World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
8821
World Ranking
5408
National Ranking
2471

Zhengming Ding 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 Zhengming Ding 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: 171 publications — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Zhengming Ding 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 Zhengming Ding 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

Zhengming Ding is affiliated with Tulane University in the United States. Their research primarily centers on computer science, with a focus on artificial intelligence and computer vision. The scientist has published extensively in related subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Radiology, Nuclear Medicine and Imaging, and Cancer Research.

The work of Zhengming Ding covers a broad spectrum of topics within machine learning and its applications, especially:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Machine Learning and Extreme Learning Machines (ELM)
  • Video Surveillance and Tracking Methods
  • Human Pose and Action Recognition
  • Advanced Neural Network Applications
  • Cancer-related molecular mechanisms research

Frequent co-authors collaborating with Zhengming Ding include:

  • Taotao Jing
  • Haifeng Xia
  • Gan Sun
  • Jihun Hamm
  • Yang Cong

The main publication venues for Zhengming Ding's research include:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)

Selected recent publications by Zhengming Ding demonstrate a focus on machine learning techniques applied to vision and biomedical data:

  • "3D Human Pose Estimation with Spatial and Temporal Transformers," 2021, presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification," 2021, published in Nature Communications
  • "Maximum Density Divergence for Domain Adaptation," 2020, featured in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Adaptive Adversarial Network for Source-free Domain Adaptation," 2021, presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Deep Residual Correction Network for Partial Domain Adaptation," 2020, published in IEEE Transactions on Pattern Analysis and Machine Intelligence

With a publication record focused heavily on domain adaptation methods and multimodal data integration, Zhengming Ding's work contributes to advances in transfer learning frameworks and biomedical informatics. Their research often involves neural networks and advanced machine learning architectures applied to diverse data types including images and molecular datasets.

Best Publications

  • MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification

    Tongxin Wang;Wei Shao;Zhi Huang;Zhi Huang;Haixu Tang

  • Multi-View Clustering via Deep Matrix Factorization.

    Handong Zhao;Zhengming Ding;Yun Fu

  • Leveraging the Invariant Side of Generative Zero-Shot Learning

    Jingjing Li;Mengmeng Jing;Ke Lu;Zhengming Ding

  • Maximum Density Divergence for Domain Adaptation

    Jingjing Li;Erpeng Chen;Zhengming Ding;Lei Zhu

  • Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation

    Shuang Li;Shiji Song;Gao Huang;Zhengming Ding

  • Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning

    Unknown

  • Robust Transfer Metric Learning for Image Classification

    Zhengming Ding;Yun Fu

  • Adaptive Adversarial Network for Source-Free Domain Adaptation

    Haifeng Xia;Handong Zhao;Zhengming Ding

  • Low-Rank Common Subspace for Multi-view Learning

    Zhengming Ding;Yun Fu

  • Deep Residual Correction Network for Partial Domain Adaptation

    Shuang Li;Chi Harold Liu;Qiuxia Lin;Qi Wen

  • Partial Multi-view Clustering via Consistent GAN

    Qianqian Wang;Zhengming Ding;Zhiqiang Tao;Quanxue Gao

  • Leveraging the Invariant Side of Generative Zero-Shot Learning

    Jingjing Li;Mengmeng Jin;Ke Lu;Zhengming Ding

  • Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation.

    Jiahua Dong;Yang Cong;Gan Sun;Zhen Fang

  • Generative Partial Multi-View Clustering With Adaptive Fusion and Cycle Consistency

    Qianqian Wang;Zhengming Ding;Zhiqiang Tao;Quanxue Gao

  • From Ensemble Clustering to Multi-View Clustering.

    Zhiqiang Tao;Hongfu Liu;Sheng Li;Zhengming Ding

  • Deep Domain Generalization With Structured Low-Rank Constraint

    Zhengming Ding;Yun Fu

  • Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning

    Zhengming Ding;Ming Shao;Yun Fu

  • Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation

    Zhengming Ding;Sheng Li;Ming Shao;Yun Fu

  • Generative Multi-View Human Action Recognition

    Lichen Wang;Zhengming Ding;Zhiqiang Tao;Yunyu Liu

  • Latent low-rank transfer subspace learning for missing modality recognition

    Zhengming Ding;Ming Shao;Yun Fu

  • Divergence-agnostic Unsupervised Domain Adaptation by Adversarial Attacks.

    Jingjing Li;Zhekai Du;Lei Zhu;Zhengming Ding

  • Joint Adversarial Domain Adaptation

    Shuang Li;Chi Harold Liu;Binhui Xie;Limin Su

  • Consensus Regularized Multi-View Outlier Detection

    Handong Zhao;Hongfu Liu;Zhengming Ding;Yun Fu

Frequent Co-Authors

Yun Fu
Yun Fu Northeastern University
Sheng Li
Sheng Li University of Virginia
Lei Zhu
Lei Zhu Tongji University
Yang Cong
Yang Cong Chinese Academy of Sciences
Jingjing Li
Jingjing Li Chinese University of Hong Kong
Ke Lu
Ke Lu Chinese Academy of Sciences
Chi Harold Liu
Chi Harold Liu Beijing Institute of Technology
Gao Huang
Gao Huang Tsinghua University
Zi Huang
Zi Huang University of Queensland
Haixu Tang
Haixu Tang Indiana University

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