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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
20724
World Ranking
1291
National Ranking
44

Ming J. Zuo 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 Ming J. Zuo 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: 364 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Ming J. Zuo 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 Ming J. Zuo 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: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2023 - Research.com Computer Science in Canada Leader Award
  • 2022 - Research.com Computer Science in Canada Leader Award
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering

Overview

Ming J. Zuo is affiliated with the University of Alberta in Canada and specializes primarily in the field of Engineering. Their research output encompasses a broad range of topics within this domain, focusing significantly on Mechanical Engineering, Control and Systems Engineering, Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering, and Mechanics of Materials.

Their work spans several main research topics, including:

  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Electrocatalysts for Energy Conversion
  • Fuel Cells and Related Materials
  • Fault Detection and Control Systems
  • Non-Destructive Testing Techniques
  • Advanced Battery Technologies Research

Ming J. Zuo has contributed to numerous scientific venues, with frequent publications in:

  • Mechanical Systems and Signal Processing
  • 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM)
  • Nature Communications
  • Measurement
  • Reliability Engineering & System Safety

Their significant recent publications include:

  • "Electrochemical deposition as a universal route for fabricating single-atom catalysts" (2020, Nature Communications)
  • "Turning main-group element magnesium into a highly active electrocatalyst for oxygen reduction reaction" (2020, Nature Communications)
  • "Multibranch and Multiscale CNN for Fault Diagnosis of Wheelset Bearings Under Strong Noise and Variable Load Condition" (2020, IEEE Transactions on Industrial Informatics)
  • "Physics-Informed LSTM hyperparameters selection for gearbox fault detection" (2022, Mechanical Systems and Signal Processing)
  • "Scaling-Basis Chirplet Transform" (2020, IEEE Transactions on Industrial Electronics)

Throughout their research career, Ming J. Zuo has collaborated frequently with several co-authors including Zhigang Tian, Zhiliang Liu, Hai-Wei Liang, Zhirong Zhang, and Peiyu Ma.

Ming J. Zuo has been recognized by the Canadian Academy of Engineering with an award, details of which are unspecified.

Best Publications

  • Optimal Reliability Modeling: Principles and Applications

    Way Kuo;Ming J. Zuo

  • Current status of machine prognostics in condition-based maintenance: a review

    Ying Peng;Ming Dong;Ming Jian Zuo

  • Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection

    Geoff L. McDonald;Qing Zhao;Ming J. Zuo

  • GEARBOX FAULT DIAGNOSIS USING ADAPTIVE WAVELET FILTER

    J. Lin;M.J. Zuo

  • Gearbox fault detection using Hilbert and wavelet packet transform

    Xianfeng Fan;Ming J. Zuo

  • An efficient method for reliability evaluation of multistate networks given all minimal path vectors

    Ming J. Zuo;Zhigang Tian;Hong-Zhong Huang

  • Gear crack level identification based on weighted K nearest neighbor classification algorithm

    Yaguo Lei;Ming J. Zuo

  • Predicting Remaining Useful Life of Rolling Bearings Based on Deep Feature Representation and Transfer Learning

    Wentao Mao;Jianliang He;Ming J. Zuo

  • Bayesian reliability analysis for fuzzy lifetime data

    Hong-Zhong Huang;Ming J. Zuo;Zhan-Quan Sun

  • Multibranch and Multiscale CNN for Fault Diagnosis of Wheelset Bearings Under Strong Noise and Variable Load Condition

    Dandan Peng;Huan Wang;Zhiliang Liu;Wei Zhang

  • A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis

    Ning-Cong Xiao;Ning-Cong Xiao;Ming Jian Zuo;Ming Jian Zuo;Chengning Zhou

  • A multidimensional hybrid intelligent method for gear fault diagnosis

    Yaguo Lei;Ming J. Zuo;Zhengjia He;Yanyang Zi

  • Inverse Gaussian process models for degradation analysis: A Bayesian perspective

    Weiwen Peng;Yanfeng Li;Yuanjian Yang;Hong-Zhong Huang

  • Vibration signal modeling of a planetary gear set for tooth crack detection

    Xihui Liang;Ming J. Zuo;Mohammad R. Hoseini

  • Reliability evaluation of multi-state weighted k-out-of-n systems

    Wei Li;Ming Jian Zuo

  • Fault diagnosis of machines based on D-S evidence theory. Part 1: D-S evidence theory and its improvement

    Xianfeng Fan;Ming J. Zuo

  • Generalized multi-state k-out-of-n:G systems

    J. Huang;M.J. Zuo;Y. Wu

  • Linear and Nonlinear Preventive Maintenance Models

    Shaomin Wu;M.J. Zuo

  • Posbist fault tree analysis of coherent systems

    Hong-Zhong Huang;Xin Tong;Ming Jian Zuo

  • Approaches for reliability modeling of continuous-state devices

    M.J. Zuo;Renyan Jiang;R.C.M. Yam

Frequent Co-Authors

Hong-Zhong Huang
Hong-Zhong Huang University of Electronic Science and Technology of China
Xihui Liang
Xihui Liang University of Manitoba
Zhipeng Feng
Zhipeng Feng University of Science and Technology Beijing
Richard C.M. Yam
Richard C.M. Yam City University of Hong Kong
Fulei Chu
Fulei Chu Tsinghua University
Yaguo Lei
Yaguo Lei Xi'an Jiaotong University
Yu Liu
Yu Liu University of Electronic Science and Technology of China
Zhengjia He
Zhengjia He Xi'an Jiaotong University
Yan-Feng Li
Yan-Feng Li University of Electronic Science and Technology of China
Yi Ding
Yi Ding Zhejiang University

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