World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
83
Citations
42972
World Ranking
883
National Ranking
132

Qingfu 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 Qingfu 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: 378 publications — 85th percentile

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

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

Qingfu 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 Qingfu 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: 83 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2017 - IEEE Fellow For contributions to multi-objective evolutionary computation methodologies

Overview

Qingfu Zhang is a researcher affiliated with the City University of Hong Kong in China whose work spans several interconnected areas within computer science and engineering. Their publication record includes a strong focus on evolutionary computation, optimization algorithms, and artificial intelligence.

Their recent papers include:

  • "A Constrained Multiobjective Evolutionary Algorithm With Detect-and-Escape Strategy" (2020, IEEE Transactions on Evolutionary Computation)
  • "Investigating the Properties of Indicators and an Evolutionary Many-Objective Algorithm Using Promising Regions" (2020, IEEE Transactions on Evolutionary Computation)
  • "Band structure engineered tunneling heterostructures for high-performance visible and near-infrared photodetection" (2020, Science China Materials)
  • "Multi-View Spectral Clustering Tailored Tensor Low-Rank Representation" (2021, IEEE Transactions on Circuits and Systems for Video Technology)
  • "Building Change Detection for VHR Remote Sensing Images via Local-Global Pyramid Network and Cross-Task Transfer Learning Strategy" (2021, IEEE Transactions on Geoscience and Remote Sensing)

Qingfu Zhang's frequent co-authors include:

  • Zhenkun Wang
  • Xi Lin
  • Fei Liu
  • Jianyong Sun
  • Hui Liu

They have contributed extensively to several publication venues, predominantly in the fields of evolutionary computation and artificial intelligence:

  • arXiv (Cornell University)
  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Cybernetics
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence

In terms of fields of study, their work is mainly situated within:

  • Computer Science
  • Engineering

Within these broader fields, their subfields of study cover:

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Industrial and Manufacturing Engineering
  • Computational Mechanics

The main research topics associated with their work include:

  • Advanced Multi-Objective Optimization Algorithms
  • Metaheuristic Optimization Algorithms Research
  • Evolutionary Algorithms and Applications
  • Vehicle Routing Optimization Methods
  • Sparse and Compressive Sensing Techniques
  • Advanced Manufacturing and Logistics Optimization
  • Complex Network Analysis Techniques

Qingfu Zhang has also authored a book published by Springer Science+Business Media titled Evolutionary Multi-Criterion Optimization (2021).

They have been recognized by the IEEE as a Fellow since 2017 for their contributions to multi-objective evolutionary computation methodologies.

Best Publications

  • MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition

    Qingfu Zhang;Hui Li

  • Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II

    Hui Li;Qingfu Zhang

  • Multiobjective evolutionary algorithms: A survey of the state of the art

    Aimin Zhou;Bo-Yang Qu;Hui Li;Shi-Zheng Zhao

  • Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters

    Yong Wang;Zixing Cai;Qingfu Zhang

  • An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition

    Ke Li;Kalyanmoy Deb;Qingfu Zhang;Sam Kwong

  • Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition

    Qingfu Zhang;Aimin Zhou;Shizheng Zhao;Ponnuthurai Nagaratnam Suganthan

  • RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm

    Qingfu Zhang;Aimin Zhou;Yaochu Jin

  • Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems

    Hai-Lin Liu;Fangqing Gu;Qingfu Zhang

  • Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model

    Qingfu Zhang;Wudong Liu;Edward Tsang;Botond Virginas

  • The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances

    Qingfu Zhang;Wudong Liu;Hui Li

  • A Gaussian Process Surrogate Model Assisted Evolutionary Algorithm for Medium Scale Expensive Optimization Problems

    Bo Liu;Qingfu Zhang;Georges G. E. Gielen

  • A Population Prediction Strategy for Evolutionary Dynamic Multiobjective Optimization

    Aimin Zhou;Yaochu Jin;Qingfu Zhang

  • Push and pull search for solving constrained multi-objective optimization problems

    Zhun Fan;Wenji Li;Xinye Cai;Hui Li

  • Distributed evolutionary algorithms and their models

    Yue-Jiao Gong;Wei-Neng Chen;Zhi-Hui Zhan;Jun Zhang

  • Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition

    Ke Li;Alvaro Fialho;Sam Kwong;Qingfu Zhang

  • DE/EDA: a new evolutionary algorithm for global optimization

    Jianyong Sun;Qingfu Zhang;Edward P. K. Tsang

  • Stable Matching-Based Selection in Evolutionary Multiobjective Optimization

    Ke Li;Qingfu Zhang;Sam Kwong;Miqing Li

  • An orthogonal genetic algorithm for multimedia multicast routing

    Qingfu Zhang;Yiu-Wing Leung

  • Approximating the Set of Pareto-Optimal Solutions in Both the Decision and Objective Spaces by an Estimation of Distribution Algorithm

    Aimin Zhou;Qingfu Zhang;Yaochu Jin

  • Combining Model-based and Genetics-based Offspring Generation for Multi-objective Optimization Using a Convergence Criterion

    Aimin Zhou;Yaochu Jin;Qingfu Zhang;B. Sendhoff

  • Objective Reduction in Many-Objective Optimization: Linear and Nonlinear Algorithms

    D. K. Saxena;J. A. Duro;A. Tiwari;K. Deb

Frequent Co-Authors

Edward Tsang
Edward Tsang University of Essex
Sam Kwong
Sam Kwong Lingnan University
Yaochu Jin
Yaochu Jin Westlake University
Kalyanmoy Deb
Kalyanmoy Deb Michigan State University
Licheng Jiao
Licheng Jiao Xidian University
Kun Yang
Kun Yang University of Essex
Bernhard Sendhoff
Bernhard Sendhoff Honda (Germany)
Xin Yao
Xin Yao Lingnan University
Pei-Chann Chang
Pei-Chann Chang Yuan Ze University

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