction by Using an Optimized Weights Spectrum based Index for Machinery Fault Diagnosis, IEEE Transactions on Industrial Electronics, (2023) accepted and to appear.
Bingchang Hou, Dong Wang*, Tangbin Xia, Zhike Peng, Kwok Leung Tsui, Difference Mode Decomposition for Adaptive Signal Decomposition, Mechanical Systems and Signal Processing, 191 (2023) 110203.
Bingchang Hou, Xiao Feng, Jinzhen Kong, Zhike Peng, Kwok Leung Tsui, Dong Wang*, Optimized Weights Spectrum Autocorrelation: A New and Promising Method for Fault Characteristic Frequency Identification for Rotating Machine Fault Diagnosis, Mechanical Systems and Signal Processing, 191 (2023) 110200.
Bingchang Hou, Dong Wang*, Optimal Noise Subtraction based Fault Components Extraction for Machinery Fault Diagnosis, IEEE Transactions on Instrumentation and Measurement (2023), online Early Access.
Bingchang Hou, Min Xie, Hong Yan, Dong Wang*, Impulsive Mode Decomposition, Mechanical Systems and Signal Processing, 211 (2024) 111227.
Bingchang Hou, Min Xie, Zhike Peng, Dong Wang*, Enspectrumix: Novel Adaptive Methodology for Fault Components Extraction from Vibration Mixtures, Mechanical Systems and Signal Processing, 219 (2024), 111611.
Bingchang Hou, Yu Wang, Dong Wang, Cycle-Embedded Sparsity Measures as A Generalized Objective Function of Impulsive Mode Decomposition for Impulsive Fault Component Extraction, Mechanical Systems and Signal Processing, (2025) accepted and to appear.
Sha Wei; Dong Wang; Shulin Liu; Zhike Peng, Parameterized Time-Varying Tracking Filtering for Extracting Adjacent Time-Frequency Fault Features of Nonstationary Signals in Planetary Gearboxes, IEEE Transactions on Instrumentation and Measurement, (2025) in press.

*Teaching @ SJTU
Postgraduate Course: Statistical Learning
Teaching Book: Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. "The elements of statistical learning: data mining, inference, and prediction." .

Undergraduate Course: Service Management
Teaching Book: Bordoloi, Sanjeev, James A. Fitzsimmons, and Mona J. Fitzsimmons. Service management: operations, strategy, information technology.

*Associate Editor->Topical Editor, IEEE Sensors Journal (2021 to now)
*Editorial Board Member->Associate Editor, Mechanical Systems and Signal Processing, (2020 to now)
*Associate Editor, IEEE Transactions on Instrumentation and Measurement (2020 to now)
*Associate Editor, Measurement, and Measurement: Sensors (2022 to now)
*Associate Editor, Journal of Dynamics, Monitoring and Diagnostics (2022 to now)
*Area Editor, Journal of Reliability Science and Engineering (2024 to now)
*Associate Editor, Journal of Low Frequency Noise, Vibration & Active Control (2017 to 2022)
*Guest Editor, Mechanical Systems and Signal Processing (2022)
*Guest Editor, IEEE Transactions on Instrumentation and Measurement (2023)
*Guest Editor, Reliability Engineering and System Safety (2023)
*Guest Editor, Measurement Science and Technology (2025)
*Guest Editor, Journal of Mechanical Engineering (2023)
*Guest Editor, Journal of Risk and Reliability (2021)
*Member,The State Key Laboratory of Mechanical Systems and Vibration
*Deputy Secretary General, Chinese Society for Vibration Engineering (2019 to 2023, 2024 to 2027)
*Member, Chinese Institute of Quality Research
*Reviewer for 60+ domestic and international journals, such as MSSP, IEEE Transactions, ASME Transactions, IISE Transactions, Technometrics, RESS.
*Committee member for various conferences, such as EPHM, IEEE PHM, ICSMD, DAMAS, QR2MSE, ICSMD, APARM, survishno23, ICASD, UNIfied 2023, etc.

Personal Honors and Awards
2019: Young Expert of High-Level Talent Introduction at the National Level (Batch 15)
2025: First Prize in Science and Technology Award (Science and Technology Innovation Award, National Social Science and Technology Award Catalogue Number 0255) by the China Science and Technology Industrialization Promotion Association
2025: Lenovo's Highest Honor for University-Enterprise Cooperation, "Outstanding Cooperation Achievement Award" (reported by mainstream media such as People's Daily, People's Daily Online, Xinhua Finance, Guangming Daily, and Beijing Youth Daily)
2024: Youth Science and Technology Award by the Chinese Society of Vibration Engineering (National Social Science and Technology Award Catalogue Number 0310)
2024: First Prize in Science and Technology Award (Science and Technology Industrialization Award, National Social Science and Technology Award Catalogue Number 0255) by the China Science and Technology Industrialization Promotion Association
2023: Gold Medal in Invention and Entrepreneurship by the China Invention Association (National Social Science and Technology Award Catalogue Number 0123)
2024: Excellent Completion of National Natural Science Foundation of China General Project
2023: Outstanding Instructor in the 2nd China Graduate Engineering Management Case Competition
2023: Outstanding Associate Editor for IEEE Transactions on Instrumentation and Measurement
2022: First Prize in Shanghai Teaching Achievement Award
2021: "Excellent" in the Performance Evaluation by Shanghai Jiao Tong University
2021: Outstanding Class Advisor by Shanghai Jiao Tong University
2020: Third Prize in the Mechanical and Power Engineering College Young Teacher Teaching Competition
2019: Excellence Award in the China Advanced Technology Transformation and Application Competition
2018–Present: IEEE Transactions on Instrumentation and Measurement Outstanding Reviewer for six consecutive years, IOP Measurement Science and Technology Outstanding Reviewer, "Outstanding Review Expert" for three consecutive years by Chinese Journal of Scientific Instrument, Outstanding Reviewer by Science China Technological Sciences, Outstanding Review Expert by Journal of Ordnance Equipment Engineering, Outstanding Review Expert by Mechanical Strength, and Outstanding Reviewer by over 20 Elsevier international journals
2015–2017: Three-time Champion in the Hong Kong CSSA University Basketball League
2011–2015: Recipient of the Hong Kong PhD Fellowship Scheme (Hong Kong Research Grants Council, selected from 4,024 candidates in 103 countries at a rate of 4.15%), CityU Research Tuition Scholarship, CityU Chow Yei Ching School of Graduate Studies Scholarship (only two in engineering in 2012), and CityU Outstanding Academic Award
2010: Outstanding Graduate in Sichuan Province
2002: National Second-Level Athlete in 100m and 200m Sprint, Champion in the 100m race at the Jinniu District Games in Chengdu


Student Honor and Awards Guidance
2020–Present: National Scholarship for Graduate Students (nine students)
2024: First National Natural Science Foundation of China Youth Student Basic Research Project for Doctoral Students (Bingchang Hou)
2023: Nomination for the 8th Shanghai Jiao Tong University Graduate "Academic Star" (Bingchang Hou)
2022: Nomination for the 7th Shanghai Jiao Tong University Graduate "Academic Star" (Tongtong Yan)
2023: First Prize in the 2nd China Graduate Engineering Management Case Competition
2023: First Prize in the 18th "Dongfeng Nissan Cup" Tsinghua IE National Industrial Engineering Application Case Competition
2022: Special Prize in the 17th "Dongfeng Nissan Cup" Tsinghua IE National Industrial Engineering Application Case Competition
2021: Two First Prizes in the 16th "Dongfeng Nissan Cup" Tsinghua IE National Industrial Engineering Application Case Competition
2022: Title of Outstanding Graduate from Shanghai Municipal Ordinary Higher Education Institutions (two students)
2022: Outstanding Master's Thesis in the Mechanical and Power Engineering College
2021: First Prize in the 5th Shanghai Engineering Management Innovation Competition
2020: First Prize in the Shanghai University Students' Industrial Engineering Application and Innovation Competition
2024: Best Paper Award at the 8th International Conference on Condition Monitoring in Non-Stationary Operations (CMMNO 2024)
2024: Best Oral Presentation at the 7th International Conference on Mechanical, Electric and Industrial Engineering (MEIE 2024)
2022: Best Oral Presentation at the 5th International Conference on Mechanical, Electric and Industrial Engineering (MEIE 2022)
2022: Best Paper Award at the 3rd International Conference on Sensing, Measurement & Data Analytics in the Era of Artificial Intelligence
2021: Best Paper Award at the 14th International Conference on Damage Assessment of Structures