World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
8010
World Ranking
10078
National Ranking
1257

Wenbing Huang 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 Wenbing Huang 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: 98 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Wenbing Huang 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 Wenbing Huang 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Wenbing Huang is affiliated with Renmin University of China and specializes in the field of Computer Science. Their work encompasses various subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Materials Chemistry, and Computational Theory and Mathematics.

The research topics prominently addressed by Wenbing Huang include:

  • Advanced Graph Neural Networks
  • Machine Learning in Materials Science
  • Advanced Neural Network Applications
  • Computational Drug Discovery Methods
  • Topic Modeling
  • Protein Structure and Dynamics
  • Reinforcement Learning in Robotics

Wenbing Huang has contributed to multiple recent publications across prestigious venues. Selected papers highlight the scope of their research:

  • "Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks", 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Self-Supervised Graph Transformer on Large-Scale Molecular Data", 2020, arXiv (Cornell University)
  • "Multimodal Token Fusion for Vision Transformers", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models", 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Deep Multimodal Fusion by Channel Exchanging", 2020, arXiv (Cornell University)

The frequent publication venues for Wenbing Huang's work include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Sensors Journal
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Collaboration is an important aspect of Wenbing Huang's research activity. Frequent co-authors are:

  • Fuchun Sun
  • Yu Rong
  • Tingyang Xu
  • Junzhou Huang
  • Jiaqi Han

This profile covers Wenbing Huang's research interests, key publications, principal collaborators, and predominant venues of publication. The data reflects a concentration on graph neural networks, machine learning applications in diverse scientific domains, and advances in neural network methodologies.

Best Publications

  • DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

    Yu Rong;Wenbing Huang;Tingyang Xu;Junzhou Huang

  • Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks

    Tian Bian;Xi Xiao;Tingyang Xu;Peilin Zhao

  • Graph Representation Learning via Graphical Mutual Information Maximization

    Zhen Peng;Wenbing Huang;Minnan Luo;Qinghua Zheng

  • Graph Convolutional Networks for Temporal Action Localization

    Runhao Zeng;Wenbing Huang;Chuang Gan;Mingkui Tan

  • Progressive Feature Alignment for Unsupervised Domain Adaptation

    Chaoqi Chen;Weiping Xie;Wenbing Huang;Yu Rong

  • Self-Supervised Graph Transformer on Large-Scale Molecular Data

    Yu Rong;Yatao Bian;Tingyang Xu;Weiyang Xie

  • A Fast and Accurate One-Stage Approach to Visual Grounding

    Zhengyuan Yang;Boqing Gong;Liwei Wang;Wenbing Huang

  • Adaptive Sampling Towards Fast Graph Representation Learning

    Wenbing Huang;Tong Zhang;Yu Rong;Junzhou Huang

  • Dense Regression Network for Video Grounding

    Runhao Zeng;Haoming Xu;Wenbing Huang;Peihao Chen

  • Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering

    Xiangpeng Li;Jingkuan Song;Lianli Gao;Xianglong Liu

  • End-to-End Learning of Motion Representation for Video Understanding

    Lijie Fan;Wenbing Huang;Chuang Gan;Stefano Ermon

  • Deep Feature Pyramid Reconfiguration for Object Detection

    Tao Kong;Fuchun Sun;Wenbing Huang;Huaping Liu

  • Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

    Runfa Chen;Wenbing Huang;Binghui Huang;Fuchun Sun

  • Multimodal Token Fusion for Vision Transformers

    Unknown

  • A simple, real-time range camera

    A. Pentland;T. Darrell;M. Turk;W. Huang

  • A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models

    Heng Chang;Yu Rong;Tingyang Xu;Wenbing Huang

  • Semi-Supervised Graph Classification: A Hierarchical Graph Perspective

    Jia Li;Yu Rong;Hong Cheng;Helen Meng

  • Deep Multimodal Fusion by Channel Exchanging

    Yikai Wang;Wenbing Huang;Fuchun Sun;Tingyang Xu

  • Weakly Supervised Dense Event Captioning in Videos

    Xuguang Duan;Wenbing Huang;Chuang Gan;Jingdong Wang

  • Breaking Winner-Takes-All: Iterative-Winners-Out Networks for Weakly Supervised Temporal Action Localization

    Runhao Zeng;Chuang Gan;Peihao Chen;Wenbing Huang

  • Graph Convolutional Networks for Temporal Action Localization

    Runhao Zeng;Wenbing Huang;Mingkui Tan;Yu Rong

Frequent Co-Authors

Junzhou Huang
Junzhou Huang The University of Texas at Arlington
Fuchun Sun
Fuchun Sun Tsinghua University
Chuang Gan
Chuang Gan University of Massachusetts Amherst
Huaping Liu
Huaping Liu Tsinghua University
Wenwu Zhu
Wenwu Zhu Tsinghua University
Mingkui Tan
Mingkui Tan South China University of Technology
Tong Zhang
Tong Zhang University of Illinois at Urbana-Champaign
Peilin Zhao
Peilin Zhao Tencent (China)
Boqing Gong
Boqing Gong Google (United States)
Mehrtash Harandi
Mehrtash Harandi Monash University

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