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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
119
Citations
59739
World Ranking
151
National Ranking
19

Yaochu Jin 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 Yaochu Jin 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: 845 publications — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Yaochu Jin 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 Yaochu Jin 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: 119 D-Index — 99th percentile

99% 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

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award
  • 2021 - Member of Academia Europaea
  • 2021 - Alexander von Humboldt Professorship for Artificial Intelligence
  • 2021 - Alexander von Humboldt Professorship for Artificial Intelligence
  • 2016 - IEEE Fellow For contributions to evolutionary optimization

Overview

Yaochu Jin is affiliated with Westlake University in China and has a primary research focus within the field of computer science. Their scholarly contributions span several subfields, particularly artificial intelligence, computational theory and mathematics, computer vision and pattern recognition, nuclear and high energy physics, and industrial and manufacturing engineering.

Their work extensively covers advanced topics such as:

  • Advanced Multi-Objective Optimization Algorithms
  • Metaheuristic Optimization Algorithms Research
  • Evolutionary Algorithms and Applications
  • Privacy-Preserving Technologies in Data
  • Advanced Neural Network Applications
  • Machine Learning and Data Classification
  • Optimal Experimental Design Methods

Yaochu Jin has published research in a range of academic venues, with frequent contributions to:

  • arXiv (Cornell University)
  • IEEE Transactions on Evolutionary Computation
  • IEEE Computational Intelligence Magazine
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • Neurocomputing

Key recent papers include:

  • "Federated learning on non-IID data: A survey" (2021, Neurocomputing)
  • "A Coevolutionary Framework for Constrained Multiobjective Optimization Problems" (2020, IEEE Transactions on Evolutionary Computation)
  • "Artificial intelligence in recommender systems" (2020, Complex & Intelligent Systems)
  • "Evolutionary Large-Scale Multi-Objective Optimization: A Survey" (2021, ACM Computing Surveys)
  • "Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multiobjective Optimization" (2021, IEEE Transactions on Cybernetics)

Yaochu Jin's frequent coauthors include:

  • Handing Wang
  • Ran Cheng
  • M. Iwasaki
  • Kay Chen Tan
  • Xingyi Zhang

The researcher has contributed to several book publications primarily through Springer Nature and Springer Science+Business Media. Notable titles include:

  • Data-Driven Evolutionary Optimization (2021)
  • Federated Learning (2022)
  • Rescheduling Under Disruptions in Manufacturing Systems (2020)
  • Intelligence Science IV (2022)
  • Computational Evolution of Neural and Morphological Development (2023)

Best Publications

  • PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]

    Ye Tian;Ran Cheng;Xingyi Zhang;Yaochu Jin

  • Evolutionary optimization in uncertain environments-a survey

    Yaochu Jin;J. Branke

  • A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization

    Ran Cheng;Yaochu Jin;Markus Olhofer;Bernhard Sendhoff

  • A comprehensive survey of fitness approximation in evolutionary computation

    Y. Jin

  • Surrogate-assisted evolutionary computation: Recent advances and future challenges

    Yaochu Jin

  • A Competitive Swarm Optimizer for Large Scale Optimization

    Ran Cheng;Yaochu Jin

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

    Qingfu Zhang;Aimin Zhou;Yaochu Jin

  • A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization

    Xingyi Zhang;Ye Tian;Yaochu Jin

  • Federated learning on non-IID data: A survey

    Hangyu Zhu;Jinjin Xu;Shiqing Liu;Yaochu Jin

  • A framework for evolutionary optimization with approximate fitness functions

    Yaochu Jin;M. Olhofer;B. Sendhoff

  • A social learning particle swarm optimization algorithm for scalable optimization

    Ran Cheng;Yaochu Jin

  • A Survey of Deep Learning Applications to Autonomous Vehicle Control

    Sampo Kuutti;Richard Bowden;Yaochu Jin;Phil Barber

  • An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility

    Ye Tian;Ran Cheng;Xingyi Zhang;Fan Cheng

  • Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement

    Yaochu Jin

  • A Decision Variable Clustering-Based Evolutionary Algorithm for Large-Scale Many-Objective Optimization

    Xingyi Zhang;Ye Tian;Ran Cheng;Yaochu Jin

  • Data-Driven Evolutionary Optimization: An Overview and Case Studies

    Yaochu Jin;Handing Wang;Tinkle Chugh;Dan Guo

  • A Coevolutionary Framework for Constrained Multiobjective Optimization Problems

    Ye Tian;Tao Zhang;Jianhua Xiao;Xingyi Zhang

  • A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization

    Tinkle Chugh;Yaochu Jin;Kaisa Miettinen;Jussi Hakanen

  • An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization

    Xingyi Zhang;Ye Tian;Ran Cheng;Yaochu Jin

  • Introduction to Machine Learning

    Yaochu Jin;Handing Wang;Chaoli Sun

  • Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies

    Yaochu Jin;B. Sendhoff

  • PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization

    Ye Tian;Ran Cheng;Xingyi Zhang;Yaochu Jin

Frequent Co-Authors

Bernhard Sendhoff
Bernhard Sendhoff Honda (Germany)
Xingyi Zhang
Xingyi Zhang Anhui University
Xin Yao
Xin Yao Lingnan University
Handing Wang
Handing Wang Xidian University
Yew-Soon Ong
Yew-Soon Ong Nanyang Technological University
Qingfu Zhang
Qingfu Zhang City University of Hong Kong
Jianchao Zeng
Jianchao Zeng North University of China
Shengxiang Yang
Shengxiang Yang De Montfort University
Tianyou Chai
Tianyou Chai Northeastern University
Jürgen Branke
Jürgen Branke University of Warwick

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