World's Best Scientists 2026 revealed!
Award Badge
Electronics and Electrical Engineering
UK
2026
Award Badge
Computer Science
UK
2025

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
118
Citations
68791
World Ranking
68
National Ranking
3

Geoffrey Ye Li 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 Geoffrey Ye Li 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: 631 publications — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Geoffrey Ye Li 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 Geoffrey Ye Li 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: 118 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Electronics and Electrical Engineering in United Kingdom Leader Award
  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Electronics and Electrical Engineering in United Kingdom Leader Award

Overview

Geoffrey Ye Li is affiliated with Imperial College London in the United Kingdom. Their research primarily spans the fields of engineering and computer science, with a significant focus on electrical and electronic engineering, artificial intelligence, aerospace engineering, computer networks and communications, and computer vision and pattern recognition.

The scientist's scholarly output includes numerous papers addressing advanced topics in wireless communications and machine learning. Recent publications include:

  • Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts, 2020, Science China Information Sciences
  • Deep Learning Enabled Semantic Communication Systems, 2021, IEEE Transactions on Signal Processing
  • Model-Driven Deep Learning for MIMO Detection, 2020, IEEE Transactions on Signal Processing
  • Deep Learning-Based End-to-End Wireless Communication Systems With Conditional GANs as Unknown Channels, 2020, IEEE Transactions on Wireless Communications
  • Convolutional Neural Network-Based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis, 2020, IEEE Transactions on Wireless Communications

The main topics covered in their work include:

  • Advanced MIMO Systems Optimization
  • Wireless Signal Modulation Classification
  • Millimeter-Wave Propagation and Modeling
  • Advanced Wireless Communication Technologies
  • Antenna Design and Analysis
  • Microwave Engineering and Waveguides
  • Antenna Design and Optimization

Geoffrey Ye Li collaborates frequently with various co-authors, including Shi Jin, Zhijin Qin, Chenhao Qi, Chao-Kai Wen, and Le Liang. These professional relationships contribute to a substantial collaborative research output.

The scientist's work appears in a number of venues, with repeated publications in:

  • arXiv (Cornell University)
  • IEEE Transactions on Wireless Communications
  • IEEE Transactions on Communications
  • IEEE Wireless Communications Letters
  • IEEE Journal on Selected Areas in Communications

In addition to journal articles, Geoffrey Ye Li has contributed to academic literature through book publication. One known book is titled Wireless Communications and Machine Learning, published by Cambridge University Press in 2025.

Best Publications

  • An Overview of Massive MIMO: Benefits and Challenges

    Lu Lu;Geoffrey Ye Li;A. Lee Swindlehurst;Alexei E. Ashikhmin

  • Robust channel estimation for OFDM systems with rapid dispersive fading channels

    Ye Geoffrey Li;L.J. Cimini;N.R. Sollenberger

  • Broadband MIMO-OFDM wireless communications

    G.L. Stuber;J.R. Barry;S.W. McLaughlin;Ye Li

  • Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems

    Hao Ye;Geoffrey Ye Li;Biing-Hwang Juang

  • Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

    Xiaohu You;Cheng-Xiang Wang;Jie Huang;Xiqi Gao

  • Fundamental trade-offs on green wireless networks

    Yan Chen;Shunqing Zhang;Shugong Xu;Geoffrey Ye Li

  • OFDM and Its Wireless Applications: A Survey

    Taewon Hwang;Chenyang Yang;Gang Wu;Shaoqian Li

  • Cognitive radio networking and communications: an overview

    Ying-Chang Liang;Kwang-Cheng Chen;Geoffrey Ye Li;P. Mahonen

  • A survey of energy-efficient wireless communications

    Daquan Feng;Chenzi Jiang;Gubong Lim;L.J. Cimini

  • Deep Learning Enabled Semantic Communication Systems

    Huiqiang Xie;Zhijin Qin;Geoffrey Ye Li;Biing-Hwang Juang

  • Device-to-Device Communications Underlaying Cellular Networks

    Daquan Feng;Lu Lu;Yi Yuan-Wu;G. Y. Li

  • Energy-efficient wireless communications: tutorial, survey, and open issues

    G. Y. Li;Zhikun Xu;Cong Xiong;Chenyang Yang

  • Deep Reinforcement Learning Based Resource Allocation for V2V Communications

    Hao Ye;Geoffrey Ye Li;Biing-Hwang Fred Juang

  • Signal Processing in Cognitive Radio

    Jun Ma;G.Y. Li;Biing Hwang Juang

  • Deep Learning-Based Channel Estimation for Beamspace mmWave Massive MIMO Systems

    Hengtao He;Chao-Kai Wen;Shi Jin;Geoffrey Ye Li

  • Energy-efficient link adaptation in frequency-selective channels

    Guowang Miao;N. Himayat;G.Y. Li

  • Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities

    Mohamed A. ElMossallamy;Hongliang Zhang;Lingyang Song;Karim G. Seddik

  • Model-Driven Deep Learning for Physical Layer Communications

    Hengtao He;Shi Jin;Chao-Kai Wen;Feifei Gao

  • Deep Learning in Physical Layer Communications

    Zhijin Qin;Hao Ye;Geoffrey Ye Li;Biing-Hwang Fred Juang

  • Collaborative Cloud and Edge Computing for Latency Minimization

    Jinke Ren;Guanding Yu;Yinghui He;Geoffrey Ye Li

  • Energy- and Spectral-Efficiency Tradeoff in Downlink OFDMA Networks

    Cong Xiong;Geoffrey Ye Li;Shunqing Zhang;Yan Chen

  • MIMO-OFDM for wireless communications: signal detection with enhanced channel estimation

    Y.G. Li;J.H. Winters;N.R. Sollenberger

Frequent Co-Authors

Guanding Yu
Guanding Yu Zhejiang University
Shi Jin
Shi Jin Southeast University
Zhijin Qin
Zhijin Qin Tsinghua University
Feifei Gao
Feifei Gao Tsinghua University
Chenyang Yang
Chenyang Yang Beihang University
Shugong Xu
Shugong Xu Shanghai University
Yunlong Cai
Yunlong Cai Zhejiang University
Lingyang Song
Lingyang Song Peking University
Zhu Han
Zhu Han University of Houston
Shaoqian Li
Shaoqian Li University of Electronic Science and Technology of China

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

Pursuing a degree in Electronics and Electrical Engineering opens many avenues, but supplementing your education with additional skills can boost your career prospects. For example, a bachelor's degree in project management can help engineers develop leadership and organizational skills essential for overseeing complex engineering projects.

Many professionals opt for accelerated online degree programs for working adults, enabling them to advance their education and career without sacrificing their current job responsibilities. These programs offer flexibility and support that are crucial for busy engineers looking to upskill quickly.

Additionally, supplementing technical knowledge with programs like a master's in training and development online can prepare engineers for roles in corporate training or educational technology, expanding their career options into instructional design and workforce development.

Competency-based learning also plays a growing role in engineering education, with competency based masters degree formats emphasizing skills mastery over traditional credit hours. This approach suits self-motivated engineers ready to demonstrate expertise at their own pace.

Best Scientists Citing Geoffrey Ye Li

Trending Scientists

Recently Published Articles