World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
561859
World Ranking
1529
National Ranking
795

Kaiming He 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 Kaiming He 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 96 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Kaiming He 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 Kaiming He sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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.

Overview

Kaiming He is a researcher primarily affiliated with Facebook in the United States. Their work centers on the field of computer science, with a specific focus on computer vision and pattern recognition. They have contributed extensively to the advancement of artificial intelligence and related subfields, including electrical and electronic engineering, automotive engineering, and information systems.

The scientist's research topics cover a range of advanced areas within machine learning and neural networks. Their main fields of study include:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Advanced Memory and Neural Computing
  • Machine Learning and Data Classification

Their publication record includes significant papers in well-known venues, reflecting their ongoing contributions to both theoretical and applied aspects of vision and learning systems. Notable recent papers include:

  • "Improved Baselines with Momentum Contrastive Learning," 2020, arXiv (Cornell University)
  • "An Empirical Study of Training Self-Supervised Vision Transformers," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Exploring Simple Siamese Representation Learning," 2020, arXiv (Cornell University)
  • "Masked Autoencoders Are Scalable Vision Learners," 2021, arXiv (Cornell University)
  • "Masked Autoencoders As Spatiotemporal Learners," 2022, arXiv (Cornell University)

Frequent publication venues for Kaiming He include:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Small
  • The Journal of Supercomputing
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The scientist has collaborated with several researchers repeatedly. Their frequent coauthors are:

  • Ross Girshick
  • Saining Xie
  • Yanghao Li
  • Xinlei Chen
  • Piotr Dollár

Best Publications

  • Deep Residual Learning for Image Recognition

    Kaiming He;Xiangyu Zhang;Shaoqing Ren;Jian Sun

  • Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

    Shaoqing Ren;Kaiming He;Ross Girshick;Jian Sun

  • Mask R-CNN

    Kaiming He;Georgia Gkioxari;Piotr Dollar;Ross Girshick

  • Feature Pyramid Networks for Object Detection

    Tsung-Yi Lin;Piotr Dollar;Ross Girshick;Kaiming He

  • Focal Loss for Dense Object Detection

    Tsung-Yi Lin;Priya Goyal;Ross Girshick;Kaiming He

  • Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

    Kaiming He;Xiangyu Zhang;Shaoqing Ren;Jian Sun

  • Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

    Kaiming He;Xiangyu Zhang;Shaoqing Ren;Jian Sun

  • Momentum Contrast for Unsupervised Visual Representation Learning

    Kaiming He;Haoqi Fan;Yuxin Wu;Saining Xie

  • Aggregated Residual Transformations for Deep Neural Networks

    Saining Xie;Ross Girshick;Piotr Dollar;Zhuowen Tu

  • Identity Mappings in Deep Residual Networks

    Kaiming He;Xiangyu Zhang;Shaoqing Ren;Jian Sun

  • Non-local Neural Networks

    Xiaolong Wang;Ross Girshick;Abhinav Gupta;Kaiming He

  • Image Super-Resolution Using Deep Convolutional Networks

    Chao Dong;Chen Change Loy;Kaiming He;Xiaoou Tang

  • Focal Loss for Dense Object Detection

    Tsung-Yi Lin;Priya Goyal;Ross Girshick;Kaiming He

  • Single Image Haze Removal Using Dark Channel Prior

    Kaiming He;Jian Sun;Xiaoou Tang

  • Single image haze removal using dark channel prior

    Kaiming He;Jian Sun;Xiaoou Tang

  • Guided image filtering

    Kaiming He;Jian Sun;Xiaoou Tang

  • R-FCN: Object Detection via Region-based Fully Convolutional Networks

    Jifeng Dai;Yi Li;Kaiming He;Jian Sun

  • Guided Image Filtering

    Kaiming He;Jian Sun;Xiaoou Tang

  • Learning a Deep Convolutional Network for Image Super-Resolution

    Chao Dong;Chen Change Loy;Kaiming He;Xiaoou Tang

  • Mask R-CNN

    Kaiming He;Georgia Gkioxari;Piotr Dollar;Ross Girshick

Frequent Co-Authors

Jian Sun
Jian Sun Megvii
Ross Girshick
Ross Girshick Facebook (United States)
Piotr Dollar
Piotr Dollar Facebook (United States)
Jifeng Dai
Jifeng Dai Tsinghua University
Xiaoou Tang
Xiaoou Tang Chinese University of Hong Kong
Christoph Feichtenhofer
Christoph Feichtenhofer Meta Platforms, Inc.
Xiaolong Wang
Xiaolong Wang University of California, San Diego
Tsung-Yi Lin
Tsung-Yi Lin Nvidia (United States)
Laurens van der Maaten
Laurens van der Maaten Facebook (United States)

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