World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
76
Citations
19561
World Ranking
1359
National Ranking
183

Gang Kou 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 Gang Kou 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: 290 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Gang Kou 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 Gang Kou 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: 76 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Overview

Gang Kou is a researcher affiliated with Southwestern University of Finance and Economics in China. Their work primarily spans the field of Computer Science with a significant focus on Management Science and Operations Research, Artificial Intelligence, Economics and Econometrics, Statistical and Nonlinear Physics, and Accounting.

Their research covers various specialized topics, including:

  • Multi-Criteria Decision Making
  • Financial Distress and Bankruptcy Prediction
  • Imbalanced Data Classification Techniques
  • Complex Network Analysis Techniques
  • Opinion Dynamics and Social Influence
  • Rough Sets and Fuzzy Logic
  • Efficiency Analysis Using DEA

Gang Kou has contributed frequently to academic journals and conferences. The primary venues for their publications include:

  • Financial Innovation
  • Information Sciences
  • Applied Soft Computing
  • Information Fusion
  • International Journal of Information Technology & Decision Making

Among recent papers authored by Gang Kou are:

  • Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach, 2021, Financial Innovation
  • Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection, 2020, Decision Support Systems

Gang Kou has collaborated extensively with frequent co-authors including:

  • Yi Peng
  • Hui Xiao
  • Hasan Dınçer
  • Serhat Yüksel
  • Enrique Herrera-Viedma

The scholar has also contributed to book publications, including a book titled Innovative Approaches to Decision Making, published by World Scientific in 2024.

Best Publications

  • Evaluation of clustering algorithms for financial risk analysis using MCDM methods

    Gang Kou;Yi Peng;Guoxun Wang

  • EVALUATION OF CLASSIFICATION ALGORITHMS USING MCDM AND RANK CORRELATION

    Gang Kou;Yanqun Lu;Yi Peng;Yong Shi

  • A systematic review of blockchain

    Min Xu;Xingtong Chen;Gang Kou

  • Consensus Reaching in Social Network Group Decision Making: Research Paradigms and Challenges

    Yucheng Dong;Quanbo Zha;Hengjie Zhang;Gang Kou

  • A descriptive framework for the field of data mining and knowledge discovery

    Yong Shi;Zhengxin Chen;Yi Peng

  • Pairwise comparison matrix in multiple criteria decision making

    Gang Kou;Daji Ergu;Yang Chen;Changsheng Lin

  • A review on trust propagation and opinion dynamics in social networks and group decision making frameworks

    Raquel Ureña;Gang Kou;Yucheng Dong;Francisco Chiclana;Francisco Chiclana

  • Soft consensus cost models for group decision making and economic interpretations

    Huanhuan Zhang;Gang Kou;Yi Peng

  • IT capabilities and product innovation performance

    Yang Chen;Yi Wang;Saggi Nevo;Jose Benitez-Amado

  • A cosine maximization method for the priority vector derivation in AHP

    Gang Kou;Changsheng Lin;Changsheng Lin

  • Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection

    Gang Kou;Yong Xu;Yi Peng;Feng Shen

  • The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment

    Daji Ergu;Gang Kou;Yi Peng;Yong Shi

  • A survey on the fusion process in opinion dynamics

    Yucheng Dong;Min Zhan;Gang Kou;Zhaogang Ding

  • Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods

    Gang Kou;Pei Yang;Yi Peng;Feng Xiao

  • An overview on feedback mechanisms with minimum adjustment or cost in consensus reaching in group decision making: Research paradigms and challenges

    Hengjie Zhang;Sihai Zhao;Gang Kou;Cong-Cong Li

  • Optimization Based Data Mining: Theory and Applications

    Yong Shi;Yingjie Tian;Gang Kou;Yi Peng

  • Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: An application in financial inclusion

    Xiangrui Chao;Gang Kou;Yi Peng;Enrique Herrera Viedma;Enrique Herrera Viedma

  • A Group Decision Making Model for Integrating Heterogeneous Information

    Guangxu Li;Gang Kou;Yi Peng

  • Enhancing data consistency in decision matrix: Adapting Hadamard model to mitigate judgment contradiction

    Gang Kou;Daji Ergu;Daji Ergu;Jennifer Shang

  • Machine learning methods for systemic risk analysis in financial sectors

    Gang Kou;Xiangrui Chao;Yi Peng;Fawaz E. Alsaadi

  • A simple method to improve the consistency ratio of the pair-wise comparison matrix in ANP

    Daji Ergu;Daji Ergu;Gang Kou;Yi Peng;Yong Shi;Yong Shi

Frequent Co-Authors

Yong Shi
Yong Shi Chinese Academy of Sciences
Yi Peng
Yi Peng University of Electronic Science and Technology of China
Enrique Herrera-Viedma
Enrique Herrera-Viedma University of Granada
Yingjie Tian
Yingjie Tian University of Chinese Academy of Sciences
Yucheng Dong
Yucheng Dong Sichuan University
Francisco Chiclana
Francisco Chiclana De Montfort University
Jennifer Shang
Jennifer Shang University of Pittsburgh
Hengjie Zhang
Hengjie Zhang Hohai University
Juan M. Corchado
Juan M. Corchado University of Salamanca
Shui Yu
Shui Yu University of Technology Sydney

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