World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
8478
World Ranking
10528
National Ranking
4412

Jun Xiao 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 Jun Xiao 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: 137 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Jun Xiao 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 Jun Xiao 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Jun Xiao is affiliated with the University of Wisconsin-Madison in the United States. Their research primarily focuses on computer science, with a significant emphasis on the subfields of computer vision and pattern recognition, artificial intelligence, surgery, molecular biology, and radiology, nuclear medicine, and imaging.

The scientist's work encompasses several main topics, including multimodal machine learning applications, domain adaptation and few-shot learning, human pose and action recognition, advanced image and video retrieval techniques, topic modeling, video analysis and summarization, and advanced neural network applications.

Frequent coauthors collaborating with Jun Xiao include Long Chen, Yi Yang, Yueting Zhuang, Jian Shao, and Siliang Tang. The collaborations indicate ongoing research partnerships across multiple projects and publications.

Jun Xiao has published extensively in venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Proceedings of the 30th ACM International Conference on Multimedia, SSRN Electronic Journal, and IEEE Transactions on Circuits and Systems for Video Technology. These venues reflect a strong presence in artificial intelligence and multimedia-focused conferences and journals.

Among the recent papers authored by Jun Xiao are:

  • Rethinking the Bottom-Up Framework for Query-Based Video Localization, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Boundary Proposal Network for Two-stage Natural Language Video Localization, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • The Devil is in the Labels: Noisy Label Correction for Robust Scene Graph Generation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Darolutamide in Combination With Androgen-Deprivation Therapy in Patients With Metastatic Hormone-Sensitive Prostate Cancer From the Phase III ARANOTE Trial, 2024, Journal of Clinical Oncology

Best Publications

  • SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning

    Long Chen;Hanwang Zhang;Jun Xiao;Liqiang Nie

  • Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks

    Jun Xiao;Hao Ye;Xiangnan He;Hanwang Zhang

  • Self-Supervised Spatiotemporal Learning via Video Clip Order Prediction

    Dejing Xu;Jun Xiao;Zhou Zhao;Jian Shao

  • Video Question Answering via Gradually Refined Attention over Appearance and Motion

    Dejing Xu;Zhou Zhao;Jun Xiao;Fei Wu

  • Counterfactual Samples Synthesizing for Robust Visual Question Answering

    Long Chen;Xin Yan;Jun Xiao;Hanwang Zhang

  • Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks

    Long Chen;Hanwang Zhang;Jun Xiao;Wei Liu

  • On Geometric Features for Skeleton-Based Action Recognition Using Multilayer LSTM Networks

    Songyang Zhang;Xiaoming Liu;Jun Xiao

  • Fusing Geometric Features for Skeleton-Based Action Recognition Using Multilayer LSTM Networks

    Songyang Zhang;Yang Yang;Jun Xiao;Xiaoming Liu

  • Counterfactual Critic Multi-Agent Training for Scene Graph Generation

    Long Chen;Hanwang Zhang;Jun Xiao;Xiangnan He

  • Boundary Proposal Network for Two-stage Natural Language Video Localization.

    Shaoning Xiao;Long Chen;Songyang Zhang;Wei Ji

  • Rethinking the Bottom-Up Framework for Query-Based Video Localization

    Long Chen;Chujie Lu;Siliang Tang;Jun Xiao

  • Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States

    Yunan Ye;Hengzhi Pei;Boxin Wang;Pin-Yu Chen

  • An artificial intelligence based data-driven approach for design ideation

    Liuqing Chen;Pan Wang;Hao Dong;Feng Shi

  • DEBUG: A Dense Bottom-Up Grounding Approach for Natural Language Video Localization.

    Chujie Lu;Long Chen;Chilie Tan;Xiaolin Li

  • Adaptive unsupervised multi-view feature selection for visual concept recognition

    Yinfu Feng;Jun Xiao;Yueting Zhuang;Xiaoming Liu

  • Hierarchical Fashion Graph Network for Personalized Outfit Recommendation

    Xingchen Li;Xiang Wang;Xiangnan He;Long Chen

  • Learning a 3D Human Pose Distance Metric from Geometric Pose Descriptor

    Cheng Chen;Yueting Zhuang;Feiping Nie;Yi Yang

  • Video Question Answering via Attribute-Augmented Attention Network Learning

    Yunan Ye;Zhou Zhao;Yimeng Li;Long Chen

  • Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding

    Long Chen;Wenbo Ma;Jun Xiao;Hanwang Zhang

  • Exploiting temporal stability and low-rank structure for motion capture data refinement

    Yinfu Feng;Jun Xiao;Yueting Zhuang;Xiaosong Yang

  • Federated Unsupervised Representation Learning.

    Fengda Zhang;Kun Kuang;Zhaoyang You;Tao Shen

  • Scene Dynamics: Counterfactual Critic Multi-Agent Training for Scene Graph Generation.

    Long Chen;Hanwang Zhang;Jun Xiao;Xiangnan He

Frequent Co-Authors

Yueting Zhuang
Yueting Zhuang Zhejiang University
Fei Wu
Fei Wu Zhejiang University
Zhou Zhao
Zhou Zhao Zhejiang University
Hanwang Zhang
Hanwang Zhang Nanyang Technological University
Xiangnan He
Xiangnan He University of Science and Technology of China
Wei Liu
Wei Liu Tencent (China)
Tat-Seng Chua
Tat-Seng Chua National University of Singapore
Xi Li
Xi Li Zhejiang University
Shih-Fu Chang
Shih-Fu Chang Columbia University
Xiaolin Li
Xiaolin Li Pacific Northwest National Laboratory

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