World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
15371
World Ranking
2219
National Ranking
304

Yuhua Qian 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 Yuhua Qian 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: 189 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Yuhua Qian 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 Yuhua Qian 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: 67 D-Index — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Overview

Yuhua Qian is affiliated with Shanxi University in China and has a significant research presence in the field of computer science. Their work primarily focuses on areas related to artificial intelligence, computer vision and pattern recognition, computational theory and mathematics, information systems, and media technology.

The main topics covered in Yuhua Qian's research include:

  • Rough Sets and Fuzzy Logic
  • Text and Document Classification Technologies
  • Data Mining Algorithms and Applications
  • Image Retrieval and Classification Techniques
  • Face and Expression Recognition
  • Advanced Clustering Algorithms Research
  • Advanced Graph Neural Networks

Yuhua Qian has published extensively, with recent papers including the following:

  • "Feature Selection Using Fuzzy Neighborhood Entropy-Based Uncertainty Measures for Fuzzy Neighborhood Multigranulation Rough Sets" (2020) published in IEEE Transactions on Fuzzy Systems
  • "Feature Selection With Missing Labels Using Multilabel Fuzzy Neighborhood Rough Sets and Maximum Relevance Minimum Redundancy" (2021) published in IEEE Transactions on Fuzzy Systems
  • "A Regret-Based Three-Way Decision Model Under Interval Type-2 Fuzzy Environment" (2020) published in IEEE Transactions on Fuzzy Systems
  • "Multilabel feature selection using ML-ReliefF and neighborhood mutual information for multilabel neighborhood decision systems" (2020) published in Information Sciences
  • "Attribute group for attribute reduction" (2020) published in Information Sciences

The scientist frequently collaborates with several co-authors, including:

  • Weiping Ding
  • Xinyan Liang
  • Jieting Wang
  • Xibei Yang
  • Feijiang Li

Yuhua Qian's publications appear most often in these venues:

  • IEEE Transactions on Fuzzy Systems
  • Information Sciences
  • arXiv (Cornell University)
  • International Journal of Machine Learning and Cybernetics
  • SSRN Electronic Journal

The focus areas reflect a strong emphasis on fuzzy logic and rough sets, alongside computational intelligence methods applied to feature selection, classification, and decision-making models under uncertainty. The work demonstrates an intersection of theoretical and applied research in advanced algorithms relating to data mining, pattern recognition, and machine learning.

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

  • Multigranulation decision-theoretic rough sets

    Yuhua Qian;Hu Zhang;Yanli Sang;Jiye Liang

  • Three-way cognitive concept learning via multi-granularity

    Jinhai Li;Chenchen Huang;Jianjun Qi;Yuhua Qian

  • Concept learning via granular computing

    Jinhai Li;Changlin Mei;Weihua Xu;Yuhua Qian

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

    Jiye Liang;Feng Wang;Chuangyin Dang;Yuhua Qian

  • Test-cost-sensitive attribute reduction

    Fan Min;Huaping He;Yuhua Qian;William Zhu

  • A Fitting Model for Feature Selection With Fuzzy Rough Sets

    Changzhong Wang;Yali Qi;Mingwen Shao;Qinghua Hu

  • NMGRS: Neighborhood-based multigranulation rough sets

    Guoping Lin;Yuhua Qian;Jinjin Li

  • Feature subset selection based on fuzzy neighborhood rough sets

    Changzhong Wang;Mingwen Shao;Qiang He;Yuhua Qian

  • Feature Selection Based on Neighborhood Discrimination Index

    Changzhong Wang;Qinghua Hu;Xizhao Wang;Degang Chen

  • Feature selection using neighborhood entropy-based uncertainty measures for gene expression data classification

    Lin Sun;Xiaoyu Zhang;Yuhua Qian;Jiucheng Xu

  • 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

  • Feature Selection Using Fuzzy Neighborhood Entropy-Based Uncertainty Measures for Fuzzy Neighborhood Multigranulation Rough Sets

    Lin Sun;Lanying Wang;Weiping Ding;Yuhua Qian

  • 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

  • COMBINATION ENTROPY AND COMBINATION GRANULATION IN ROUGH SET THEORY

    Yuhua Qian;Jiye Liang

Frequent Co-Authors

Jiye Liang
Jiye Liang Shanxi University
Chuangyin Dang
Chuangyin Dang City University of Hong Kong
Xibei Yang
Xibei Yang Jiangsu University of Science and Technology
Hamido Fujita
Hamido Fujita University of Technology Malaysia
Weiping Ding
Weiping Ding Nantong University
Deyu Li
Deyu Li Shanxi University
Qinghua Hu
Qinghua Hu Tianjin University
Jingyu Yang
Jingyu Yang Nanjing University of Science and Technology
Xianzhong Zhou
Xianzhong Zhou Nanjing University
Witold Pedrycz
Witold Pedrycz University of Alberta

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