World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
25338
World Ranking
1567
National Ranking
818

Robert X. Gao 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 Robert X. Gao 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: 333 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Robert X. Gao 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 Robert X. Gao 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: 73 D-Index — 89th percentile

89% 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

  • 2006 - Fellow of the American Society of Mechanical Engineers

Overview

Robert X. Gao is affiliated with Case Western Reserve University in the United States and has a research focus primarily in the field of Engineering. Within this broad area, their work spans multiple subfields, including Industrial and Manufacturing Engineering, Control and Systems Engineering, Mechanical Engineering, Electrical and Electronic Engineering, and Biomedical Engineering.

The scientist's research topics reflect a concentration on manufacturing processes and systems. Key topics in their publications include:

  • Advanced machining processes and optimization
  • Industrial Vision Systems and Defect Detection
  • Manufacturing Process and Optimization
  • Machine Fault Diagnosis Techniques
  • Digital Transformation in Industry
  • Fault Detection and Control Systems
  • Advanced Machining and Optimization Techniques

Robert X. Gao has contributed extensively to several prominent publication venues. The most frequent venues are:

  • Journal of Manufacturing Systems
  • CIRP Annals
  • Manufacturing Letters
  • Procedia Manufacturing
  • Robotics and Computer-Integrated Manufacturing

Their notable recent papers include:

  • Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook, published in 2020 in the Journal of Manufacturing Science and Engineering
  • WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis, published in 2021 in IEEE Transactions on Systems Man and Cybernetics Systems
  • Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm, published in 2021 in the Journal of Manufacturing Systems
  • Physics guided neural network for machining tool wear prediction, published in 2020 in the Journal of Manufacturing Systems
  • Wavelet transform for rotary machine fault diagnosis:10 years revisited, published in 2023 in Mechanical Systems and Signal Processing

Frequent collaborators in their research include:

  • Jianjing Zhang
  • Lihui Wang
  • Clayton Cooper
  • Ihab Ragai
  • Xun Xu

Robert X. Gao was recognized as a Fellow of the American Society of Mechanical Engineers in 2006.

Best Publications

  • Deep learning and its applications to machine health monitoring

    Rui Zhao;Ruqiang Yan;Zhenghua Chen;Kezhi Mao

  • Deep learning for smart manufacturing: Methods and applications

    Jinjiang Wang;Yulin Ma;Laibin Zhang;Robert X. Gao

  • Wavelets for fault diagnosis of rotary machines: A review with applications

    Ruqiang Yan;Robert X. Gao;Xuefeng Chen

  • PCA-based feature selection scheme for machine defect classification

    A. Malhi;R.X. Gao

  • A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

    Dazhong Wu;Connor Jennings;Janis Terpenny;Robert X. Gao

  • Approximate Entropy as a diagnostic tool for machine health monitoring

    Ruqiang Yan;Robert X. Gao

  • Wavelets: Theory and Applications for Manufacturing

    Robert X. Gao;Ruqiang Yan

  • Symbiotic human-robot collaborative assembly

    L. Wang;R. Gao;J. Váncza;J. Váncza;J. Krüger;J. Krüger

  • WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis

    Tianfu Li;Zhibin Zhao;Chuang Sun;Li Cheng

  • Digital Twin for rotating machinery fault diagnosis in smart manufacturing

    Jinjiang Wang;Lunkuan Ye;Robert X. Gao;Chen Li

  • Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook

    Jorge F. Arinez;Qing Chang;Robert X. Gao;Chengying Xu

  • Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring

    Ruqiang Yan;R.X. Gao

  • Cloud-enabled prognosis for manufacturing

    Robert Gao;Lihui Wang;Roberto Teti;David Dornfeld

  • Long short-term memory for machine remaining life prediction

    Jianjing Zhang;Peng Wang;Ruqiang Yan;Robert X. Gao

  • Permutation entropy: A nonlinear statistical measure for status characterization of rotary machines

    Ruqiang Yan;Yongbin Liu;Robert X. Gao

  • Machine learning-based image processing for on-line defect recognition in additive manufacturing

    Alessandra Caggiano;Jianjing Zhang;Vittorio Alfieri;Fabrizia Caiazzo

  • DCNN-Based Multi-Signal Induction Motor Fault Diagnosis

    Siyu Shao;Ruqiang Yan;Yadong Lu;Peng Wang

  • Prognosis of Defect Propagation Based on Recurrent Neural Networks

    A Malhi;Ruqiang Yan;R X Gao

  • A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing

    Dazhong Wu;Shaopeng Liu;Li Zhang;Janis Terpenny

  • A New Intelligent Bearing Fault Diagnosis Method Using SDP Representation and SE-CNN

    Hui Wang;Jiawen Xu;Ruqiang Yan;Robert X. Gao

  • Performance enhancement of ensemble empirical mode decomposition

    Jian Zhang;Ruqiang Yan;Robert X. Gao;Zhihua Feng

Frequent Co-Authors

Ruqiang Yan
Ruqiang Yan Xi'an Jiaotong University
Patty S. Freedson
Patty S. Freedson University of Massachusetts Amherst
Lihui Wang
Lihui Wang Royal Institute of Technology
Jian Cao
Jian Cao Northwestern University
Jiong Tang
Jiong Tang University of Connecticut
Xuefeng Chen
Xuefeng Chen Xi'an Jiaotong University
Xingwu Zhang
Xingwu Zhang Xi'an Jiaotong University
Dazhong Wu
Dazhong Wu University of Central Florida
Qingbo He
Qingbo He Shanghai Jiao Tong University
Soundar R. T. Kumara
Soundar R. T. Kumara Pennsylvania State University

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