World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
12249
World Ranking
5546
National Ranking
168

Jun Zhou 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 Zhou 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: 249 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Jun Zhou 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 Zhou 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Jun Zhou is affiliated with Griffith University in Australia and has contributed extensively to the field of computer science, with a primary focus on artificial intelligence and related subfields. Their research portfolio includes work in areas such as advanced graph neural networks, topic modeling, recommender systems, privacy-preserving technologies in data, domain adaptation and few-shot learning, graph theory and algorithms, and adversarial robustness in machine learning.

Their main fields of study document 317 publications in computer science, with 198 specifically in artificial intelligence. Other significant subfields include computer vision and pattern recognition (51 publications), information systems (43 publications), management science and operations research (12 publications), and molecular biology (11 publications).

Jun Zhou has been frequently published in several academic venues. Their most prominent publication outlets are:

  • arXiv (Cornell University) with 72 publications
  • Proceedings of the AAAI Conference on Artificial Intelligence with 6 publications
  • IEEE Transactions on Knowledge and Data Engineering with 5 publications
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management with 4 publications
  • Proceedings of the VLDB Endowment with 3 publications

Some of their recent papers include:

  • "EATN: An Efficient Adaptive Transfer Network for Aspect-level Sentiment Analysis" (2021), published in IEEE Transactions on Knowledge and Data Engineering
  • "AGL" (2020), published in Proceedings of the VLDB Endowment
  • "ASFGNN: Automated separated-federated graph neural network" (2021), published in Peer-to-Peer Networking and Applications
  • "Rapid Target Detection of Fruit Trees Using UAV Imaging and Improved Light YOLOv4 Algorithm" (2022), published in Remote Sensing
  • "AGL: a Scalable System for Industrial-purpose Graph Machine Learning" (2020), published in arXiv (Cornell University)

Frequent collaborators of Jun Zhou include Zhiqiang Zhang, Chaochao Chen, Longfei Li, and Xiaolu Zhang. These co-authors have worked with Zhou on multiple projects and publications, indicating ongoing research partnerships.

Best Publications

  • A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects.

    Zewen Li;Fan Liu;Wenjie Yang;Shouheng Peng

  • Hyperspectral Unmixing via $L_{1/2}$ Sparsity-Constrained Nonnegative Matrix Factorization

    Yuntao Qian;Sen Jia;Jun Zhou;A. Robles-Kelly

  • Hyperspectral Image Classification Based on Structured Sparse Logistic Regression and Three-Dimensional Wavelet Texture Features

    Yuntao Qian;Minchao Ye;Jun Zhou

  • MILIS: Multiple Instance Learning with Instance Selection

    Zhouyu Fu;A Robles-Kelly;Jun Zhou

  • Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss

    Cheng Yan;Guansong Pang;Xiao Bai;Changhong Liu

  • Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery

    Yuntao Qian;Fengchao Xiong;Shan Zeng;Jun Zhou

  • Multiscale Visual Attention Networks for Object Detection in VHR Remote Sensing Images

    Chen Wang;Xiao Bai;Shuai Wang;Jun Zhou

  • Material Based Object Tracking in Hyperspectral Videos

    Fengchao Xiong;Jun Zhou;Yuntao Qian

  • On the Sampling Strategy for Evaluation of Spectral-Spatial Methods in Hyperspectral Image Classification

    Jie Liang;Jun Zhou;Yuntao Qian;Lian Wen

  • Multitask Sparse Nonnegative Matrix Factorization for Joint Spectral–Spatial Hyperspectral Imagery Denoising

    Minchao Ye;Yuntao Qian;Jun Zhou

  • Goal-Oriented Gaze Estimation for Zero-Shot Learning

    Yang Liu;Lei Zhou;Xiao Bai;Yifei Huang

  • Progressive Transfer Learning and Adversarial Domain Adaptation for Cross-Domain Skin Disease Classification

    Yanyang Gu;Zongyuan Ge;C. Paul Bonnington;Jun Zhou

  • VHR Object Detection Based on Structural Feature Extraction and Query Expansion

    Xiao Bai;Huigang Zhang;Jun Zhou

  • Dictionary Learning-Based Feature-Level Domain Adaptation for Cross-Scene Hyperspectral Image Classification

    Minchao Ye;Yuntao Qian;Jun Zhou;Yuan Yan Tang

  • Road tracking in aerial images based on human–computer interaction and Bayesian filtering

    Jun Zhou;Walter F. Bischof;Terry Caelli

  • Use of SIMD Vector Operations to Accelerate Application Code Performance on Low-Powered ARM and Intel Platforms

    Gaurav Mitra;Beau Johnston;Alistair P. Rendell;Eric McCreath

  • Hyperspectral Anomaly Detection via Deep Plug-and-Play Denoising CNN Regularization

    Xiyou Fu;Sen Jia;Lina Zhuang;Meng Xu

  • Mixing Linear SVMs for Nonlinear Classification

    Zhouyu Fu;A Robles-Kelly;Jun Zhou

  • Hyperspectral Unmixing via Total Variation Regularized Nonnegative Tensor Factorization

    Fengchao Xiong;Yuntao Qian;Jun Zhou;Yuan Yan Tang

  • Monitoring agricultural drought in Australia using MTSAT-2 land surface temperature retrievals

    Tian Hu;Tian Hu;Tian Hu;Luigi J. Renzullo;Albert I.J.M. van Dijk;Jie He

  • Adaptive hash retrieval with kernel based similarity

    Xiao Bai;Cheng Yan;Haichuan Yang;Lu Bai

  • Hyperspectral Unmixing via L 1/2 Sparsity-Constrained Nonnegative

    Yuntao Qian;Sen Jia;Jun Zhou;Antonio Robles-Kelly

Frequent Co-Authors

Yuntao Qian
Yuntao Qian Zhejiang University
Xiuping Jia
Xiuping Jia University of New South Wales
Edwin R. Hancock
Edwin R. Hancock University of York
Sen Jia
Sen Jia Shenzhen University
Zhihong Xu
Zhihong Xu Griffith University
Alan Wee-Chung Liew
Alan Wee-Chung Liew Griffith University
Walter F. Bischof
Walter F. Bischof University of British Columbia
Luigi Renzullo
Luigi Renzullo Commonwealth Scientific and Industrial Research Organisation
Terry Caelli
Terry Caelli Deakin University
Albert van Dijk
Albert van Dijk Australian National University

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