World's Best Scientists 2026 revealed!
Yizhou Wang

Yizhou Wang

D-Index & Metrics

Computer Science

D-Index
51
Citations
9061
World Ranking
5399
National Ranking
721

Yizhou Wang 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 Yizhou Wang 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: 205 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Yizhou Wang 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 Yizhou Wang 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

Yizhou Wang is affiliated with Peking University in China and has an extensive publication record primarily in the domains of computer science and engineering. Their research spans a variety of specialized subfields including computer vision and pattern recognition, artificial intelligence, radiology, nuclear medicine and imaging, cognitive neuroscience, and biomedical engineering.

The scientist's work covers diverse topics with a notable focus on human pose and action recognition, video surveillance and tracking methods, advanced neural network applications, domain adaptation and few-shot learning, applications of AI in cancer detection, advanced vision and imaging, and multimodal machine learning applications.

Among recent publications, notable papers include the following:

  • Exploring Task Structure for Brain Tumor Segmentation From Multi-Modality MR Images, 2020, IEEE Transactions on Image Processing
  • Retinal Vessel Segmentation Using Deep Learning: A Review, 2021, IEEE Access
  • Human Motion Generation: A Survey, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • AI Alignment: A Comprehensive Survey, 2023, arXiv (Cornell University)
  • Locally Connected Network for Monocular 3D Human Pose Estimation, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence

Frequent coauthors working alongside Yizhou Wang include Fangwei Zhong, Xinwei Sun, Yizhou Yu, Chunyu Wang, and Wentao Zhu.

Major publication venues where Yizhou Wang's research appears most frequently are:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Image Processing
  • SSRN Electronic Journal

Yizhou Wang's body of work integrates aspects of biomedical imagery with computer vision techniques, addressing problems such as tumor segmentation and retinal vessel analysis, as well as advancing technologies in human motion and pose estimation. The research outputs reflect a multidisciplinary approach combining engineering methods with cognitive neuroscience and biomedical applications.

Best Publications

  • An Approach to Pose-Based Action Recognition

    Chunyu Wang;Yizhou Wang;Alan L. Yuille

  • Multi-Agent Tensor Fusion for Contextual Trajectory Prediction

    Tianyang Zhao;Yifei Xu;Mathew Monfort;Wongun Choi

  • Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction

    Wei Wang;Yan Huang;Yizhou Wang;Liang Wang

  • What are Textons

    Song-Chun Zhu;Cheng-En Guo;Yizhou Wang;Zijian Xu

  • Detect-SLAM: Making Object Detection and SLAM Mutually Beneficial

    Fangwei Zhong;Sheng Wang;Ziqi Zhang;China Chen

  • Jigsaw: indoor floor plan reconstruction via mobile crowdsensing

    Ruipeng Gao;Mingmin Zhao;Tao Ye;Fan Ye

  • Optimizing Network Structure for 3D Human Pose Estimation

    Hai Ci;Chunyu Wang;Xiaoxuan Ma;Yizhou Wang

  • Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization

    Daochang Liu;Tingting Jiang;Yizhou Wang

  • Robust Estimation of 3D Human Poses from a Single Image

    Chunyu Wang;Yizhou Wang;Zhouchen Lin;Alan L. Yuille

  • Measuring visual saliency by Site Entropy Rate

    Wei Wang;Yizhou Wang;Qingming Huang;Wen Gao

  • UnrealCV: Virtual Worlds for Computer Vision

    Weichao Qiu;Fangwei Zhong;Yi Zhang;Siyuan Qiao

  • Exploring Task Structure for Brain Tumor Segmentation From Multi-Modality MR Images

    Dingwen Zhang;Guohai Huang;Qiang Zhang;Jungong Han

  • Quantized correlation hashing for fast cross-modal search

    Botong Wu;Qiang Yang;Wei-Shi Zheng;Yizhou Wang

  • Face Detection with End-to-End Integration of a ConvNet and a 3D Model

    Yunzhu Li;Benyuan Sun;Tianfu Wu;Yizhou Wang

  • AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding

    Jiahong Wu;He Zheng;Bo Zhao;Yixin Li

  • Joint learning for pulmonary nodule segmentation, attributes and malignancy prediction

    Botong Wu;Zhen Zhou;Jianwei Wang;Yizhou Wang

  • Simulating human saccadic scanpaths on natural images

    Wei Wang;Cheng Chen;Yizhou Wang;Tingting Jiang

  • End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning

    Wenhan Luo;Peng Sun;Fangwei Zhong;Wei Liu

  • L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise

    Yilun Xu;Peng Cao;Yuqing Kong;Yizhou Wang

  • Maximal Sparsity with Deep Networks

    Bo Xin;Yizhou Wang;Wen Gao;David P. Wipf

  • What Are Textons

    Song Chun Zhu;Cheng-en Guo;Ying Nian Wu;Yizhou Wang

Frequent Co-Authors

Wen Gao
Wen Gao Peking University
Yizhou Yu
Yizhou Yu University of Hong Kong
Song-Chun Zhu
Song-Chun Zhu Peking University
Fan Ye
Fan Ye Stony Brook University
Alan L. Yuille
Alan L. Yuille Johns Hopkins University
Yanwei Fu
Yanwei Fu Fudan University
Wenhan Luo
Wenhan Luo Hong Kong University of Science and Technology
Tianfu Wu
Tianfu Wu North Carolina State University
Kaigui Bian
Kaigui Bian Peking University
David Wipf
David Wipf Amazon (United States)

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