World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
8630
World Ranking
4919
National Ranking
662

Xi-Le Zhao 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 Xi-Le Zhao 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: 257 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

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

Xi-Le Zhao 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 Xi-Le Zhao 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

Xi-Le Zhao is affiliated with the University of Electronic Science and Technology of China in China. Their research spans primarily across the fields of Computer Science and Engineering, with significant contributions to subfields such as Computer Vision and Pattern Recognition, Computational Mechanics, Media Technology, Computational Mathematics, and Radiology, Nuclear Medicine and Imaging.

The scientist's work prominently focuses on several specialized topics within these fields, including Image and Signal Denoising Methods, Sparse and Compressive Sensing Techniques, Tensor Decomposition and Applications, Advanced Image Fusion Techniques, Advanced Image Processing Techniques, Remote-Sensing Image Classification, and Advanced Neuroimaging Techniques and Applications.

Their recent notable publications include:

  • Hyperspectral Image Denoising via Tensor Low-Rank Prior and Unsupervised Deep Spatial-Spectral Prior, 2022, IEEE Transactions on Geoscience and Remote Sensing
  • Weighted Low-Rank Tensor Recovery for Hyperspectral Image Restoration, 2020, IEEE Transactions on Cybernetics
  • Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral Image, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Deep plug-and-play prior for low-rank tensor completion, 2020, Neurocomputing

Throughout their career, Xi-Le Zhao has frequently published in venues such as arXiv (Cornell University), IEEE Transactions on Geoscience and Remote Sensing, Journal of Scientific Computing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, and IEEE Transactions on Neural Networks and Learning Systems.

The scientist has collaborated extensively with several frequent coauthors, including Ting-Zhu Huang, Tai-Xiang Jiang, Michael K. Ng, Yu-Bang Zheng, and Yisi Luo.

Best Publications

  • Hyperspectral Image Denoising via Tensor Low-Rank Prior and Unsupervised Deep Spatial–Spectral Prior

    Unknown

  • Hyperspectral Image Restoration Via Total Variation Regularized Low-Rank Tensor Decomposition

    Yao Wang;Jiangjun Peng;Qian Zhao;Yee Leung

  • Framelet Representation of Tensor Nuclear Norm for Third-Order Tensor Completion

    Tai-Xiang Jiang;Michael K. Ng;Xi-Le Zhao;Ting-Zhu Huang

  • Mixed Noise Removal in Hyperspectral Image via Low-Fibered-Rank Regularization

    Yu-Bang Zheng;Ting-Zhu Huang;Xi-Le Zhao;Tai-Xiang Jiang

  • Weighted Low-Rank Tensor Recovery for Hyperspectral Image Restoration

    Yi Chang;Luxin Yan;Xi-Le Zhao;Houzhang Fang

  • FastDeRain: A Novel Video Rain Streak Removal Method Using Directional Gradient Priors

    Tai-Xiang Jiang;Ting-Zhu Huang;Xi-Le Zhao;Liang-Jian Deng

  • Deblurring and Sparse Unmixing for Hyperspectral Images

    Xi-Le Zhao;Fan Wang;Ting-Zhu Huang;M. K. Ng

  • A Novel Tensor-Based Video Rain Streaks Removal Approach via Utilizing Discriminatively Intrinsic Priors

    Tai-Xiang Jiang;Ting-Zhu Huang;Xi-Le Zhao;Liang-Jian Deng

  • Tensor completion using total variation and low-rank matrix factorization

    Teng-Yu Ji;Ting-Zhu Huang;Xi-Le Zhao;Tian-Hui Ma

  • A directional global sparse model for single image rain removal

    Liang-Jian Deng;Ting-Zhu Huang;Xi-Le Zhao;Tai-Xiang Jiang

  • A New Convex Optimization Model for Multiplicative Noise and Blur Removal

    Xi Le Zhao;Xi Le Zhao;Fan Wang;Michael K. Ng

  • Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion

    Yu-Bang Zheng;Ting-Zhu Huang;Xi-Le Zhao;Qibin Zhao

  • Non-Local Robust Quaternion Matrix Completion for Large-Scale Color Image and Video Inpainting

    Unknown

  • GraphGST: Graph Generative Structure-Aware Transformer for Hyperspectral Image Classification

    Unknown

  • Remote sensing images destriping using unidirectional hybrid total variation and nonconvex low-rank regularization

    Jing-Hua Yang;Xi-Le Zhao;Tian-Hui Ma;Yong Chen

  • Multi-dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm

    Tai-Xiang Jiang;Tai-Xiang Jiang;Ting-Zhu Huang;Xi-Le Zhao;Liang-Jian Deng

  • Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral Image

    Yu-Bang Zheng;Ting-Zhu Huang;Xi-Le Zhao;Yong Chen

  • Low-rank tensor train for tensor robust principal component analysis

    Jing-Hua Yang;Xi-Le Zhao;Teng-Yu Ji;Tian-Hui Ma

  • A non-convex tensor rank approximation for tensor completion

    Teng-Yu Ji;Ting-Zhu Huang;Xi-Le Zhao;Tian-Hui Ma

  • Nonlocal Tensor-Ring Decomposition for Hyperspectral Image Denoising

    Yong Chen;Wei He;Naoto Yokoya;Ting-Zhu Huang

  • Tensor N-tubal rank and its convex relaxation for low-rank tensor recovery

    Yu-Bang Zheng;Ting-Zhu Huang;Xi-Le Zhao;Tai-Xiang Jiang

  • Deep plug-and-play prior for low-rank tensor completion

    Xi-Le Zhao;Wen-Hao Xu;Tai-Xiang Jiang;Yao Wang;Yao Wang

  • Speckle noise removal in ultrasound images by first- and second-order total variation

    Si Wang;Ting-Zhu Huang;Xi-Le Zhao;Jin-Jin Mei

  • Low-rank tensor completion via smooth matrix factorization

    Yu-Bang Zheng;Ting-Zhu Huang;Teng-Yu Ji;Xi-Le Zhao

  • Hyperspectral Image Restoration via Total Variation Regularized Low-rank Tensor Decomposition

    Yao Wang;Jiangjun Peng;Qian Zhao;Deyu Meng

Frequent Co-Authors

Ting-Zhu Huang
Ting-Zhu Huang University of Electronic Science and Technology of China
Liang-Jian Deng
Liang-Jian Deng University of Electronic Science and Technology of China
Michael K. Ng
Michael K. Ng Hong Kong Baptist University
Zongben Xu
Zongben Xu Xi'an Jiaotong University
Deyu Meng
Deyu Meng Xi'an Jiaotong University
Luxin Yan
Luxin Yan Huazhong University of Science and Technology
Wei Wang
Wei Wang Harbin Institute of Technology
Naoto Yokoya
Naoto Yokoya University of Tokyo
Hongyan Zhang
Hongyan Zhang China University of Geosciences
Qian Zhao
Qian Zhao Xi'an Jiaotong University

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