World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
10697
World Ranking
5090
National Ranking
690

Degang Chen 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 Degang Chen 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: 180 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Degang Chen 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 Degang Chen 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: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Overview

Degang Chen is affiliated with North China Electric Power University in China and has a significant research presence in the field of Computer Science. Their work spans multiple subfields including Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Computer Vision and Pattern Recognition, and Management Science and Operations Research.

The scientist's research topics are diverse, with notable focus areas in Rough Sets and Fuzzy Logic, Data Mining Algorithms and Applications, Text and Document Classification Technologies, Multi-Criteria Decision Making, Image Retrieval and Classification Techniques, Fuzzy Logic and Control Systems, and Web Data Mining and Analysis.

Degang Chen has published multiple papers in a range of academic journals. Recent publications include:

  • "A novel approach to attribute reduction based on weighted neighborhood rough sets," 2021, Knowledge-Based Systems
  • "Jensen's inequalities for set-valued and fuzzy set-valued functions," 2020, Fuzzy Sets and Systems
  • "Proximity ranking-based multimodal differential evolution," 2023, Swarm and Evolutionary Computation
  • "Attribute reduction based on overlap degree and k-nearest-neighbor rough sets in decision information systems," 2021, Information Sciences
  • "Label correlation in multi-label classification using local attribute reductions with fuzzy rough sets," 2021, Fuzzy Sets and Systems

Frequent publication venues for Degang Chen include:

  • International Journal of Machine Learning and Cybernetics
  • Information Sciences
  • IEEE Transactions on Fuzzy Systems
  • Fuzzy Sets and Systems
  • Knowledge-Based Systems

Frequent co-authors collaborating with Degang Chen are:

  • Xiaoya Che
  • Hui Wang
  • Meng Hu
  • Eric C.C. Tsang
  • Yanting Guo

Degang Chen's work contributes primarily to the development and application of computational methods in the areas of rough sets and fuzzy logic, with implications for data mining, classification, and decision-making systems. The combination of these research areas highlights a coordinated approach toward complex information processing systems and algorithms.

Best Publications

  • The parameterization reduction of soft sets and its applications

    Degang Chen;E. C. C. Tsang;Daniel S. Yeung;Xizhao Wang

  • On the generalization of fuzzy rough sets

    D.S. Yeung;Degang Chen;E.C.C. Tsang;J.W.T. Lee

  • Feature selection in mixed data

    Xiao Zhang;Changlin Mei;Degang Chen;Jinhai Li

  • Attributes Reduction Using Fuzzy Rough Sets

    E.C.C. Tsang;Degang Chen;D.S. Yeung;Xi-Zhao Wang

  • The Model of Fuzzy Variable Precision Rough Sets

    Suyun Zhao;E. Tsang;Degang Chen

  • A Fitting Model for Feature Selection With Fuzzy Rough Sets

    Changzhong Wang;Yali Qi;Mingwen Shao;Qinghua Hu

  • A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets

    Unknown

  • Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications

    Qinghua Hu;Lei Zhang;Degang Chen;Witold Pedrycz

  • Feature Selection Based on Neighborhood Discrimination Index

    Changzhong Wang;Qinghua Hu;Xizhao Wang;Degang Chen

  • Rough approximations on a complete completely distributive lattice with applications to generalized rough sets

    Unknown

  • Learning fuzzy rules from fuzzy samples based on rough set technique

    Xizhao Wang;Eric C. C. Tsang;Suyun Zhao;Degang Chen

  • Kernelized Fuzzy Rough Sets and Their Applications

    Qinghua Hu;Daren Yu;Witold Pedrycz;Degang Chen

  • Feature Selection Based on Neighborhood Self-Information

    Changzhong Wang;Yang Huang;Mingwen Shao;Qinghua Hu

  • A Novel Algorithm for Finding Reducts With Fuzzy Rough Sets

    Degang Chen;Lei Zhang;Suyun Zhao;Qinghua Hu

  • Fuzzy rough set theory for the interval-valued fuzzy information systems

    Bingzhen Sun;Zengtai Gong;Degang Chen

  • Rough set theory for the interval-valued fuzzy information systems

    Zengtai Gong;Bingzhen Sun;Degang Chen

  • Covering-Based Variable Precision $(\mathcal {I},\mathcal {T})$ -Fuzzy Rough Sets With Applications to Multiattribute Decision-Making

    Haibo Jiang;Jianming Zhan;Degang Chen

  • Fuzzy Rough Attribute Reduction for Categorical Data

    Changzhong Wang;Yan Wang;Mingwen Shao;Yuhua Qian

  • Approximations and reducts with covering generalized rough sets

    Unknown

  • A systematic study on attribute reduction with rough sets based on general binary relations

    Changzhong Wang;Congxin Wu;Degang Chen

  • Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach

    Suyun Zhao;E.C.C. Tsang;Degang Chen;Xizhao Wang

  • Attribute Reduction for Heterogeneous Data Based on the Combination of Classical and Fuzzy Rough Set Models

    Degang Chen;Yanyan Yang

  • On the upper approximations of covering generalized rough sets

    E.C.C. Tsang;Degang Chen;J.W.T. Lee;D.S. Yeung

  • Active Incremental Feature Selection Using a Fuzzy-Rough-Set-Based Information Entropy

    Xiao Zhang;Changlin Mei;Degang Chen;Yanyan Yang

Frequent Co-Authors

Qinghua Hu
Qinghua Hu Tianjin University
Xi-Zhao Wang
Xi-Zhao Wang Tsinghua University
Sam Kwong
Sam Kwong Lingnan University
Hui Wang
Hui Wang University of Ulster
Cheng Wu
Cheng Wu Tsinghua University
Xibei Yang
Xibei Yang Jiangsu University of Science and Technology
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Jianming Zhan
Jianming Zhan Hubei University for Nationalities
Witold Pedrycz
Witold Pedrycz University of Alberta
Yuhua Qian
Yuhua Qian Shanxi University

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