World's Best Scientists 2026 revealed!
Award Badge
Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
96
Citations
26529
World Ranking
449
National Ranking
59

Ling Wang 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 Ling Wang 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: 352 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Ling Wang 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 Ling Wang 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: 96 D-Index — 97th percentile

97% 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

Overview

Ling Wang is affiliated with Tsinghua University in China and has contributed extensively to research in engineering and computer science. Their work primarily intersects industrial and manufacturing engineering, artificial intelligence, computational theory and mathematics, electrical and electronic engineering, and aerospace engineering.

The scientist's research topics focus on scheduling and optimization algorithms, advanced manufacturing and logistics optimization, metaheuristic optimization algorithms, advanced multi-objective optimization, assembly line balancing optimization, vehicle routing optimization methods, and transportation and mobility innovations.

Ling Wang has published numerous papers in various reputable venues, including:

  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Systems Man and Cybernetics Systems
  • IEEE Transactions on Intelligent Transportation Systems
  • Swarm and Evolutionary Computation
  • IEEE Transactions on Emerging Topics in Computational Intelligence

Recent significant publications include:

  • "A Cooperative Memetic Algorithm With Learning-Based Agent for Energy-Aware Distributed Hybrid Flow-Shop Scheduling," 2021, IEEE Transactions on Evolutionary Computation
  • "Assessing the effects of China's Three-North Shelter Forest Program over 40 years," 2022, The Science of The Total Environment
  • "A Knowledge-Based Two-Population Optimization Algorithm for Distributed Energy-Efficient Parallel Machines Scheduling," 2020, IEEE Transactions on Cybernetics
  • "A Bi-Population Cooperative Memetic Algorithm for Distributed Hybrid Flow-Shop Scheduling," 2020, IEEE Transactions on Emerging Topics in Computational Intelligence
  • "A Generic Markov Decision Process Model and Reinforcement Learning Method for Scheduling Agile Earth Observation Satellites," 2020, IEEE Transactions on Systems Man and Cybernetics Systems

Frequent collaborators include Guohua Wu, Jingjing Wang, Jing-fang Chen, Rui Wang, and Zixiao Pan.

Best Publications

  • Improved particle swarm optimization combined with chaos

    Bo Liu;Ling Wang;Yi-Hui Jin;Fang Tang

  • An effective co-evolutionary particle swarm optimization for constrained engineering design problems

    Qie He;Ling Wang

  • An effective co-evolutionary differential evolution for constrained optimization

    Fu zhuo Huang;Ling Wang;Qie He

  • An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling

    Bo Liu;Ling Wang;Yi-Hui Jin

  • A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization

    Qie He;Ling Wang

  • An effective hybrid optimization strategy for job-shop scheduling problems

    Ling Wang;Da-Zhong Zheng

  • A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems

    Ling Wang;Quan-Ke Pan;P. N. Suganthan;Wen-Hong Wang

  • An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers

    Bo Liu;Ling Wang;Yi-Hui Jin

  • A Hybrid Quantum-Inspired Genetic Algorithm for Multiobjective Flow Shop Scheduling

    Bin-Bin Li;Ling Wang

  • Parameter extraction of photovoltaic models using an improved teaching-learning-based optimization

    Shuijia Li;Wenyin Gong;Xuesong Yan;Chengyu Hu

  • A Knowledge-Based Cooperative Algorithm for Energy-Efficient Scheduling of Distributed Flow-Shop

    Jing-Jing Wang;Ling Wang

  • An Effective Hybrid Heuristic for Flow Shop Scheduling

    D.-Z. Zheng;L. Wang

  • An effective artificial bee colony algorithm for the flexible job-shop scheduling problem

    Ling Wang;Gang Zhou;Ye Xu;Shengyao Wang

  • Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem

    Quan-Ke Pan;Quan-Ke Pan;Liang Gao;Ling Wang;Jing Liang

  • A novel binary fruit fly optimization algorithm for solving the multidimensional knapsack problem

    Ling Wang;Xiao-long Zheng;Sheng-yao Wang

  • An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem

    Sheng-yao Wang;Ling Wang;Min Liu;Ye Xu

  • A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem

    Jin Deng;Ling Wang

  • Parameter estimation for chaotic systems by particle swarm optimization

    Qie He;Ling Wang;Bo Liu

  • A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation

    Quan-Ke Pan;Quan-Ke Pan;Ling Wang;Jun-Qing Li;Jun-Qing Li;Jun-Hua Duan;Jun-Hua Duan

  • A review of energy-efficient scheduling in intelligent production systems

    Kaizhou Gao;Kaizhou Gao;Yun Huang;Ali Sadollah;Ling Wang

  • A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems

    Quan-Ke Pan;Ling Wang;Bin Qian

  • An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flowshop Problem in Steelmaking Process

    Quan-Ke Pan;Ling Wang;Kun Mao;Jin-Hui Zhao

Frequent Co-Authors

Quan-Ke Pan
Quan-Ke Pan Shanghai University
Liang Gao
Liang Gao Huazhong University of Science and Technology
Wenyin Gong
Wenyin Gong China University of Geosciences
Junqing Li
Junqing Li Liaocheng University
Kaizhou Gao
Kaizhou Gao Macau University of Science and Technology
Xinyu Li
Xinyu Li Huazhong University of Science and Technology
Witold Pedrycz
Witold Pedrycz University of Alberta
Hisao Ishibuchi
Hisao Ishibuchi Southern University of Science and Technology
Yun Li
Yun Li University of Electronic Science and Technology of China

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens doors to a variety of related online degrees and dynamic career options. Many students choose to diversify their technical backgrounds by pursuing specialized programs alongside or after their computer science studies.

For those interested in designing and building machinery, an online mechanical engineering degree can be a cost-effective and flexible route. If you have a passion for the fundamental principles behind technology, you might consider the cheapest online physics degree options, which provide strong analytical and problem-solving skills.

Students eager to enter the rapidly growing field of data analytics can look to an affordable data science degree, combining statistics, programming, and big data. Meanwhile, an electrical engineering degree online admissions path provides another high-demand career option with courses in circuits, systems, and digital design.

By considering these related online degrees, computer science students can further expand their skill sets and prepare for a broad range of impactful STEM careers.

Best Scientists Citing Ling Wang

Trending Scientists

Recently Published Articles