World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
50
Citations
8655
World Ranking
2841
National Ranking
472

Jun Fang 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 Jun Fang 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: 317 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Jun Fang 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 Jun Fang 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: 50 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Overview

Jun Fang is affiliated with the University of Electronic Science and Technology of China. Their research primarily spans the fields of Engineering and Computer Science, with a strong focus on Electrical and Electronic Engineering, Aerospace Engineering, Artificial Intelligence, Computer Networks and Communications, and Computational Mechanics.

The scientist has contributed extensively to topics related to advanced wireless communication and antenna technologies. Key areas of their work include:

  • Advanced Wireless Communication Technologies
  • Antenna Design and Analysis
  • Advanced MIMO Systems Optimization
  • Indoor and Outdoor Localization Technologies
  • Millimeter-Wave Propagation and Modeling
  • Sparse and Compressive Sensing Techniques
  • Antenna Design and Optimization

Jun Fang's publication record includes papers in several notable scientific venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Wireless Communications Letters
  • IEEE Transactions on Wireless Communications
  • IEEE Transactions on Vehicular Technology

Representative recent papers authored or co-authored by Jun Fang are:

  • "Terahertz Multi-User Massive MIMO With Intelligent Reflecting Surface: Beam Training and Hybrid Beamforming," 2021, IEEE Transactions on Vehicular Technology
  • "Joint Transceiver and Large Intelligent Surface Design for Massive MIMO mmWave Systems," 2020, IEEE Transactions on Wireless Communications
  • "Deep Learning-Based Spectrum Sensing in Cognitive Radio: A CNN-LSTM Approach," 2020, IEEE Communications Letters
  • "Joint Waveform and Beamforming Design for RIS-Aided ISAC Systems," 2023, IEEE Signal Processing Letters
  • "Unsupervised Deep Spectrum Sensing: A Variational Auto-Encoder Based Approach," 2020, IEEE Transactions on Vehicular Technology

The scientist's frequent collaborators include:

  • Hongbin Li
  • Peilan Wang
  • Bin Wang
  • Zhi Chen
  • Boyu Ning

Best Publications

  • Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design

    Peilan Wang;Jun Fang;Xiaojun Yuan;Zhi Chen

  • Compressed Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave Systems

    Peilan Wang;Jun Fang;Huiping Duan;Hongbin Li

  • Multiantenna-Assisted Spectrum Sensing for Cognitive Radio

    Pu Wang;Jun Fang;Ning Han;Hongbin Li

  • Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design

    Peilan Wang;Jun Fang;Xiaojun Yuan;Zhi Chen

  • Low-Rank Tensor Decomposition-Aided Channel Estimation for Millimeter Wave MIMO-OFDM Systems

    Zhou Zhou;Jun Fang;Linxiao Yang;Hongbin Li

  • Pattern-Coupled Sparse Bayesian Learning for Recovery of Block-Sparse Signals

    Jun Fang;Yanning Shen;Hongbin Li;Pu Wang

  • Terahertz Multi-User Massive MIMO With Intelligent Reflecting Surface: Beam Training and Hybrid Beamforming

    Boyu Ning;Zhi Chen;Wenrong Chen;Yiming Du

  • Improving Physical Layer Security Using UAV-Enabled Mobile Relaying

    Qian Wang;Zhi Chen;Weidong Mei;Jun Fang

  • Intelligent Power Control for Spectrum Sharing in Cognitive Radios: A Deep Reinforcement Learning Approach

    Xingjian Li;Jun Fang;Wen Cheng;Huiping Duan

  • Super-Resolution Compressed Sensing for Line Spectral Estimation: An Iterative Reweighted Approach

    Jun Fang;Feiyu Wang;Yanning Shen;Hongbin Li

  • Millimeter Wave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures

    Xingjian Li;Jun Fang;Hongbin Li;Pu Wang

  • Channel Estimation for TDD/FDD Massive MIMO Systems With Channel Covariance Computing

    Hongxiang Xie;Feifei Gao;Shi Jin;Jun Fang

  • Joint Transceiver and Large Intelligent Surface Design for Massive MIMO MmWave Systems

    Peilan Wang;Jun Fang;Linglong Dai;Hongbin Li

  • Deep Learning-Based Spectrum Sensing in Cognitive Radio: A CNN-LSTM Approach

    Jiandong Xie;Jun Fang;Chang Liu;Xuanheng Li

  • Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding

    Linxiao Yang;Ngai-Man Cheung;Jiaying Li;Jun Fang

  • Joint Waveform and Beamforming Design for RIS-Aided ISAC Systems

    Unknown

  • Super-Resolution Channel Estimation for MmWave Massive MIMO With Hybrid Precoding

    Chen Hu;Linglong Dai;Talha Mir;Zhen Gao

  • Beamforming Optimization for Intelligent Reflecting Surface Assisted MIMO: A Sum-Path-Gain Maximization Approach

    Boyu Ning;Zhi Chen;Wenjie Chen;Jun Fang

  • Channel Estimation for Millimeter-Wave Multiuser MIMO Systems via PARAFAC Decomposition

    Zhou Zhou;Jun Fang;Linxiao Yang;Hongbin Li

  • Spherical Wave Channel and Analysis for Large Linear Array in LoS Conditions

    Zhou Zhou;Xiang Gao;Jun Fang;Zhi Chen

  • Global and local structure preserving sparse subspace learning

    Nan Zhou;Yangyang Xu;Hong Cheng;Jun Fang

  • Low-Rank Covariance-Assisted Downlink Training and Channel Estimation for FDD Massive MIMO Systems

    Jun Fang;Xingjian Li;Hongbin Li;Feifei Gao

  • Data-Driven-Based Analog Beam Selection for Hybrid Beamforming Under mm-Wave Channels

    Yin Long;Zhi Chen;Jun Fang;Chintha Tellambura

  • Distributed Adaptive Quantization for Wireless Sensor Networks: From Delta Modulation to Maximum Likelihood

    Jun Fang;Hongbin Li

  • Applications of the SRV constraint in broadband pattern synthesis

    Huiping Duan;Boon Poh Ng;Chong Meng Samson See;Jun Fang

  • Joint Channel Estimation and Multiuser Detection for Uplink Grant-Free NOMA

    Yang Du;Binhong Dong;Wuyong Zhu;Pengyu Gao

  • Block-Sparsity-Based Multiuser Detection for Uplink Grant-Free NOMA

    Yang Du;Cong Cheng;Binhong Dong;Zhi Chen

Frequent Co-Authors

Hongbin Li
Hongbin Li Stevens Institute of Technology
Zhi Chen
Zhi Chen University of Kentucky
Shaoqian Li
Shaoqian Li University of Electronic Science and Technology of China
Ying-Chang Liang
Ying-Chang Liang University of Electronic Science and Technology of China
Lei Huang
Lei Huang Shenzhen University
Bing Zeng
Bing Zeng University of Electronic Science and Technology of China
Feifei Gao
Feifei Gao Tsinghua University
Rick S. Blum
Rick S. Blum Lehigh University
Xiaojun Yuan
Xiaojun Yuan University of Electronic Science and Technology of China
Athina P. Petropulu
Athina P. Petropulu Rutgers, The State University of New Jersey

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