World's Best Scientists 2026 revealed!
Xiao-Yuan Jing

Xiao-Yuan Jing

D-Index & Metrics

Computer Science

D-Index
46
Citations
7952
World Ranking
6884
National Ranking
920

Xiao-Yuan Jing 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 Xiao-Yuan Jing 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: 286 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Xiao-Yuan Jing 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 Xiao-Yuan Jing 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

Xiao-Yuan Jing is affiliated with Wuhan University in China and has contributed extensively to research in the field of computer science, with a focus on areas such as computer vision and pattern recognition, artificial intelligence, and information systems. Their work spans multiple subfields including software and biomedical engineering.

The scientist has published prominently in venues that include:

  • Pattern Recognition
  • Neurocomputing
  • IEEE Access
  • Knowledge-Based Systems
  • arXiv (Cornell University)

Frequent collaborators include Fei Wu, Yimu Ji, Changhui Hu, Ziyun Cai, and Xiaoke Zhu, reflecting a pattern of sustained joint research efforts.

Some of the main topics addressed in their research are:

  • Software Engineering Research
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications
  • Software Reliability and Analysis Research
  • Human Pose and Action Recognition
  • Face and Expression Recognition

Selected recent papers include:

  • DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Semi-Supervised Multi-View Deep Discriminant Representation Learning (2020), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Modality-specific and shared generative adversarial network for cross-modal retrieval (2020), featured in Pattern Recognition
  • Adaptive deformable convolutional network (2020), published in Neurocomputing
  • Semi-supervised multi-view graph convolutional networks with application to webpage classification (2022), appearing in Information Sciences

The work of Xiao-Yuan Jing reflects a broad engagement with technological and methodological challenges in computer science, particularly in leveraging machine learning techniques across multiple modalities and applications. Their research output contributes to foundational and applied studies within software engineering, artificial intelligence, and computer vision domains.

Best Publications

  • DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis

    Unknown

  • A face and palmprint recognition approach based on discriminant DCT feature extraction

    Xiao-Yuan Jing;D. Zhang

  • Super-resolution Person re-identification with semi-coupled low-rank discriminant dictionary learning

    Xiao-Yuan Jing;Xiaoke Zhu;Fei Wu;Xinge You

  • Progress on approaches to software defect prediction

    Zhiqiang Li;Xiao-Yuan Jing;Xiao-Yuan Jing;Xiaoke Zhu;Xiaoke Zhu

  • Dictionary learning based software defect prediction

    Xiao-Yuan Jing;Shi Ying;Zhi-Wu Zhang;Shan-Shan Wu

  • Heterogeneous cross-company defect prediction by unified metric representation and CCA-based transfer learning

    Xiaoyuan Jing;Fei Wu;Xiwei Dong;Fumin Qi

  • Face and palmprint pixel level fusion and Kernel DCV-RBF classifier for small sample biometric recognition

    Xiao-Yuan Jing;Yong-Fang Yao;David Zhang;Jing-Yu Yang

  • An Improved SDA Based Defect Prediction Framework for Both Within-Project and Cross-Project Class-Imbalance Problems

    Xiao-Yuan Jing;Fei Wu;Xiwei Dong;Baowen Xu

  • Letters: Face and palmprint feature level fusion for single sample biometrics recognition

    Yong-Fang Yao;Xiao-Yuan Jing;Hau-San Wong

  • Semi-Supervised Multi-View Deep Discriminant Representation Learning

    Xiaodong Jia;Xiao-Yuan Jing;Xiaoke Zhu;Songcan Chen

  • Video-Based Person Re-Identification by Simultaneously Learning Intra-Video and Inter-Video Distance Metrics

    Xiaoke Zhu;Xiao-Yuan Jing;Xinge You;Xinyu Zhang

  • Multi-view low-rank dictionary learning for image classification

    Fei Wu;Xiao-Yuan Jing;Xinge You;Dong Yue

  • Multiple kernel ensemble learning for software defect prediction

    Tiejian Wang;Zhiwu Zhang;Xiaoyuan Jing;Liqiang Zhang

  • Cross-Project and Within-Project Semisupervised Software Defect Prediction: A Unified Approach

    Fei Wu;Xiao-Yuan Jing;Ying Sun;Jing Sun

  • Rapid and brief communication: Face recognition based on 2D Fisherface approach

    Xiao-Yuan Jing;Hau-San Wong;David Zhang

  • Label propagation based semi-supervised learning for software defect prediction

    Zhi-Wu Zhang;Xiao-Yuan Jing;Tie-Jian Wang

  • Multiset Feature Learning for Highly Imbalanced Data Classification

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

  • Cost-sensitive transfer kernel canonical correlation analysis for heterogeneous defect prediction

    Zhiqiang Li;Xiao-Yuan Jing;Xiao-Yuan Jing;Fei Wu;Xiaoke Zhu;Xiaoke Zhu

  • Learning robust and discriminative low-rank representations for face recognition with occlusion

    Guangwei Gao;Jian Yang;Xiao-Yuan Jing;Fumin Shen

  • DF-GAN: Deep Fusion Generative Adversarial Networks for Text-to-Image Synthesis

    Ming Tao;Hao Tang;Songsong Wu;Nicu Sebe

  • Video-based person re-identification by simultaneously learning intra-video and inter-video distance metrics

    Xiaoke Zhu;Xiao-Yuan Jing;Fei Wu;Hui Feng

  • Principle Component Analysis

    David Zhang;Xiao-Yuan Jing;Jian Yang

Frequent Co-Authors

Fei Wu
Fei Wu Zhejiang University
David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen
Jingyu Yang
Jingyu Yang Nanjing University of Science and Technology
Sheng Li
Sheng Li University of Virginia
Jian Yang
Jian Yang University of Birmingham
Xinge You
Xinge You Huazhong University of Science and Technology
Dong Yue
Dong Yue Nanjing University of Posts and Telecommunications
Baowen Xu
Baowen Xu Nanjing University
Hongyu Zhang
Hongyu Zhang Chongqing University
C. L. Philip Chen
C. L. Philip Chen South China University of Technology

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