World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
64
Citations
15575
World Ranking
2614
National Ranking
354

Ran 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 Ran 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: 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: 285 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Ran 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 Ran He 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: 64 D-Index — 82nd percentile

82% 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

  • 2020 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to biometrics, face recognition, and applications

Overview

Ran He is affiliated with the Chinese Academy of Sciences in China and has a significant body of research in Computer Science, particularly focusing on Computer Vision and Pattern Recognition. Their work spans several subfields including Artificial Intelligence, Signal Processing, Radiology, Nuclear Medicine and Imaging, and Neurology.

The scientist has published extensively, contributing to a diverse set of topics such as:

  • Generative Adversarial Networks and Image Synthesis
  • Face recognition and analysis
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Advanced Image Processing Techniques
  • Video Surveillance and Tracking Methods

Ran He's recent papers demonstrate active engagement with contemporary research problems and include:

  • Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (2021), presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Deep Audio-visual Learning: A Survey (2021), published in International Journal of Automation and Computing
  • ShipRSImageNet: A Large-Scale Fine-Grained Dataset for Ship Detection in High-Resolution Optical Remote Sensing Images (2021), published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • A Comprehensive Survey on Test-Time Adaptation Under Distribution Shifts (2024), published in International Journal of Computer Vision

Frequent publication venues for Ran He include:

  • arXiv (Cornell University)
  • IEEE Transactions on Information Forensics and Security
  • International Journal of Computer Vision
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Pattern Recognition

Collaborations have been an important aspect of Ran He's research output. Notable frequent co-authors include:

  • Huaibo Huang
  • Jian Liang
  • Tieniu Tan
  • Chaoyou Fu
  • Junchi Yu

Ran He has been recognized with awards including becoming a Fellow of the International Association for Pattern Recognition (IAPR) in 2020 for contributions to biometrics, face recognition, and applications.

Best Publications

  • A Light CNN for Deep Face Representation With Noisy Labels

    Xiang Wu;Ran He;Zhenan Sun;Tieniu Tan

  • Maximum Correntropy Criterion for Robust Face Recognition

    Ran He;Wei-Shi Zheng;Bao-Gang Hu

  • Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

    Rui Huang;Shu Zhang;Tianyu Li;Ran He

  • Wavelet-SRNet: A Wavelet-Based CNN for Multi-scale Face Super Resolution

    Huaibo Huang;Ran He;Zhenan Sun;Tieniu Tan

  • Robust Principal Component Analysis Based on Maximum Correntropy Criterion

    Ran He;Bao-Gang Hu;Wei-Shi Zheng;Xiang-Wei Kong

  • Half-Quadratic-Based Iterative Minimization for Robust Sparse Representation

    Ran He;Wei-Shi Zheng;Tieniu Tan;Zhenan Sun

  • Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval

    Kaiye Wang;Ran He;Liang Wang;Wei Wang

  • Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition

    Ran He;Xiang Wu;Zhenan Sun;Tieniu Tan

  • Robust view transformation model for gait recognition

    Shuai Zheng;Junge Zhang;Kaiqi Huang;Ran He

  • MEAD: A Large-Scale Audio-Visual Dataset for Emotional Talking-Face Generation

    Kaisiyuan Wang;Qianyi Wu;Linsen Song;Linsen Song;Zhuoqian Yang

  • Learning Coupled Feature Spaces for Cross-Modal Matching

    Kaiye Wang;Ran He;Wei Wang;Liang Wang

  • Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer

    Jian Liang;Dapeng Hu;Yunbo Wang;Ran He

  • IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis

    Huaibo Huang;zhihang li;Ran He;Zhenan Sun

  • Deep Aesthetic Quality Assessment With Semantic Information

    Yueying Kao;Ran He;Kaiqi Huang

  • Deep Supervised Discrete Hashing

    Qi Li;Zhenan Sun;Ran He;Tieniu Tan

  • Pose-Guided Photorealistic Face Rotation

    Yibo Hu;Xiang Wu;Bing Yu;Ran He

  • A Lightened CNN for Deep Face Representation

    Xiang Wu;Ran He;Zhenan Sun

  • l 2, 1 Regularized correntropy for robust feature selection

    Ran He;Tieniu Tan;Liang Wang;Wei-Shi Zheng

  • Learning Invariant Deep Representation for NIR-VIS Face Recognition

    Ran He;Xiang Wu;Zhenan Sun;Tieniu Tan

  • PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer

    Wentao Jiang;Si Liu;Chen Gao;Jie Cao

  • Two-Stage Nonnegative Sparse Representation for Large-Scale Face Recognition

    Ran He;Wei-Shi Zheng;Bao-Gang Hu;Xiang-Wei Kong

  • Gabor Ordinal Measures for Face Recognition

    Zhenhua Chai;Zhenan Sun;Heydi Mendez-Vazquez;Ran He

  • Geometry Guided Adversarial Facial Expression Synthesis

    Lingxiao Song;Zhihe Lu;Ran He;Zhenan Sun

Frequent Co-Authors

Zhenan Sun
Zhenan Sun Chinese Academy of Sciences
Tieniu Tan
Tieniu Tan Chinese Academy of Sciences
Bao-Gang Hu
Bao-Gang Hu Chinese Academy of Sciences
Wei-Shi Zheng
Wei-Shi Zheng Sun Yat-sen University
Stan Z. Li
Stan Z. Li Westlake University
Zhen Lei
Zhen Lei Chinese Academy of Sciences
Shengcai Liao
Shengcai Liao United Arab Emirates University
Kaiqi Huang
Kaiqi Huang Chinese Academy of Sciences
Jiashi Feng
Jiashi Feng ByteDance
Shuicheng Yan
Shuicheng Yan National University of Singapore

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