World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5704
World Ranking
10289
National Ranking
4317

Yang Song 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 Yang Song 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: 165 publications — 33rd percentile

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

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

Yang Song 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 Yang Song 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

Yang Song is affiliated with the California Institute of Technology in the United States. Their research spans the fields of Computer Science and Medicine, with a particular focus on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biophysics, and Electrical and Electronic Engineering.

Their work covers multiple topics including:

  • AI in cancer detection
  • Advanced Neural Network Applications
  • Cell Image Analysis Techniques
  • Digital Imaging for Blood Diseases
  • Domain Adaptation and Few-Shot Learning
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Neuroimaging Techniques and Applications

Yang Song has contributed extensively to academic publications with a particular focus on venues such as:

  • arXiv (Cornell University)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Medical Image Analysis
  • SSRN Electronic Journal
  • bioRxiv (Cold Spring Harbor Laboratory)

They have collaborated frequently with a number of researchers, including:

  • Maurice Pagnucco (37 coauthored papers)
  • Weidong Cai (36 coauthored papers)
  • Chaoyi Zhang (31 coauthored papers)
  • Erik Meijering (25 coauthored papers)
  • Lauren J. O'Donnell (16 coauthored papers)

Notable recent papers by Yang Song include:

  • "SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations", published in 2021 in arXiv (Cornell University)
  • "Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis", published in 2021 at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "NFN: A novel network followed network for retinal vessel segmentation", published in 2020 in Neural Networks
  • "Network Localization of State and Trait of Auditory Verbal Hallucinations in Schizophrenia", published in 2024 in Schizophrenia Bulletin
  • "PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images", published in 2020 in IEEE Transactions on Medical Imaging

Best Publications

  • Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT

    Yutong Xie;Yong Xia;Jianpeng Zhang;Yang Song

  • Sequential Recommendation with Graph Neural Networks

    Jianxin Chang;Chen Gao;Yu Zheng;Yiqun Hui

  • Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis

    Tiange Xiang;Chaoyi Zhang;Yang Song;Jianhui Yu

  • Feature-Based Image Patch Approximation for Lung Tissue Classification

    Yang Song;Weidong Cai;Yun Zhou;D. D. Feng

  • Learning to Recommend With Multiple Cascading Behaviors

    Chen Gao;Xiangnan He;Dahua Gan;Xiangning Chen

  • NFN+: A novel network followed network for retinal vessel segmentation.

    Yicheng Wu;Yong Xia;Yang Song;Yanning Zhang

  • Multiscale Network Followed Network Model for Retinal Vessel Segmentation

    Yicheng Wu;Yong Xia;Yang Song;Yanning Zhang

  • Vessel-Net: Retinal Vessel Segmentation Under Multi-path Supervision

    Yicheng Wu;Yong Xia;Yang Song;Donghao Zhang

  • Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images

    Dongnan Liu;Donghao Zhang;Yang Song;Heng Huang

  • 3D APA-Net: 3D Adversarial Pyramid Anisotropic Convolutional Network for Prostate Segmentation in MR Images

    Haozhe Jia;Yong Xia;Yang Song;Donghao Zhang

  • Lung Nodule Classification With Multilevel Patch-Based Context Analysis

    Fan Zhang;Yang Song;Weidong Cai;Min-Zhao Lee

  • Multi-Pass Fast Watershed for Accurate Segmentation of Overlapping Cervical Cells

    Afaf Tareef;Yang Song;Heng Huang;Dagan Feng

  • Large Margin Local Estimate With Applications to Medical Image Classification

    Yang Song;Weidong Cai;Heng Huang;Yun Zhou

  • Whole brain white matter connectivity analysis using machine learning: An application to autism.

    Fan Zhang;Peter Savadjiev;Weidong Cai;Yang Song

  • Atlas registration and ensemble deep convolutional neural network-based prostate segmentation using magnetic resonance imaging

    Haozhe Jia;Yong Xia;Yang Song;Weidong Cai

  • Adapting fisher vectors for histopathology image classification

    Yang Song;Ju Jia Zou;Hang Chang;Weidong Cai

  • BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture

    Tiange Xiang;Chaoyi Zhang;Dongnan Liu;Yang Song

  • Decompose to Adapt: Cross-Domain Object Detection Via Feature Disentanglement

    Unknown

  • Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting

    Dongnan Liu;Donghao Zhang;Yang Song;Fan Zhang

  • PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images

    Dongnan Liu;Donghao Zhang;Yang Song;Fan Zhang

  • A Multistage Discriminative Model for Tumor and Lymph Node Detection in Thoracic Images

    Yang Song;Weidong Cai;Jinman Kim;D. D. Feng

  • Optimizing the cervix cytological examination based on deep learning and dynamic shape modeling

    Afaf Tareef;Yang Song;Heng Huang;Yue Wang

  • Automatic segmentation of overlapping cervical smear cells based on local distinctive features and guided shape deformation

    Afaf Tareef;Yang Song;Weidong Cai;Heng Huang

Frequent Co-Authors

Weidong Cai
Weidong Cai University of Sydney
Dagan Feng
Dagan Feng University of Sydney
Heng Huang
Heng Huang University of Pittsburgh
Yue Wang
Yue Wang Zhejiang University
Yong Xia
Yong Xia Northwestern Polytechnical University
Ron Kikinis
Ron Kikinis Brigham and Women's Hospital
Hanchuan Peng
Hanchuan Peng Southeast University
Wojciech Chrzanowski
Wojciech Chrzanowski University of Sydney
Yogesh Rathi
Yogesh Rathi Brigham and Women's Hospital
Qing Li
Qing Li University of Sydney

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