World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
8870
World Ranking
9591
National Ranking
4064

Wei Shen 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 Wei Shen 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: 100 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.

Wei Shen 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 Wei Shen 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Wei Shen is affiliated with Johns Hopkins University in the United States and has contributed extensively to research in computer science and medicine. Their work spans over 190 publications, with a significant focus on computer vision, artificial intelligence, and medical imaging.

Their primary fields of study include:

  • Computer Science
  • Medicine

Within these broader disciplines, Wei Shen specializes in several subfields, notably:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Human-Computer Interaction
  • Oncology

The main topics covered in their research work are:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Visual Attention and Saliency Detection
  • Advanced Vision and Imaging
  • Anomaly Detection Techniques and Applications
  • 3D Shape Modeling and Analysis
  • AI in Cancer Detection

Wei Shen's recent publications demonstrate contributions to both foundational and applied aspects of these areas. Notable papers include:

  • "The Medical Segmentation Decathlon," 2022, Nature Communications
  • "iBOT: Image BERT Pre-Training with Online Tokenizer," 2021, arXiv (Cornell University)
  • "Intriguing Findings of Frequency Selection for Image Deblurring," 2023, Proceedings of the AAAI Conference on Artificial Intelligence
  • "A Survey on Label-Efficient Deep Image Segmentation: Bridging the Gap Between Weak Supervision and Dense Prediction," 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "End-to-End Human-Gaze-Target Detection with Transformers," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Wei Shen frequently publishes in several prominent venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Applied Sciences
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

The researcher has collaborated extensively with other scientists. Among the frequent co-authors are:

  • Alan Yuille
  • Xiaokang Yang
  • Guangtao Zhai
  • Yingda Xia
  • Lingxi Xie

Wei Shen's body of work encompasses both theoretical and practical advancements in neural networks, image segmentation, and cancer detection technologies, reflecting an interdisciplinary approach that integrates computer science methodologies with medical applications.

Best Publications

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Multi-oriented Text Detection with Fully Convolutional Networks

    Zheng Zhang;Chengquan Zhang;Wei Shen;Cong Yao

  • DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection

    Wei Shen;Xinggang Wang;Yan Wang;Xiang Bai

  • Few-Shot Image Recognition by Predicting Parameters from Activations

    Siyuan Qiao;Chenxi Liu;Wei Shen;Alan Yuille

  • Deep Co-Training for Semi-Supervised Image Recognition

    Siyuan Qiao;Wei Shen;Zhishuai Zhang;Bo Wang

  • PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

    Peng Tang;Xinggang Wang;Song Bai;Wei Shen

  • Symmetry-based text line detection in natural scenes

    Zheng Zhang;Wei Shen;Cong Yao;Xiang Bai

  • A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

    Yuyin Zhou;Lingxi Xie;Wei Shen;Wei Shen;Yan Wang

  • Spatial-temporal convolutional neural networks for anomaly detection and localization in crowded scenes

    Shifu Zhou;Wei Shen;Dan Zeng;Mei Fang

  • Abdominal multi-organ segmentation with organ-attention networks and statistical fusion

    Yan Wang;Yuyin Zhou;Wei Shen;Seyoun Park

  • Single-Shot Object Detection with Enriched Semantics

    Zhishuai Zhang;Siyuan Qiao;Cihang Xie;Wei Shen

  • iBOT: Image BERT Pre-Training with Online Tokenizer.

    Jinghao Zhou;Chen Wei;Huiyu Wang;Wei Shen

  • A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

    Zhuotun Zhu;Yingda Xia;Wei Shen;Wei Shen;Elliot Fishman

  • Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

    Siyuan Qiao;Huiyu Wang;Chenxi Liu;Wei Shen

  • Deep Regression Forests for Age Estimation

    Wei Shen;Yilu Guo;Yan Wang;Kai Zhao

  • Domain adaptive relational reasoning for 3D multi-organ segmentation

    Shuhao Fu;Yongyi Lu;Yan Wang;Yuyin Zhou

  • Semi-Supervised 3D Abdominal Multi-Organ Segmentation Via Deep Multi-Planar Co-Training

    Yuyin Zhou;Yan Wang;Peng Tang;Song Bai

  • Skeleton growing and pruning with bending potential ratio

    Wei Shen;Xiang Bai;Rong Hu;Hongyuan Wang

  • Synthesize Then Compare: Detecting Failures and Anomalies for Semantic Segmentation

    Yingda Xia;Yi Zhang;Fengze Liu;Wei Shen

  • Deep Distance Transform for Tubular Structure Segmentation in CT Scans

    Yan Wang;Xu Wei;Fengze Liu;Jieneng Chen

  • Weight Standardization

    Siyuan Qiao;Huiyu Wang;Chenxi Liu;Wei Shen

Frequent Co-Authors

Alan L. Yuille
Alan L. Yuille Johns Hopkins University
Xiang Bai
Xiang Bai Huazhong University of Science and Technology
Yuyin Zhou
Yuyin Zhou University of California, Santa Cruz
Elliot K. Fishman
Elliot K. Fishman Johns Hopkins University
Wenyu Liu
Wenyu Liu Huazhong University of Science and Technology
Lingxi Xie
Lingxi Xie Huawei Technologies (China)
Xinggang Wang
Xinggang Wang Huazhong University of Science and Technology
Cong Yao
Cong Yao Alibaba Group (China)
Longin Jan Latecki
Longin Jan Latecki Temple University
Song Bai
Song Bai ByteDance

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