World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
79
Citations
22296
World Ranking
1153
National Ranking
67

Shengxiang Yang 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 Shengxiang Yang 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 523 publications — 94th percentile

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

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

Shengxiang Yang 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 Shengxiang Yang sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 79 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Overview

Shengxiang Yang is affiliated with De Montfort University in the United Kingdom and has contributed extensively to the fields of computer science and engineering. Their work primarily spans artificial intelligence, computational theory and mathematics, and various engineering disciplines.

Their research topics include:

  • Metaheuristic Optimization Algorithms Research
  • Advanced Multi-Objective Optimization Algorithms
  • Evolutionary Algorithms and Applications
  • Optimal Experimental Design Methods
  • Data Stream Mining Techniques
  • Vehicle Routing Optimization Methods
  • Topology Optimization in Engineering

Yang has authored publications in several venues, frequently contributing to:

  • Swarm and Evolutionary Computation
  • Information Sciences
  • IEEE Transactions on Evolutionary Computation
  • Applied Soft Computing
  • SSRN Electronic Journal

Notable recent papers include:

  • "An Adaptive Localized Decision Variable Analysis Approach to Large-Scale Multiobjective and Many-Objective Optimization," 2021, IEEE Transactions on Cybernetics
  • "Learning to Optimize: Reference Vector Reinforcement Learning Adaption to Constrained Many-Objective Optimization of Industrial Copper Burdening System," 2021, IEEE Transactions on Cybernetics
  • "Handling Constrained Many-Objective Optimization Problems via Problem Transformation," 2020, IEEE Transactions on Cybernetics
  • "Evolutionary Dynamic Multi-objective Optimisation: A Survey," 2022, ACM Computing Surveys
  • "A dual-population algorithm based on alternative evolution and degeneration for solving constrained multi-objective optimization problems," 2021, Information Sciences

Frequent co-authors in their collaborative work include:

  • Juan Zou
  • Jinhua Zheng
  • Yaru Hu
  • Changhe Li
  • Yuan Liu

Yang has contributed to book publications under Springer Science+Business Media, including the 2024 title Intelligent Information Processing XII.

Best Publications

  • A Grid-Based Evolutionary Algorithm for Many-Objective Optimization

    Shengxiang Yang;Miqing Li;Xiaohui Liu;Jinhua Zheng

  • Evolutionary dynamic optimization: A survey of the state of the art

    Trung Thanh Nguyen;Shengxiang Yang;Juergen Branke

  • Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization

    Miqing Li;Shengxiang Yang;Xiaohui Liu

  • A survey of swarm intelligence for dynamic optimization: Algorithms and applications

    Michalis Mavrovouniotis;Changhe Li;Shengxiang Yang

  • A benchmark test suite for evolutionary many-objective optimization

    Ran Cheng;Miqing Li;Ye Tian;Xingyi Zhang

  • A Self-Learning Particle Swarm Optimizer for Global Optimization Problems

    Changhe Li;Shengxiang Yang;Trung Thanh Nguyen

  • A Clustering Particle Swarm Optimizer for Locating and Tracking Multiple Optima in Dynamic Environments

    Shengxiang Yang;Changhe Li

  • A Strength Pareto Evolutionary Algorithm Based on Reference Direction for Multiobjective and Many-Objective Optimization

    Shouyong Jiang;Shengxiang Yang

  • A Steady-State and Generational Evolutionary Algorithm for Dynamic Multiobjective Optimization

    Shouyong Jiang;Shengxiang Yang

  • Experimental study on population-based incremental learning algorithms for dynamic optimization problems

    Shengxiang Yang;Xin Yao

  • Population-Based Incremental Learning With Associative Memory for Dynamic Environments

    Shengxiang Yang;Xin Yao

  • Pareto or Non-Pareto: Bi-Criterion Evolution in Multiobjective Optimization

    Miqing Li;Shengxiang Yang;Xiaohui Liu

  • Genetic algorithms with memory-and elitism-based immigrants in dynamic environments

    Shengxiang Yang

  • An Adaptive Localized Decision Variable Analysis Approach to Large-Scale Multiobjective and Many-Objective Optimization.

    Lianbo Ma;Min Huang;Shengxiang Yang;Rui Wang

  • Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems

    Michalis Mavrovouniotis;Felipe M. Muller;Shengxiang Yang

  • An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts

    Shouyong Jiang;Shengxiang Yang

  • Genetic Algorithms With Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks

    Shengxiang Yang;Hui Cheng;Fang Wang

  • A Survey on Problem Models and Solution Approaches to Rescheduling in Railway Networks

    Wei Fang;Shengxiang Yang;Xin Yao

  • Bi-goal evolution for many-objective optimization problems

    Miqing Li;Shengxiang Yang;Xiaohui Liu

  • Benchmark Generator for CEC'2009 Competition on Dynamic Optimization

    C Li;S Yang;T T Nguyen;E L Yu

  • Evolutionary computation in dynamic and uncertain environments

    Shengxiang Yang;Yew-Soon Ong;Yaochu Jin

Frequent Co-Authors

Xin Yao
Xin Yao Lingnan University
Dingwei Wang
Dingwei Wang Northeastern University
Miqing Li
Miqing Li University of Birmingham
Yaochu Jin
Yaochu Jin Westlake University
Xiaohui Liu
Xiaohui Liu Brunel University London
Yong Wang
Yong Wang Central South University
Tianyou Chai
Tianyou Chai Northeastern University
Ferrante Neri
Ferrante Neri University of Nottingham
Natalio Krasnogor
Natalio Krasnogor Newcastle University
Marcus Kaiser
Marcus Kaiser University of Nottingham

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