World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
9332
World Ranking
9139
National Ranking
3887

Yan-Qing Zhang 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 Yan-Qing Zhang 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: 261 publications — 65th percentile

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

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

Yan-Qing Zhang 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 Yan-Qing Zhang 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Yan-Qing Zhang is affiliated with Georgia State University in the United States. Their primary research domains encompass engineering and computer science, with specific contributions totaling 37 publications in engineering and 31 in computer science.

The subfields of study where Yan-Qing Zhang has contributed include:

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Hardware and Architecture
  • Control and Systems Engineering

Their research topics cover a range of specialized areas such as:

  • VLSI and FPGA Design Techniques
  • Advanced Memory and Neural Computing
  • Video Coding and Compression Technologies
  • Advanced Neural Network Applications
  • Ferroelectric and Negative Capacitance Devices
  • Embedded Systems Design Techniques
  • Advanced Wireless Communication Technologies

Yan-Qing Zhang has contributed to various noted publication venues, including:

  • Journal of Agricultural and Food Chemistry
  • IEEE Transactions on Vehicular Technology
  • IEEE Journal of Solid-State Circuits
  • IEEE Micro
  • Communications of the ACM

Among recent papers associated with Yan-Qing Zhang's research environment or collaborations, the following are notable:

  • "A 0.32-128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm" (2020), IEEE Journal of Solid-State Circuits
  • "Accelerating Chip Design With Machine Learning" (2020), IEEE Micro
  • "Enantioselective Bioactivity, Toxicity, and Degradation in Vegetables and Soil of Chiral Fungicide Mandipropamid" (2021), Journal of Agricultural and Food Chemistry
  • "Selectively Desirable Rapeseed and Corn Stalks Distinctive for Low-Cost Bioethanol Production and High-Active Biosorbents" (2020), Waste and Biomass Valorization
  • "Simba" (2021), Communications of the ACM

Frequent co-authors collaborating with Yan-Qing Zhang include:

  • Brucek Khailany
  • Haoxing Ren
  • Mohammed El-Hajjar
  • Lajos Hanzo
  • Rangharajan Venkatesan

Best Publications

  • Single Valued Neutrosophic Sets

    Haibin Wang;Florentin Smarandache;Yan-Qing Zhang;Rajshekhar Sunderraman

  • SVMs Modeling for Highly Imbalanced Classification

    Yuchun Tang;Yan-Qing Zhang;N.V. Chawla;S. Krasser

  • A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

    Yunan Luo;Xinbin Zhao;Jingtian Zhou;Jinglin Yang

  • Support vector machines and Word2vec for text classification with semantic features

    Joseph Lilleberg;Yun Zhu;Yanqing Zhang

  • A genetic algorithm-based method for feature subset selection

    Feng Tan;Xuezheng Fu;Yanqing Zhang;Anu G. Bourgeois

  • Using Word2Vec to process big text data

    Long Ma;Yanqing Zhang

  • Development of Two-Stage SVM-RFE Gene Selection Strategy for Microarray Expression Data Analysis

    Yuchun Tang;Yan-Qing Zhang;Zhen Huang

  • Parallel granular neural networks for fast credit card fraud detection

    M. Syeda;Yan-Qing Zhang;Yi Pan

  • Compensatory neurofuzzy systems with fast learning algorithms

    Yan-Qing Zhang;A. Kandel

  • Granular neural networks for numerical-linguistic data fusion and knowledge discovery

    Yan-Qing Zhang;M.D. Fraser;R.A. Gagliano;A. Kandel

  • Visual Sentiment Analysis for Social Images Using Transfer Learning Approach

    Unknown

  • Support vector machines with genetic fuzzy feature transformation for biomedical data classification

    Bo Jin;Y.C. Tang;Yan-Qing Zhang

  • A New Improved K-Means Algorithm with Penalized Term

    Zejin Ding;Jian Yu;Yan-Qing Zhang

  • Stability analysis of fuzzy control systems

    A. Kandel;Y. Luo;Y. Q Zhang

  • Granular support vector machines with association rules mining for protein homology prediction

    Yuchun Tang;Bo Jin;Yan-Qing Zhang

  • Machine Learning in Bioinformatics

    Yanqing Zhang;Jagath C. Rajapakse

  • Interval Neutrosophic Logics: Theory and Applications

    Haibin Wang;Florentin Smarandache;Yanqing Zhang;Rajshekhar Sunderraman

  • Statistical fuzzy interval neural networks for currency exchange rate time series prediction

    Yan-Qing Zhang;Xuhui Wan

  • Evolutionary fuzzy neural networks for hybrid financial prediction

    Lixin Yu;Yan-Qing Zhang

  • Compensatory Genetic Fuzzy Neural Networks and Their Applications

    Yan-Qing Zhang;Abraham Kandel

  • Granular support vector machines for medical binary classification problems

    Yuchun Tang;Bo Jin;Yi Sun;Yan-Qing Zhang

Frequent Co-Authors

Abraham Kandel
Abraham Kandel University of South Florida
Xiaohua Hu
Xiaohua Hu Drexel University
Alexander Zelikovsky
Alexander Zelikovsky Georgia State University
Tsau Young Lin
Tsau Young Lin San Jose State University
Binghe Wang
Binghe Wang Georgia State University
Florentin Smarandache
Florentin Smarandache University of New Mexico
Angela R. Laird
Angela R. Laird Florida International University
Peter T. Fox
Peter T. Fox The University of Texas Health Science Center at San Antonio
Jessica A. Turner
Jessica A. Turner The Ohio State University
David A. Washburn
David A. Washburn Georgia State University

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