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Dong Wang

D-Index & Metrics

Computer Science

D-Index
57
Citations
10196
World Ranking
3904
National Ranking
523

Dong Wang publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Dong Wang sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 154 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Dong Wang D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Dong Wang sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Dong Wang is affiliated with Shanghai Jiao Tong University in China and has a primary focus in the field of Engineering, with extensive contributions across several key subfields. Their research output spans Control and Systems Engineering, Mechanical Engineering, Electrical and Electronic Engineering, Civil and Structural Engineering, and Mechanics of Materials.

The scientist's main research topics include:

  • Machine Fault Diagnosis Techniques
  • Fault Detection and Control Systems
  • Gear and Bearing Dynamics Analysis
  • Non-Destructive Testing Techniques
  • Reliability and Maintenance Optimization
  • Structural Health Monitoring Techniques
  • Advanced machining processes and optimization

Notable recent papers authored or coauthored by Dong Wang feature work in machine health monitoring, fault diagnosis, and battery lifespan prediction. These include:

  • The sum of weighted normalized square envelope: A unified framework for kurtosis, negative entropy, Gini index and smoothness index for machine health monitoring, 2020, Mechanical Systems and Signal Processing
  • Multi-scale deep intra-class transfer learning for bearing fault diagnosis, 2020, Reliability Engineering & System Safety
  • Image recognition of wind turbine blade damage based on a deep learning model with transfer learning and an ensemble learning classifier, 2020, Renewable Energy
  • Lifespan prediction of lithium-ion batteries based on various extracted features and gradient boosting regression tree model, 2020, Journal of Power Sources
  • Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis Under Unseen Conditions, 2021, IEEE Transactions on Industrial Informatics

Dong Wang frequently publishes in the following venues:

  • Mechanical Systems and Signal Processing
  • IEEE Transactions on Instrumentation and Measurement
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Journal of Physics Conference Series

Collaborative research partnerships include frequent coauthors such as Zhike Peng, Tangbin Xia, Lifeng Xi, Changqing Shen, and Tongtong Yan, reflecting a pattern of sustained academic collaboration.

In addition to journal articles, Dong Wang has contributed to book publications, including a title in the Springer series in reliability engineering: Advances in Reliability and Maintainability Methods and Engineering Applications (2023).

Best Publications

  • An enhanced Kurtogram method for fault diagnosis of rolling element bearings

    Dong Wang;Peter W. Tse;Kwok Leung Tsui

  • Prognostics and Health Management: A Review of Vibration Based Bearing and Gear Health Indicators

    Dong Wang;Kwok-Leung Tsui;Qiang Miao

  • Combined CNN-LSTM Network for State-of-Charge Estimation of Lithium-Ion Batteries

    Xiangbao Song;Fangfang Yang;Dong Wang;Kwok-Leung Tsui

  • The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement – Parts 1 and 2”

    Peter W. Tse;Dong Wang

  • Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter

    Dong Wang;Fangfang Yang;Kwok-Leung Tsui;Qiang Zhou

  • Multi-scale deep intra-class transfer learning for bearing fault diagnosis

    Xu Wang;Changqing Shen;Min Xia;Dong Wang

  • Fault diagnosis of rotating machinery based on the statistical parameters of wavelet packet paving and a generic support vector regressive classifier

    Changqing Shen;Changqing Shen;Dong Wang;Fanrang Kong;Peter W. Tse

  • Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings

    Dong Wang;Yang Zhao;Cai Yi;Cai Yi;Kwok-Leung Tsui

  • Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery

    Yumei Qi;Changqing Shen;Dong Wang;Juanjuan Shi

  • Some further thoughts about spectral kurtosis, spectral L2/L1 norm, spectral smoothness index and spectral Gini index for characterizing repetitive transients

    Dong Wang

  • A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile

    Fangfang Yang;Yinjiao Xing;Dong Wang;Kwok-Leung Tsui

  • Adversarial domain-invariant generalization: a generic domain-regressive framework for bearing fault diagnosis under unseen conditions

    Liang Chen;Qi Li;Changqing Shen;Jun Zhu

  • Lifespan prediction of lithium-ion batteries based on various extracted features and gradient boosting regression tree model

    Fangfang Yang;Dong Wang;Fan Xu;Zhelin Huang

  • The sum of weighted normalized square envelope: A unified framework for kurtosis, negative entropy, Gini index and smoothness index for machine health monitoring

    Dong Wang;Zhike Peng;Lifeng Xi

  • Voltage-temperature health feature extraction to improve prognostics and health management of lithium-ion batteries

    Jin-zhen Kong;Fangfang Yang;Xi Zhang;Ershun Pan

  • K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

    Dong Wang

  • Spectral L2 / L1 norm: A new perspective for spectral kurtosis for characterizing non-stationary signals

    Dong Wang

  • Robust health evaluation of gearbox subject to tooth failure with wavelet decomposition

    Dong Wang;Qiang Miao;Rui Kang

  • A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis

    Dong Wang;Dong Wang;Xuejun Zhao;Lin-Lin Kou;Yong Qin

  • Robustness Evaluation of Extended and Unscented Kalman Filter for Battery State of Charge Estimation

    Chao Huang;Zhenhua Wang;Zihan Zhao;Long Wang

  • The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection Part 2 of the two related manuscripts that have a joint title as "Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement—Parts 1 and 2"

    Peter W. Tse;Dong Wang

Frequent Co-Authors

Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Peter W. Tse
Peter W. Tse City University of Hong Kong
Changqing Shen
Changqing Shen Soochow University
Zhike Peng
Zhike Peng Shanghai Jiao Tong University
Yang Zhao
Yang Zhao Beijing Institute of Technology
Lifeng Xi
Lifeng Xi Shanghai Jiao Tong University
Zhongkui Zhu
Zhongkui Zhu Soochow University
Chuan Li
Chuan Li Chongqing Technology and Business University
Hong-Zhong Huang
Hong-Zhong Huang University of Electronic Science and Technology of China
Michael Pecht
Michael Pecht University of Maryland, College Park

External Links

Personal website of Dong Wang Google Scholar page

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Best Scientists Citing Dong Wang

Michael Pecht

Michael Pecht

University of Maryland, College Park

Publications: 42

Changqing Shen

Changqing Shen

Soochow University

Publications: 37

Qingbo He

Qingbo He

Shanghai Jiao Tong University

Publications: 37

Zhongkui Zhu

Zhongkui Zhu

Soochow University

Publications: 37

Jing Lin

Jing Lin

Beihang University

Publications: 34

Ming Zhao

Ming Zhao

Xi'an Jiaotong University

Publications: 27

Chuan Li

Chuan Li

Chongqing Technology and Business University

Publications: 26

Siliang Lu

Siliang Lu

Anhui University

Publications: 25

Xuefeng Chen

Xuefeng Chen

Xi'an Jiaotong University

Publications: 22

Yaguo Lei

Yaguo Lei

Xi'an Jiaotong University

Publications: 21

Jong-Myon Kim

Jong-Myon Kim

University of Ulsan

Publications: 21

Xingxing Jiang

Xingxing Jiang

Soochow University

Publications: 20

Kwok-Leung Tsui

Kwok-Leung Tsui

Virginia Tech

Publications: 19

Ruqiang Yan

Ruqiang Yan

Xi'an Jiaotong University

Publications: 19

Ming J. Zuo

Ming J. Zuo

University of Alberta

Publications: 19

Fang Liu

Fang Liu

Beihang University

Publications: 17

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