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2025

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Rising Stars

D-Index
52
Citations
12952
World Ranking
265
National Ranking
87

Computer Science

D-Index
57
Citations
16365
World Ranking
3776
National Ranking
502

Jiawen Kang 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 Jiawen Kang 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: 183 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Jiawen Kang 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 Jiawen Kang 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: 57 D-Index — 74th percentile

74% 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

  • 2025 - Research.com Rising Stars Award

Overview

Jiawen Kang is affiliated with Guangdong University of Technology in China. Their research focuses primarily on computer science and engineering, with significant contributions in artificial intelligence, computer networks and communications, electrical and electronic engineering, information systems, and computer vision and pattern recognition.

The scientist has published extensively on a range of topics, including:

  • Privacy-Preserving Technologies in Data
  • IoT and Edge/Fog Computing
  • Blockchain Technology Applications and Security
  • UAV Applications and Optimization
  • Advanced Wireless Communication Technologies
  • Transportation and Mobility Innovations
  • Speech Recognition and Synthesis

Jiawen Kang has contributed to multiple recent papers, notable among them are:

  • "Reliable Federated Learning for Mobile Networks," 2020, published in IEEE Wireless Communications
  • "Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach," 2020, IEEE Internet of Things Journal
  • "Fusing Blockchain and AI With Metaverse: A Survey," 2022, IEEE Open Journal of the Computer Society
  • "A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges," 2022, IEEE Communications Surveys & Tutorials
  • "Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach," 2021, IEEE Transactions on Intelligent Transportation Systems

The frequent co-authors in Jiawen Kang's research include Dusit Niyato, Zehui Xiong, Hongyang Du, Dong In Kim, and Minrui Xu.

The scientist's work is published largely in the following venues:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • IEEE Transactions on Vehicular Technology
  • IEEE Wireless Communications
  • IEEE Network

Best Publications

  • Enabling Localized Peer-to-Peer Electricity Trading Among Plug-in Hybrid Electric Vehicles Using Consortium Blockchains

    Jiawen Kang;Rong Yu;Xumin Huang;Sabita Maharjan

  • Consortium Blockchain for Secure Energy Trading in Industrial Internet of Things

    Zhetao Li;Jiawen Kang;Rong Yu;Dongdong Ye

  • Deep Anomaly Detection for Time-Series Data in Industrial IoT: A Communication-Efficient On-Device Federated Learning Approach

    Yi Liu;Sahil Garg;Jiangtian Nie;Yang Zhang

  • Incentive Mechanism for Reliable Federated Learning: A Joint Optimization Approach to Combining Reputation and Contract Theory

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Shengli Xie

  • Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

    Jiawen Kang;Rong Yu;Xumin Huang;Maoqiang Wu

  • Fusing Blockchain and AI With Metaverse: A Survey

    Unknown

  • Federated learning for 6G communications: Challenges, methods, and future directions

    Yi Liu;Xingliang Yuan;Zehui Xiong;Jiawen Kang

  • A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges

    Unknown

  • Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach

    Yi Liu;James J. Q. Yu;Jiawen Kang;Dusit Niyato

  • Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Dongdong Ye

  • Reliable Federated Learning for Mobile Networks

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Yuze Zou

  • Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach

    Wei Yang Bryan Lim;Jianqiang Huang;Zehui Xiong;Jiawen Kang

  • A Secure Federated Learning Framework for 5G Networks

    Yi Liu;Jialiang Peng;Jiawen Kang;Abdullah M. Iliyasu

  • Privacy-Preserved Pseudonym Scheme for Fog Computing Supported Internet of Vehicles

    Jiawen Kang;Rong Yu;Xumin Huang;Yan Zhang

  • Distributed Reputation Management for Secure and Efficient Vehicular Edge Computing and Networks

    Xumin Huang;Rong Yu;Jiawen Kang;Yan Zhang

  • Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Han Yu

  • Exploring Mobile Edge Computing for 5G-Enabled Software Defined Vehicular Networks

    Xumin Huang;Rong Yu;Jiawen Kang;Yejun He

  • MixGroup: Accumulative Pseudonym Exchanging for Location Privacy Enhancement in Vehicular Social Networks

    Rong Yu;Jiawen Kang;Xumin Huang;Shengli Xie

  • Machine Learning-Powered Encrypted Network Traffic Analysis: A Comprehensive Survey

    Unknown

  • Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT

    Unknown

  • Cooperative Resource Management in Cloud-Enabled Vehicular Networks

    Rong Yu;Xumin Huang;Jiawen Kang;Jiefei Ding

  • Cloud/Edge Computing Service Management in Blockchain Networks: Multi-Leader Multi-Follower Game-Based ADMM for Pricing

    Zehui Xiong;Jiawen Kang;Dusit Niyato;Ping Wang

  • Incentivizing Consensus Propagation in Proof-of-Stake Based Consortium Blockchain Networks

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Ping Wang

  • Towards Secure Blockchain-enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Dongdong Ye

Frequent Co-Authors

Dusit Niyato
Dusit Niyato Nanyang Technological University
Zehui Xiong
Zehui Xiong Queen's University Belfast
Rong Yu
Rong Yu Guangdong University of Technology
Chunyan Miao
Chunyan Miao Nanyang Technological University
Dong In Kim
Dong In Kim Sungkyunkwan University
Cyril Leung
Cyril Leung University of British Columbia
Stein Gjessing
Stein Gjessing University of Oslo
Shengli Xie
Shengli Xie Guangdong University of Technology
Sabita Maharjan
Sabita Maharjan University of Oslo
Ping Wang
Ping Wang York University

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