World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
11397
World Ranking
3480
National Ranking
1678

Kun 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 Kun 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: 443 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.

Kun 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 Kun 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: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Overview

Kun Wang is affiliated with the University of California, Los Angeles in the United States. Their research spans multiple fields including Health Professions, Physics and Astronomy, and Arts and Humanities, with particular focus on several interdisciplinary topics.

Wang's scholarly contributions include work in the following main fields of study:

  • Health Professions (4 publications)
  • Physics and Astronomy (3 publications)
  • Arts and Humanities (2 publications)

The subfields of study covered by Wang involve:

  • General Health Professions (4 publications)
  • Astronomy and Astrophysics (2 publications)
  • Philosophy (2 publications)
  • Instrumentation (1 publication)

Their research addresses key topics such as:

  • Hermeneutics and Narrative Identity (4 publications)
  • Aging, Elder Care, and Social Issues (4 publications)
  • Health, Medicine and Society (4 publications)
  • Stellar, planetary, and galactic studies (2 publications)
  • Astronomy and Astrophysical Research (2 publications)
  • Gamma-ray bursts and supernovae (2 publications)

Kun Wang has published research in these venues:

  • The Astrophysical Journal Supplement Series (1 publication)
  • International Journal of Computer Vision (1 publication)

Recent papers include:

  • Unveiling Hidden Stellar Aggregates in the Milky Way: 1656 New Star Clusters Found in Gaia EDR3, 2022, The Astrophysical Journal Supplement Series
  • Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy, 2025, International Journal of Computer Vision

Frequent collaborators in Wang's work are:

  • Zhihong He
  • Xiaochen Liu
  • Yangping Luo
  • Qing-Quan Jiang
  • Zhiqiang Yan

Best Publications

  • Green Industrial Internet of Things Architecture: An Energy-Efficient Perspective

    Kun Wang;Yihui Wang;Yanfei Sun;Song Guo

  • A Survey on Energy Internet: Architecture, Approach, and Emerging Technologies

    Kun Wang;Jun Yu;Yan Yu;Yirou Qian

  • A Comprehensive Survey of Blockchain: From Theory to IoT Applications and Beyond

    Mingli Wu;Kun Wang;Xiaoqin Cai;Song Guo

  • $\mathsf{LightChain}$ : A Lightweight Blockchain System for Industrial Internet of Things

    Yinqiu Liu;Kun Wang;Yun Lin;Wenyao Xu

  • Making Big Data Open in Edges: A Resource-Efficient Blockchain-Based Approach

    Chenhan Xu;Kun Wang;Peng Li;Song Guo

  • Energy big data: A survey

    Hui Jiang;Kun Wang;Yihui Wang;Min Gao

  • Enabling FPGAs in the cloud

    Fei Chen;Yi Shan;Yu Zhang;Yu Wang

  • Robust Big Data Analytics for Electricity Price Forecasting in the Smart Grid

    Kun Wang;Chenhan Xu;Yan Zhang;Song Guo

  • Strategic Honeypot Game Model for Distributed Denial of Service Attacks in the Smart Grid

    Kun Wang;Miao Du;Sabita Maharjan;Yanfei Sun

  • Traffic and Computation Co-Offloading With Reinforcement Learning in Fog Computing for Industrial Applications

    Yixuan Wang;Kun Wang;Huawei Huang;Toshiaki Miyazaki

  • Green Resource Allocation Based on Deep Reinforcement Learning in Content-Centric IoT

    Xiaoming He;Kun Wang;Huawei Huang;Toshiaki Miyazaki

  • Intelligent Resource Management in Blockchain-Based Cloud Datacenters

    Chenhan Xu;Kun Wang;Mingyi Guo

  • Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud

    Tian Wang;Haoxiong Ke;Xi Zheng;Kun Wang

  • An Energy-Efficient Reliable Data Transmission Scheme for Complex Environmental Monitoring in Underwater Acoustic Sensor Networks

    Kun Wang;Hui Gao;Xiaoling Xu;Jinfang Jiang

  • Big Data Privacy Preserving in Multi-Access Edge Computing for Heterogeneous Internet of Things

    Miao Du;Kun Wang;Yuanfang Chen;Xiaoyan Wang

  • Wireless Big Data Computing in Smart Grid

    Kun Wang;Yunqi Wang;Xiaoxuan Hu;Yanfei Sun

  • A Game Theory-Based Energy Management System Using Price Elasticity for Smart Grids

    Kun Wang;Zhiyou Ouyang;Rahul Krishnan;Lei Shu

  • Mobile big data fault-tolerant processing for ehealth networks

    Kun Wang;Yun Shao;Lei Shu;Chunsheng Zhu

  • Edge QoE: Computation Offloading With Deep Reinforcement Learning for Internet of Things

    Haodong Lu;Xiaoming He;Miao Du;Xiukai Ruan

  • Big Data Analytics for System Stability Evaluation Strategy in the Energy Internet

    Kun Wang;Huining Li;Yixiong Feng;Guangdong Tian

  • A Survey on Energy Internet Communications for Sustainability

    Kun Wang;Xiaoxuan Hu;Huining Li;Peng Li

  • Social-aware energy harvesting device-to-device communications in 5G networks

    Li Jiang;Hui Tian;Zi Xing;Kun Wang

Frequent Co-Authors

Song Guo
Song Guo Hong Kong University of Science and Technology
Lei Shu
Lei Shu Nanjing Agricultural University
Lei He
Lei He University of California, Los Angeles
Xianling Liang
Xianling Liang Shanghai Jiao Tong University
Chunsheng Zhu
Chunsheng Zhu Southern University of Science and Technology
Ronghong Jin
Ronghong Jin Shanghai Jiao Tong University
Junping Geng
Junping Geng Shanghai Jiao Tong University
Minyi Guo
Minyi Guo Shanghai Jiao Tong University
Huawei Huang
Huawei Huang Sun Yat-sen University
Weiren Zhu
Weiren Zhu Shanghai Jiao Tong University

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

Choosing the right educational path in Computer Science can open diverse career opportunities. In addition to traditional bachelor's programs, many students consider earning an associate's degree online for a faster, more affordable entry into the tech industry. These programs are ideal for those seeking foundational knowledge or a stepping stone to higher degrees.

For professionals looking to accelerate their careers, exploring the shortest masters degree options can be a smart move. Such programs allow students to deepen their expertise and boost employability in less time than traditional routes.

It's also important to consider which fields offer strong job prospects. Reviewing the most useful graduate degrees in demand helps align your educational investment with current market needs.

Beyond degrees, earning additional certifications that pay well in specialized areas of technology can further boost your credentials and salary potential. Combining degrees and certifications provides a flexible, efficient path to a rewarding career in Computer Science.

Best Scientists Citing Kun Wang

Trending Scientists

Recently Published Articles