World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
7185
World Ranking
8026
National Ranking
251

Yan 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 Yan 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: 274 publications — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Yan 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 Yan 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Yan Wang is affiliated with Macquarie University in Australia. Their research spans multiple areas within computer science, with a considerable focus on artificial intelligence, computer vision and pattern recognition, and information systems.

The scientist's work explores various subfields, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Yan Wang's main fields of study reflect extensive engagement with computer science topics. Their research interests cover:

  • Topic Modeling
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Graph Neural Networks
  • Recommender Systems and Techniques
  • Complex Network Analysis Techniques
  • Natural Language Processing Techniques

They have contributed frequently to well-known scholarly outlets. The venues with the highest number of their publications include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • Information Sciences

Yan Wang has coauthored multiple research papers with various collaborators. Notable frequent coauthors include:

  • Shoujin Wang
  • Guanfeng Liu
  • Mehmet A. Orgun
  • Quan Z. Sheng
  • Chaochao Chen

Selected recent papers by Yan Wang feature a range of topics and publication venues:

  • The Medical Segmentation Decathlon, 2022, Nature Communications
  • A Survey on Session-based Recommender Systems, 2021, ACM Computing Surveys
  • HiFuse: Hierarchical multi-scale feature fusion network for medical image classification, 2023, Biomedical Signal Processing and Control
  • MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • When AWGN-Based Denoiser Meets Real Noises, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

In addition to journal and conference papers, Yan Wang has contributed to book publications. One such title is "Veri Yönetiminde Araştırmacılarla Etkileşim: Örnek Çalışmalar Kitabı," published by Hacettepe University in 2020.

Best Publications

  • Sequential Recommender Systems: Challenges, Progress and Prospects

    Shoujin Wang;Liang Hu;Liang Hu;Yan Wang;Longbing Cao

  • A Survey on Session-based Recommender Systems

    Shoujin Wang;Longbing Cao;Yan Wang;Quan Z. Sheng

  • A service computing manifesto: the next 10 years

    Athman Bouguettaya;Munindar Singh;Michael Huhns;Quan Z. Sheng

  • A Proof-of-Trust Consensus Protocol for Enhancing Accountability in Crowdsourcing Services

    Jun Zou;Bin Ye;Lie Qu;Yan Wang

  • Cross-Domain Recommendation: Challenges, Progress, and Prospects

    Feng Zhu;Yan Wang;Chaochao Chen;Jun Zhou

  • DTCDR: A Framework for Dual-Target Cross-Domain Recommendation

    Feng Zhu;Chaochao Chen;Yan Wang;Guanfeng Liu

  • Finding the Optimal Social Trust Path for the Selection of Trustworthy Service Providers in Complex Social Networks

    Guanfeng Liu;Yan Wang;Mehmet A. Orgun;Ee-Peng Lim

  • Graph learning based recommender systems: a review

    Shoujin Wang;Liang Hu;Yan Wang;Xiangnan He

  • Cloud Service Selection Based on the Aggregation of User Feedback and Quantitative Performance Assessment

    Lie Qu;Yan Wang;Mehmet A. Orgun

  • Reputation-Oriented Trustworthy Computing in E-Commerce Environments

    Yan Wang;Kwei-Jay Lin

  • A graphical and attentional framework for dual-target cross-domain recommendation

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • Enhancing grid security with trust management

    C. Lin;V. Varadharajan;Y. Wang;V. Pruthi

  • Optimal social trust path selection in complex social networks

    Guanfeng Liu;Yan Wang;Mehmet A. Orgun

  • Modeling multi-purpose sessions for next-item recommendations via mixture-channel purpose routing networks

    Shoujin Wang;Liang Hu;Liang Hu;Yan Wang;Quan Z. Sheng

  • A Deep Framework for Cross-Domain and Cross-System Recommendations.

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • Context- ware collaborative topic regression with social matrix factorization for recommender systems

    Chaochao Chen;Xiaolin Zheng;Yan Wang;Fuxing Hong

  • Trust transitivity in complex social networks

    Guanfeng Liu;Yan Wang;Mehmet A. Orgun

  • Efficient Query of Quality Correlation for Service Composition

    Yiwen Zhang;Guangming Cui;Shuiguang Deng;Feifei Chen

  • CommTrust: Computing Multi-Dimensional Trust by Mining E-Commerce Feedback Comments

    Xiuzhen Zhang;Lishan Cui;Yan Wang

  • A graph-based comprehensive reputation model

    Su-Rong Yan;Xiao-Lin Zheng;Yan Wang;William Wei Song

  • Social context-aware trust inference for trust enhancement in social network based recommendations on service providers

    Yan Wang;Lei Li;Guanfeng Liu

Frequent Co-Authors

Mehmet A. Orgun
Mehmet A. Orgun Macquarie University
Guanfeng Liu
Guanfeng Liu Macquarie University
Vijay Varadharajan
Vijay Varadharajan University of Newcastle Australia
Quan Z. Sheng
Quan Z. Sheng Macquarie University
Kian-Lee Tan
Kian-Lee Tan National University of Singapore
Yi Shen
Yi Shen Harbin Institute of Technology
Longbing Cao
Longbing Cao University of Technology Sydney
Duncan S. Wong
Duncan S. Wong City University of Hong Kong
Chaochao Chen
Chaochao Chen Zhejiang University
Ee-Peng Lim
Ee-Peng Lim Singapore Management University

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