World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
13175
World Ranking
2949
National Ranking
402

S. Kevin Zhou 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 S. Kevin Zhou 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: 224 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

S. Kevin Zhou 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 S. Kevin Zhou 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: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Overview

S. Kevin Zhou is affiliated with the University of Science and Technology of China in China. Their research spans multiple intersecting domains including computer science, medicine, and engineering. The main fields of study in their body of work comprise computer science, medicine, and engineering, with significant emphasis on subfields such as radiology, nuclear medicine and imaging, computer vision and pattern recognition, biomedical engineering, artificial intelligence, and electrical and electronic engineering.

The scientist's research topics cover a range of areas critical to medical imaging and analysis. Key topics explored include radiomics and machine learning in medical imaging, medical imaging techniques and applications, advanced X-ray and CT imaging, COVID-19 diagnosis using artificial intelligence, medical imaging and analysis, advanced neural network applications, and medical image segmentation techniques.

Notable recent papers by S. Kevin Zhou include:

  • Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives (2023, Medical Image Analysis)
  • Knowledge matters: Chest radiology report generation with general and specific knowledge (2022, Medical Image Analysis)
  • Rubik's Cube+: A self-supervised feature learning framework for 3D medical image analysis (2020, Medical Image Analysis)
  • Label-Free Segmentation of COVID-19 Lesions in Lung CT (2021, IEEE Transactions on Medical Imaging)
  • Deep learning to segment pelvic bones: large-scale CT datasets and baseline models (2021, International Journal of Computer Assisted Radiology and Surgery)

S. Kevin Zhou has collaborated frequently with multiple co-authors, including Heqin Zhu, Fenghe Tang, Qingsong Yao, and Zihang Jiang. These collaborators have contributed considerably to the shared research output, with some publications reflecting close ongoing partnerships.

The scientist's work has appeared repeatedly in key publication venues, predominantly in arXiv (Cornell University), Medical Image Analysis, IEEE Transactions on Medical Imaging, Lecture Notes in Computer Science, and npj Digital Medicine. The distribution of publications indicates a strong presence in both open-access preprints and peer-reviewed journals specialized in medical imaging and computer science.

Beyond journal articles, S. Kevin Zhou has contributed to book publications with Springer Science+Business Media, featuring in volumes related to Medical Image Computing and Computer Assisted Intervention presented at MICCAI 2020.

Best Publications

  • A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

    S. Kevin Zhou;Hayit Greenspan;Christos Davatzikos;James S. Duncan

  • Visual tracking and recognition using appearance-adaptive models in particle filters

    Shaohua Kevin Zhou;R. Chellappa;B. Moghaddam

  • FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition

    Hui Ding;Shaohua Kevin Zhou;Rama Chellappa

  • Probabilistic recognition of human faces from video

    Shaohua Zhou;Volker Krueger;Rama Chellappa

  • Combo loss: Handling input and output imbalance in multi-organ segmentation

    Saeid Asgari Taghanaki;Saeid Asgari Taghanaki;Yefeng Zheng;S. Kevin Zhou;Bogdan Georgescu

  • Shallow Attention Network for Polyp Segmentation.

    Jun Wei;Yiwen Hu;Yiwen Hu;Ruimao Zhang;Zhen Li

  • From sample similarity to ensemble similarity: probabilistic distance measures in reproducing kernel Hilbert space

    S.K. Zhou;R. Chellappa

  • Deep Learning for Medical Image Analysis

    S. Kevin Zhou;Hayit Greenspan;Dinggang Shen

  • Learning to Prune Filters in Convolutional Neural Networks

    Qiangui Huang;Kevin Zhou;Suya You;Ulrich Neumann

  • Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

    Dong Yang;Daguang Xu;S. Kevin Zhou;Bogdan Georgescu

  • Hierarchical, learning-based automatic liver segmentation

    Haibin Ling;S.K. Zhou;Yefeng Zheng;B. Georgescu

  • Deep reinforcement learning in medical imaging: A literature review

    S. Kevin Zhou;T. Hoang Ngan Le;Khoa Luu;Hien Van Nguyen

  • Automatic Liver Segmentation Using Adversarial Image-to-Image Network

    Dong Yang;Daguang Xu;Shaohua Kevin Zhou;Bogdan Georgescu

  • ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

    Haofu Liao;Wei-An Lin;S. Kevin Zhou;Jiebo Luo

  • Hierarchical Parsing and Semantic Navigation of Full Body CT Data

    Sascha Seifert;Adrian Barbu;S. Kevin Zhou;David Liu

  • DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction With Deep T1 Prior

    Bo Zhou;S. Kevin Zhou

  • Image based regression using boosting method

    Shaohua Kevin Zhou;B. Georgescu;Xiang Sean Zhou;D. Comaniciu

  • Dual-GAN: Joint BVP and Noise Modeling for Remote Physiological Measurement

    Hao Lu;Hu Han;S. Kevin Zhou

  • Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

    Haofu Liao;Wei-An Lin;Jianbo Yuan;S. Kevin Zhou

  • Rubik's Cube+: A self-supervised feature learning framework for 3D medical image analysis.

    Jiuwen Zhu;Yuexiang Li;Yifan Hu;Kai Ma

  • Appearance Characterization of Linear Lambertian Objects, Generalized Photometric Stereo, and Illumination-Invariant Face Recognition

    S.K. Zhou;G. Aggarwal;R. Chellappa;D.W. Jacobs

  • Spine detection in CT and MR using iterated marginal space learning

    B. Michael Kelm;Michael Wels;S. Kevin Zhou;Sascha Seifert

  • 3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

    Siqi Liu;Daguang Xu;S. Kevin Zhou;Thomas Mertelmeier

Frequent Co-Authors

Dorin Comaniciu
Dorin Comaniciu Siemens (United States)
Yefeng Zheng
Yefeng Zheng Tencent (China)
Hu Han
Hu Han Chinese Academy of Sciences
Daguang Xu
Daguang Xu Nvidia (United Kingdom)
Jiebo Luo
Jiebo Luo University of Rochester
Bogdan Georgescu
Bogdan Georgescu Princeton University
James S. Duncan
James S. Duncan Yale University
Joachim Hornegger
Joachim Hornegger University of Erlangen-Nuremberg
Rama Chellappa
Rama Chellappa Johns Hopkins University
Ghassan Hamarneh
Ghassan Hamarneh Simon Fraser University

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