World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
7871
World Ranking
6892
National Ranking
416

Yang Gao 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 Gao 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: 238 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Yang Gao 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 Gao 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Yang Gao is affiliated with Google in the United Kingdom. Their research primarily focuses on the field of Computer Science, with a significant number of publications spanning various subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, and Control and Systems Engineering.

Their work covers a variety of main topics including Domain Adaptation and Few-Shot Learning, Multimodal Machine Learning Applications, Advanced Neural Network Applications, Reinforcement Learning in Robotics, Topic Modeling, Natural Language Processing Techniques, and Advanced Image and Video Retrieval Techniques.

Yang Gao has published extensively across multiple venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Medical Imaging
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Circuits and Systems for Video Technology

Among Yang Gao's recent papers are:

  • ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation (2022), published in the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Multi-Agent Game Abstraction via Graph Attention Neural Network (2020), in the Proceedings of the AAAI Conference on Artificial Intelligence
  • Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images (2021), published in Pattern Recognition
  • Hop Reachable Domain on Irregularly Shaped Asteroids (2020), published in the Journal of Guidance Control and Dynamics
  • Local descriptor-based multi-prototype network for few-shot learning (2021), also in Pattern Recognition

Yang Gao collaborates frequently with a group of coauthors including Yinghuan Shi, Jing Huo, Lei Qi, Wenbin Li, and Lei Wang, with the number of joint publications ranging from 19 to 54.

The researcher has also contributed to book publications, notably a title on Big Data published by Springer Science+Business Media in 2022.

Best Publications

  • Revisiting Local Descriptor Based Image-To-Class Measure for Few-Shot Learning

    Wenbin Li;Lei Wang;Jinglin Xu;Jing Huo

  • ST++: Make Self-trainingWork Better for Semi-supervised Semantic Segmentation

    Unknown

  • Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

    Yinghuan Shi;Jian Zhang;Tong Ling;Jiwen Lu

  • Adaptive grid job scheduling with genetic algorithms

    Yang Gao;Hongqiang Rong;Joshua Zhexue Huang

  • Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning

    Wenbin Li;Jinglin Xu;Jing Huo;Lei Wang

  • Multi-Agent Game Abstraction via Graph Attention Neural Network

    Yong Liu;Weixun Wang;Yujing Hu;Jianye Hao

  • A Novel Unsupervised Camera-Aware Domain Adaptation Framework for Person Re-Identification

    Lei Qi;Lei Wang;Jing Huo;Luping Zhou

  • Multiset Feature Learning for Highly Imbalanced Data Classification

    Xiao-Yuan Jing;Xinyu Zhang;Xiaoke Zhu;Fei Wu

  • Crossbar-Net: A Novel Convolutional Neural Network for Kidney Tumor Segmentation in CT Images

    Qian Yu;Yinghuan Shi;Jinquan Sun;Yang Gao

  • Pelvic Organ Segmentation Using Distinctive Curve Guided Fully Convolutional Networks

    Kelei He;Xiaohuan Cao;Yinghuan Shi;Dong Nie

  • Differentiable Meta-Learning Model for Few-Shot Semantic Segmentation

    Pinzhuo Tian;Zhangkai Wu;Lei Qi;Lei Wang

  • Local descriptor-based multi-prototype network for few-shot Learning

    Hongwei Huang;Zhangkai Wu;Wenbin Li;Jing Huo

  • From Few to More: Large-Scale Dynamic Multiagent Curriculum Learning

    Weixun Wang;Tianpei Yang;Yong Liu;Jianye Hao

  • Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images.

    Kelei He;Wei Zhao;Xingzhi Xie;Wen Ji

  • Real-Time Abnormal Event Detection in Complicated Scenes

    Yinghuan Shi;Yang Gao;Ruili Wang

  • Asymmetric Distribution Measure for Few-shot Learning

    Wenbin Li;Lei Wang;Jing Huo;Yinghuan Shi

  • Adaptive Label Correlation Based Asymmetric Discrete Hashing for Cross-modal Retrieval

    Huaxiong Li;Chao Zhang;Xiuyi Jia;Yang Gao

  • HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation in CT Images

    Kelei He;Chunfeng Lian;Bing Zhang;Xin Zhang

  • Multiagent Reinforcement Learning With Unshared Value Functions

    Yujing Hu;Yang Gao;Bo An

  • MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification.

    Lei Qi;Jing Huo;Lei Wang;Yinghuan Shi

  • Joint multi-label classification and label correlations with missing labels and feature selection

    Zhi-Fen He;Ming Yang;Yang Gao;Hui-Dong Liu

  • Crossbar-Net: A Novel Convolutional Network for Kidney Tumor Segmentation in CT Images

    Qian Yu;Yinghuan Shi;Jinquan Sun;Yang Gao

  • An efficient adaptive focused crawler based on ontology learning

    Chang Su;Yang Gao;Jianmei Yang;Bin Luo

  • Measuring the Distance Between Finite Markov Decision Processes

    Jinhua Song;Yang Gao;Hao Wang;Bo An

  • WebCaricature: a benchmark for caricature face recognition

    Jing Huo;Wenbin Li;Yinghuan Shi;Yang Gao

  • Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images

    Kelei He;Wei Zhao;Xingzhi Xie;Wen Ji

Frequent Co-Authors

Yinghuan Shi
Yinghuan Shi Nanjing University
Lei Wang
Lei Wang University of Wollongong
Dinggang Shen
Dinggang Shen ShanghaiTech University
Jiebo Luo
Jiebo Luo University of Rochester
Hujun Yin
Hujun Yin University of Manchester
Longbing Cao
Longbing Cao University of Technology Sydney
Bo An
Bo An Nanyang Technological University
Yu-Kun Lai
Yu-Kun Lai Cardiff University
Daoqiang Zhang
Daoqiang Zhang Nanjing University of Aeronautics and Astronautics
Yaozong Gao
Yaozong Gao United Imaging Healthcare (China)

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