World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
10917
World Ranking
5836
National Ranking
775

Qinghua Zheng 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 Qinghua Zheng 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: 449 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Qinghua Zheng 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 Qinghua Zheng 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: 49 D-Index — 60th percentile

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

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

Overview

Qinghua Zheng is affiliated with Xi'an Jiaotong University in China. Their primary research field is Computer Science, with a focus on several subfields and topics.

The main subfields of their research include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Computer Networks and Communications
  • Statistical and Nonlinear Physics

The primary topics covered by their work are:

  • Advanced Graph Neural Networks
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Complex Network Analysis Techniques
  • Text and Document Classification Technologies

Their recent publications include:

  • "ZeroNAS: Differentiable Generative Adversarial Networks Search for Zero-Shot Learning," 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Self-weighted Robust LDA for Multiclass Classification with Edge Classes," 2020, ACM Transactions on Intelligent Systems and Technology
  • "A survey on deploying mobile deep learning applications: A systemic and technical perspective," 2021, Digital Communications and Networks
  • "Semantics-Guided Contrastive Network for Zero-Shot Object Detection," 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "A Deep Multi-View Framework for Anomaly Detection on Attributed Networks," 2020, IEEE Transactions on Knowledge and Data Engineering

Frequent co-authors working with Qinghua Zheng include:

  • Minnan Luo
  • Yanping Chen
  • Bo Dong
  • Feng Tian
  • Xiaojun Chang

Their publications are most often found in the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Image Processing
  • Knowledge-Based Systems
  • Expert Systems with Applications

Best Publications

  • Graph Representation Learning via Graphical Mutual Information Maximization

    Zhen Peng;Wenbing Huang;Minnan Luo;Qinghua Zheng

  • Regularized Extreme Learning Machine

    Wanyu Deng;Qinghua Zheng;Lin Chen

  • GLEAM : The GaLactic and Extragalactic All-sky MWA survey

    R. B. Wayth;E. Lenc;M. E. Bell;J. R. Callingham;J. R. Callingham

  • An Adaptive Semisupervised Feature Analysis for Video Semantic Recognition

    Minnan Luo;Xiaojun Chang;Liqiang Nie;Yi Yang

  • An E-learning Ecosystem Based on Cloud Computing Infrastructure

    Bo Dong;Qinghua Zheng;Jie Yang;Haifei Li

  • Android Malware Familial Classification and Representative Sample Selection via Frequent Subgraph Analysis

    Ming Fan;Jun Liu;Xiapu Luo;Kai Chen

  • Adaptive Unsupervised Feature Selection With Structure Regularization

    Minnan Luo;Feiping Nie;Xiaojun Chang;Yi Yang

  • A Novel Approach to Improving the Efficiency of Storing and Accessing Small Files on Hadoop: A Case Study by PowerPoint Files

    Bo Dong;Jie Qiu;Qinghua Zheng;Xiao Zhong

  • ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks

    Zhen Peng;Minnan Luo;Jundong Li;Huan Liu

  • Cross-person activity recognition using reduced kernel extreme learning machine.

    Wan-Yu Deng;Qing-Hua Zheng;Zhong-Min Wang

  • Virtual machine consolidated placement based on multi-objective biogeography-based optimization

    Qinghua Zheng;Rui Li;Xiuqi Li;Nazaraf Shah

  • ZeroNAS: Differentiable Generative Adversarial Networks Search for Zero-Shot Learning.

    Caixia Yan;Xiaojun Chang;Zhihui Li;Weili Guan

  • An optimized approach for storing and accessing small files on cloud storage

    Bo Dong;Qinghua Zheng;Feng Tian;Kuo-Ming Chao

  • BlueSky Cloud Framework: An E-Learning Framework Embracing Cloud Computing

    Bo Dong;Qinghua Zheng;Mu Qiao;Jian Shu

  • Power-Aware and Performance-Guaranteed Virtual Machine Placement in the Cloud

    Hui Zhao;Jing Wang;Feng Liu;Quan Wang

  • A multi-constraint learning path recommendation algorithm based on knowledge map

    Haiping Zhu;Feng Tian;Ke Wu;Nazaraf Shah

  • Automatic extraction of titles from general documents using machine learning

    Yunhua Hu;Hang Li;Yunbo Cao;Dmitriy Meyerzon

  • Ordinal extreme learning machine

    Wan-Yu Deng;Qing-Hua Zheng;Shiguo Lian;Lin Chen

  • Service Candidate Identification from Monolithic Systems Based on Execution Traces

    Wuxia Jin;Ting Liu;Yuanfang Cai;Rick Kazman

  • Self-weighted Robust LDA for Multiclass Classification with Edge Classes

    Caixia Yan;Xiaojun Chang;Minnan Luo;Qinghua Zheng

  • A Fast Reduced Kernel Extreme Learning Machine

    Wan-Yu Deng;Yew-Soon Ong;Qing-Hua Zheng

Frequent Co-Authors

Bryan Gaensler
Bryan Gaensler University of California, Santa Cruz
Lister Staveley-Smith
Lister Staveley-Smith University of Western Australia
Steven Tingay
Steven Tingay Curtin University
David L. Kaplan
David L. Kaplan University of Wisconsin–Milwaukee
Gianni Bernardi
Gianni Bernardi National Institute for Astrophysics
Xiaohong Guan
Xiaohong Guan Xi'an Jiaotong University
Zijiang Yang
Zijiang Yang Western Michigan University
Zheng Yan
Zheng Yan Xidian University
Lincoln J. Greenhill
Lincoln J. Greenhill Harvard University
Yan Chen
Yan Chen Northwestern University

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