World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
10618
World Ranking
5599
National Ranking
743

Chuangyin Dang 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 Chuangyin Dang 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: 243 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Chuangyin Dang 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 Chuangyin Dang 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

Chuangyin Dang is a researcher affiliated with the City University of Hong Kong in China. Their academic work primarily spans the fields of Computer Science and Economics, Econometrics and Finance, with significant contributions also noted in subfields such as Economics and Econometrics, Management Science and Operations Research, Computer Vision and Pattern Recognition, Numerical Analysis, and Artificial Intelligence.

Their research focuses on a range of topics, including:

  • Game Theory and Applications
  • Economic Theories and Models
  • Advanced Optimization Algorithms Research
  • Face and Expression Recognition
  • Video Surveillance and Tracking Methods
  • Game Theory and Voting Systems
  • Supply Chain and Inventory Management

Dang has contributed to numerous journals and conference publications. Their frequent publication venues include:

  • arXiv (Cornell University)
  • International Journal of Machine Learning and Cybernetics
  • SSRN Electronic Journal
  • INFORMS Journal on Computing
  • Journal of Optimization Theory and Applications

Among their recent published papers are:

  • "Distributed Prescribed-Time Formation Control for Underactuated Surface Vehicles With Input Saturation: Theory and Experiment" (2024), published in IEEE Transactions on Intelligent Transportation Systems
  • "An Interior-Point Differentiable Path-Following Method to Compute Stationary Equilibria in Stochastic Games" (2022), published in INFORMS Journal on Computing
  • "The Optimal Carbon Tax Mechanism for Managing Carbon Emissions" (2023), published in Socio-Economic Planning Sciences
  • "Path-based Estimation for Link Prediction" (2021), published in International Journal of Machine Learning and Cybernetics
  • "Multiple Metric Learning via Local Metric Fusion" (2022), published in Information Sciences

Dang has collaborated frequently with other researchers, including:

  • Yiyin Cao
  • Peixuan Li
  • Jiye Liang
  • P. Jean-Jacques Herings
  • Zhiqing Meng

Best Publications

  • MGRS: A multi-granulation rough set

    Yuhua Qian;Jiye Liang;Yiyu Yao;Chuangyin Dang

  • Positive approximation: An accelerator for attribute reduction in rough set theory

    Yuhua Qian;Jiye Liang;Witold Pedrycz;Chuangyin Dang

  • Incomplete Multigranulation Rough Set

    Yuhua Qian;Jiye Liang;Chuangyin Dang

  • A NEW METHOD FOR MEASURING UNCERTAINTY AND FUZZINESS IN ROUGH SET THEORY

    Jiye Liang;Kwai-Sang Chin;Chuangyin Dang;Richard C. M. Yam

  • A Group Incremental Approach to Feature Selection Applying Rough Set Technique

    Jiye Liang;Feng Wang;Chuangyin Dang;Yuhua Qian

  • Stability Analysis of Positive Switched Linear Systems With Delays

    Xingwen Liu;Chuangyin Dang

  • Knowledge structure, knowledge granulation and knowledge distance in a knowledge base

    Yuhua Qian;Jiye Liang;Chuangyin Dang

  • Interval ordered information systems

    Yuhua Qian;Jiye Liang;Chuangyin Dang

  • An efficient accelerator for attribute reduction from incomplete data in rough set framework

    Yuhua Qian;Jiye Liang;Witold Pedrycz;Chuangyin Dang

  • An efficient rough feature selection algorithm with a multi-granulation view

    Jiye Liang;Feng Wang;Chuangyin Dang;Yuhua Qian

  • Set-valued ordered information systems

    Yuhua Qian;Chuangyin Dang;Jiye Liang;Dawei Tang

  • Information Granularity in Fuzzy Binary GrC Model

    Yuhua Qian;Jiye Liang;Wei-zhi Z Wu;Chuangyin Dang

  • An Evolutionary Algorithm for Global Optimization Based on Level-Set Evolution and Latin Squares

    Yuping Wang;Chuangyin Dang

  • Fuzzy-rough feature selection accelerator

    Yuhua Qian;Qi Wang;Honghong Cheng;Jiye Liang

  • A dissimilarity measure for the k-Modes clustering algorithm

    Fuyuan Cao;Jiye Liang;Deyu Li;Liang Bai

  • Determining the number of clusters using information entropy for mixed data

    Jiye Liang;Xingwang Zhao;Deyu Li;Fuyuan Cao

  • An aftertreatment technique for improving the accuracy of Adomian's decomposition method

    Y.C. Jiao;Y. Yamamoto;C. Dang;Y. Hao

  • Local rough set: A solution to rough data analysis in big data

    Yuhua Qian;Xinyan Liang;Qi Wang;Jiye Liang

  • Measures for evaluating the decision performance of a decision table in rough set theory

    Yuhua Qian;Jiye Liang;Deyu Li;Haiyun Zhang

  • The $K$ -Means-Type Algorithms Versus Imbalanced Data Distributions

    Jiye Liang;Liang Bai;Chuangyin Dang;Fuyuan Cao

  • Attribute reduction for dynamic data sets

    Feng Wang;Jiye Liang;Chuangyin Dang

Frequent Co-Authors

Jiye Liang
Jiye Liang Shanxi University
Yuhua Qian
Yuhua Qian Shanxi University
Shouyang Wang
Shouyang Wang Chinese Academy of Sciences
Yinyu Ye
Yinyu Ye Stanford University
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Deyu Li
Deyu Li Shanxi University
Songtao Guo
Songtao Guo Chongqing University
Bing Liu
Bing Liu University of Illinois at Chicago
Witold Pedrycz
Witold Pedrycz University of Alberta
Hamid Reza Karimi
Hamid Reza Karimi Polytechnic University of Milan

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