World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
70
Citations
18142
World Ranking
1887
National Ranking
261

Guoyin 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 Guoyin 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: 809 publications — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Guoyin 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 Guoyin 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: 70 D-Index — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Overview

Guoyin Wang is affiliated with Chongqing University of Posts and Telecommunications in China. Their research primarily focuses on the field of Computer Science, with a significant emphasis on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Information Systems, and Signal Processing.

The scientist has contributed extensively to topics including Rough Sets and Fuzzy Logic, Advanced Graph Neural Networks, Topic Modeling, Natural Language Processing Techniques, Data Mining Algorithms and Applications, Text and Document Classification Technologies, and Anomaly Detection Techniques and Applications.

Guoyin Wang's recent scholarly papers include the following:

  • GBNRS: A Novel Rough Set Algorithm for Fast Adaptive Attribute Reduction in Classification, 2020, published in IEEE Transactions on Knowledge and Data Engineering
  • Optimized Content Caching and User Association for Edge Computing in Densely Deployed Heterogeneous Networks, 2020, published in IEEE Transactions on Mobile Computing
  • A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction, 2020, published in IEEE Transactions on Knowledge and Data Engineering
  • Dynamic Computation Offloading and Server Deployment for UAV-Enabled Multi-Access Edge Computing, 2021, published in IEEE Transactions on Mobile Computing
  • RSMOTE: A self-adaptive robust SMOTE for imbalanced problems with label noise, 2020, published in Information Sciences

The frequent co-authors collaborating with Guoyin Wang include:

  • Shuyin Xia
  • Qinghua Zhang
  • Qun Liu
  • Xinbo Gao
  • Hong Yu

Guoyin Wang has published frequently in several venues, among the most common are:

  • arXiv (Cornell University)
  • Information Sciences
  • Knowledge-Based Systems
  • SSRN Electronic Journal
  • IEEE Transactions on Neural Networks and Learning Systems

The scientist has contributed to scholarly literature beyond journal articles by authoring a book titled Big Data, published in 2022 by Springer Science+Business Media.

Best Publications

  • Rough sets, fuzzy sets, data mining and granular computing

    Sergei O. Kuznetsov;Dominik Ślęzak;Daryl H. Hepting;Boris G. Mirkin

  • Erratum to “Experimental Analyses of the Major Parameters Affecting the Intensity of Outbursts of Coal and Gas”

    W. Nie;S. J. Peng;J. Xu;L. R. Liu

  • Joint Embedding of Words and Labels for Text Classification

    Guoyin Wang;Chunyuan Li;Wenlin Wang;Yizhe Zhang

  • Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

    Dinghan Shen;Guoyin Wang;Wenlin Wang;Martin Renqiang Min

  • Decision Table Reduction based on Conditional Information Entropy

    Unknown

  • Generic normal cloud model

    Guoyin Wang;Guoyin Wang;Changlin Xu;Changlin Xu;Deyi Li

  • Pixel Convolutional Neural Network for Multi-Focus Image Fusion

    Han Tang;Bin Xiao;Weisheng Li;Guoyin Wang

  • Extension of rough set under incomplete information systems

    Guoyin Wang

  • A survey on rough set theory and its applications

    Qinghua Zhang;Qin Xie;Guoyin Wang

  • An automatic method to determine the number of clusters using decision-theoretic rough set

    Hong Yu;Zhanguo Liu;Guoyin Wang

  • A tree-based incremental overlapping clustering method using the three-way decision theory

    Hong Yu;Cong Zhang;Guoyin Wang

  • Granular ball computing classifiers for efficient, scalable and robust learning

    Shuyin Xia;Yunsheng Liu;Xin Ding;Guoyin Wang

  • GBNRS: A Novel Rough Set Algorithm for Fast Adaptive Attribute Reduction in Classification

    Shuyin Xia;Zhao Zhang;Wenhua Li;Guoyin Wang

  • Optimized Content Caching and User Association for Edge Computing in Densely Deployed Heterogeneous Networks

    Yun Li;Hui Ma;Lei Wang;Shiwen Mao

  • A Decision-Theoretic Rough Set Approach for Dynamic Data Mining

    Hongmei Chen;Tianrui Li;Chuan Luo;Shi-Jinn Horng

  • Rough reduction in algebra view and information view

    Guoyin Wang

  • Dynamic Computation Offloading and Server Deployment for UAV-Enabled Multi-Access Edge Computing

    Zhaolong Ning;Yuxuan Yang;Xiaojie Wang;Lei Guo

  • A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction

    Di Wu;Xin Luo;Mingsheng Shang;Yi He

  • An active three-way clustering method via low-rank matrices for multi-view data

    Hong Yu;Xincheng Wang;Guoyin Wang;Xianhua Zeng

  • Granular computing: from granularity optimization to multi-granularity joint problem solving

    Guoyin Wang;Guoyin Wang;Jie Yang;Ji Xu

  • A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems

    Di Wu;Xin Luo;Mingsheng Shang;Yi He

  • A Comparative Study of Algebra Viewpoint and Information Viewpoint in Attribute Reduction

    Guoyin Y. Wang;Jun Zhao;Jiujiang An;Yu Wu

  • A Survey on Rough Set Theory and Applications: A Survey on Rough Set Theory and Applications

    Guo-Yin Wang;Yi-Yu Yao;Hong Yu

Frequent Co-Authors

Lawrence Carin
Lawrence Carin Duke University
Zhe Gan
Zhe Gan Microsoft (United States)
Liqun Chen
Liqun Chen University of Surrey
Chunyuan Li
Chunyuan Li Microsoft (United States)
Michael H. Bergin
Michael H. Bergin Duke University
Guglielmo Scovazzi
Guglielmo Scovazzi Duke University

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