World's Best Scientists 2026 revealed!
Honggang Zhang

Honggang Zhang

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
45
Citations
8857
World Ranking
3523
National Ranking
561

Honggang Zhang publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Honggang Zhang sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 263 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Honggang Zhang D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Honggang Zhang sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 45 D-Index — 50th percentile

50% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Honggang Zhang is a researcher affiliated with Zhejiang University in China. Their scholarly work spans multiple domains within engineering and computer science, focusing extensively on electrical and electronic engineering, computer networks and communications, and artificial intelligence. The scope of their research also includes civil and structural engineering and computer vision and pattern recognition, reflecting a multidisciplinary approach.

The core topics addressed in Zhang's publications cover various aspects of transportation and wireless communication technologies. These topics include:

  • Transportation Planning and Optimization
  • Traffic control and management
  • Wireless Signal Modulation Classification
  • Electrodeposition and Electroless Coatings
  • Privacy-Preserving Technologies in Data
  • IoT and Edge/Fog Computing
  • Transportation and Mobility Innovations

Zhang has contributed to several peer-reviewed papers, some of which have gained notable citations. Representative recent works include:

  • "Age of Information Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective," 2020, IEEE Transactions on Wireless Communications
  • "The LSTM-Based Advantage Actor-Critic Learning for Resource Management in Network Slicing With User Mobility," 2020, IEEE Communications Letters
  • "Semantic Communication With Adaptive Universal Transformer," 2021, IEEE Wireless Communications Letters
  • "Rethinking Modern Communication from Semantic Coding to Semantic Communication," 2022, IEEE Wireless Communications
  • "Information Freshness-Aware Task Offloading in Air-Ground Integrated Edge Computing Systems," 2021, IEEE Journal on Selected Areas in Communications

The frequent coauthors collaborating with Zhang include Rongpeng Li, Zhifeng Zhao, Zhiyuan Liu, Chenghui Peng, and Xianfu Chen. These collaborations indicate a consistent engagement with professionals specializing in related fields.

Zhang's publishing activity is notably concentrated in a few key venues, with a significant number of publications appearing in arXiv (Cornell University), SSRN Electronic Journal, and Construction and Building Materials. Other frequent publication venues include Transportation Research Part E Logistics and Transportation Review and IET conference proceedings.

Best Publications

  • Optimized Computation Offloading Performance in Virtual Edge Computing Systems Via Deep Reinforcement Learning

    Xianfu Chen;Honggang Zhang;Celimuge Wu;Shiwen Mao

  • Intelligent 5G: When Cellular Networks Meet Artificial Intelligence

    Rongpeng Li;Zhifeng Zhao;Xuan Zhou;Guoru Ding

  • CogMesh: A Cluster-Based Cognitive Radio Network

    Tao Chen;Honggang Zhang;G.M. Maggio;I. Chlamtac

  • Deep Reinforcement Learning for Resource Management in Network Slicing

    Rongpeng Li;Zhifeng Zhao;Qi Sun;Chih-Lin I

  • Network slicing as a service: enabling enterprises' own software-defined cellular networks

    Xuan Zhou;Rongpeng Li;Tao Chen;Honggang Zhang

  • Network energy saving technologies for green wireless access networks

    Tao Chen;Yang Yang;Honggang Zhang;Haesik Kim

  • Energy-Efficiency Oriented Traffic Offloading in Wireless Networks: A Brief Survey and a Learning Approach for Heterogeneous Cellular Networks

    Xianfu Chen;Jinsong Wu;Yueming Cai;Honggang Zhang

  • Spatial modeling of the traffic density in cellular networks

    Dongheon Lee;Sheng Zhou;Xiaofeng Zhong;Zhisheng Niu

  • GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

    Yuxiu Hua;Rongpeng Li;Zhifeng Zhao;Xianfu Chen

  • Green communications: Theoretical fundamentals, algorithms, and applications

    Jinsong Wu;Sundeep Rangan;Honggang Zhang

  • Age of Information Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective

    Xianfu Chen;Celimuge Wu;Tao Chen;Honggang Zhang

  • TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

    Rongpeng Li;Zhifeng Zhao;Xianfu Chen;Jacques Palicot

  • On the limits of predictability in real-world radio spectrum state dynamics: from entropy theory to 5G spectrum sharing

    Guoru Ding;Jinlong Wang;Qihui Wu;Yu-Dong Yao

  • Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning

    Xianfu Chen;Honggang Zhang;Celimuge Wu;Shiwen Mao

  • The Learning and Prediction of Application-Level Traffic Data in Cellular Networks

    Rongpeng Li;Zhifeng Zhao;Jianchao Zheng;Chengli Mei

  • The prediction analysis of cellular radio access network traffic: From entropy theory to networking practice

    Rongpeng Li;Zhifeng Zhao;Xuan Zhou;Jacques Palicot

  • Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach

    Xianfu Chen;Zhifeng Zhao;Celimuge Wu;Mehdi Bennis

  • Rethinking Modern Communication from Semantic Coding to Semantic Communication

    Kun Lu;Qingyang Zhou;Rongpeng Li;Zhifeng Zhao

  • The LSTM-Based Advantage Actor-Critic Learning for Resource Management in Network Slicing With User Mobility

    Rongpeng Li;Chujie Wang;Zhifeng Zhao;Rongbin Guo

  • Semantic Communication with Adaptive Universal Transformer

    Qingyang Zhou;Rongpeng Li;Zhifeng Zhao;Chenghui Peng

  • Multiple signal waveforms adaptation in cognitive ultra-wideband radio evolution

    Honggang Zhang;Xiaofei Zhou;K.Y. Yazdandoost;I. Chlamtac

  • GAN-Based Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

    Yuxiu Hua;Rongpeng Li;Zhifeng Zhao;Honggang Zhang

  • Deep Reinforcement Learning for Resource Management in Network Slicing

    Rongpeng Li;Zhifeng Zhao;Qi Sun;Chi-Lin I

Frequent Co-Authors

Zhifeng Zhao
Zhifeng Zhao Zhejiang Lab
Tao Chen
Tao Chen VTT Technical Research Centre of Finland
Mehdi Bennis
Mehdi Bennis University of Oulu
Yusheng Ji
Yusheng Ji National Institute of Informatics
Sundeep Rangan
Sundeep Rangan New York University
David Grace
David Grace University of York
Shiwen Mao
Shiwen Mao Auburn University
Jon Crowcroft
Jon Crowcroft University of Cambridge
A. P. Vinod
A. P. Vinod Singapore Institute of Technology
Mario Pickavet
Mario Pickavet Ghent University

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