World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
8734
World Ranking
6507
National Ranking
870

Fangchun 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 Fangchun 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: 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: 347 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Fangchun 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 Fangchun Yang 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Fangchun Yang is affiliated with Beijing University of Posts and Telecommunications in China. Their research primarily focuses on the fields of computer science and engineering, with a significant emphasis on computer networks and communications, information systems, electrical and electronic engineering, artificial intelligence, and transportation.

The scientist's publications cover several key areas, prominently including IoT and edge/fog computing, blockchain technology applications and security, age of information optimization, vehicular ad hoc networks (VANETs), recommender systems and techniques, as well as traffic prediction and management techniques.

Frequent publication venues for Fangchun Yang include:

  • IEEE Internet of Things Journal
  • China Communications
  • IEEE Transactions on Mobile Computing
  • arXiv (Cornell University)
  • Sensors

Yang's recent papers illustrate the focus on edge computing and related technologies. Notable recent works include:

  • Dependency-Aware Task Scheduling in Vehicular Edge Computing, 2020, IEEE Internet of Things Journal
  • QoS Driven Task Offloading with Statistical Guarantee in Mobile Edge Computing, 2020, IEEE Transactions on Mobile Computing
  • Service Coverage for Satellite Edge Computing, 2021, IEEE Internet of Things Journal
  • Edgence: A blockchain-enabled edge-computing platform for intelligent IoT-based dApps, 2020, China Communications
  • Cross-Domain Resource Orchestration for the Edge-Computing-Enabled Smart Road, 2020, IEEE Network

The scientist frequently collaborates with colleagues including Jinglin Li, Shangguang Wang, Guiyang Luo, Ao Zhou, and Xiao Ma. These coauthors have multiple joint publications indicating ongoing research partnerships.

Yang's body of work is situated within major topics such as:

  • IoT and Edge/Fog Computing
  • Blockchain Technology Applications and Security
  • Age of Information Optimization
  • Vehicular Ad Hoc Networks (VANETs)
  • Recommender Systems and Techniques
  • Traffic Prediction and Management Techniques
  • Traffic Control and Management

The combination of publication venues, coauthor networks, and diverse yet interconnected topics outlines a research trajectory anchored in advancing computing technologies at the network edge, with applications that extend into intelligent transportation systems and blockchain-enabled solutions.

Best Publications

  • An overview of Internet of Vehicles

    Fangchun Yang;Shangguang Wang;Jinglin Li;Zhihan Liu

  • Virtual network embedding through topology-aware node ranking

    Xiang Cheng;Sen Su;Zhongbao Zhang;Hanchi Wang

  • Toward Efficient Content Delivery for Automated Driving Services: An Edge Computing Solution

    Quan Yuan;Haibo Zhou;Jinglin Li;Zhihan Liu

  • Dependency-Aware Task Scheduling in Vehicular Edge Computing

    Yujiong Liu;Shangguang Wang;Qinglin Zhao;Shiyu Du

  • Cloud Service Reliability Enhancement via Virtual Machine Placement Optimization

    Ao Zhou;Shangguang Wang;Bo Cheng;Zibin Zheng

  • Artificial Intelligence Powered Mobile Networks: From Cognition to Decision

    Unknown

  • Towards an accurate evaluation of quality of cloud service in service-oriented cloud computing

    Shangguang Wang;Zhipiao Liu;Qibo Sun;Hua Zou

  • Virtual network embedding through topology awareness and optimization

    Xiang Cheng;Sen Su;Zhongbao Zhang;Kai Shuang

  • Cooperative vehicular content distribution in edge computing assisted 5G-VANET

    Guiyang Luo;Quan Yuan;Haibo Zhou;Nan Cheng

  • Architecture and key technologies for Internet of Vehicles:a survey

    Fangchun Yang;Jinglin Li;Tao Lei;Shangguang Wang

  • Cloud model for service selection

    Shangguang Wang;Zibin Zheng;Qibo Sun;Hua Zou

  • Reputation Measurement and Malicious Feedback Rating Prevention in Web Service Recommendation Systems

    Shangguang Wang;Zibin Zheng;Zhengping Wu;Michael R. Lyu

  • A Vertical Handoff Method via Self-Selection Decision Tree for Internet of Vehicles

    Shangguang Wang;Cunqun Fan;Ching-Hsien Hsu;Qibo Sun

  • Particle Swarm Optimization for Energy-Aware Virtual Machine Placement Optimization in Virtualized Data Centers

    Shangguang Wang;Zhipiao Liu;Zibin Zheng;Qibo Sun

  • Software-Defined Cooperative Data Sharing in Edge Computing Assisted 5G-VANET

    Guiyang Luo;Haibo Zhou;Nan Cheng;Quan Yuan

  • A Blockchain-Enabled Trustless Crowd-Intelligence Ecosystem on Mobile Edge Computing

    Jinliang Xu;Shangguang Wang;Bharat K. Bhargava;Fangchun Yang

  • Multi-Dimensional QoS Prediction for Service Recommendations

    Shangguang Wang;You Ma;Bo Cheng;Fangchun Yang

  • Using Proactive Fault-Tolerance Approach to Enhance Cloud Service Reliability

    Jialei Liu;Shangguang Wang;Ao Zhou;Sathish A. P. Kumar

  • Provision of Data-Intensive Services Through Energy- and QoS-Aware Virtual Machine Placement in National Cloud Data Centers

    Shangguang Wang;Ao Zhou;Ching-Hsien Hsu;Xuanyu Xiao

  • Particle Swarm Optimization with Skyline Operator for Fast Cloud-based Web Service Composition

    Shangguang Wang;Qibo Sun;Hua Zou;Fangchun Yang

  • A Highly Accurate Prediction Algorithm for Unknown Web Service QoS Values

    You Ma;Shangguang Wang;Patrick C.K. Hung;Ching-Hsien Hsu

Frequent Co-Authors

Shangguang Wang
Shangguang Wang Beijing University of Posts and Telecommunications
Ching-Hsien Hsu
Ching-Hsien Hsu Asia University Taiwan
Zibin Zheng
Zibin Zheng Sun Yat-sen University
Haibo Zhou
Haibo Zhou Nanjing University
Michael R. Lyu
Michael R. Lyu Chinese University of Hong Kong
Xuemin Shen
Xuemin Shen University of Waterloo
Rajkumar Buyya
Rajkumar Buyya University of Melbourne
Bo Cheng
Bo Cheng Beijing University of Posts and Telecommunications
Ning Zhang
Ning Zhang University of Windsor
Nan Cheng
Nan Cheng Xidian University

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