World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
51
Citations
10508
World Ranking
2663
National Ranking
441

Computer Science

D-Index
51
Citations
10532
World Ranking
5336
National Ranking
715

Guanding Yu 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 Guanding Yu 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: 272 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Guanding Yu 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 Guanding Yu 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

Guanding Yu is affiliated with Zhejiang University in China and focuses research efforts on computer science and engineering fields, particularly within electrical and electronic engineering and computer networks and communications.

Their research spans multiple subfields including artificial intelligence, computer vision and pattern recognition, and aerospace engineering. The scientist's work covers key topics such as:

  • Advanced MIMO Systems Optimization
  • Wireless Signal Modulation Classification
  • Privacy-Preserving Technologies in Data
  • Cooperative Communication and Network Coding
  • Wireless Communication Security Techniques
  • Advanced Wireless Communication Technologies
  • Millimeter-Wave Propagation and Modeling

Guanding Yu has produced numerous publications, frequently contributing to the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Wireless Communications
  • IEEE Transactions on Communications
  • IEEE Journal on Selected Areas in Communications
  • IEEE Internet of Things Journal

Among recent papers are:

  • Scheduling for Cellular Federated Edge Learning With Importance and Channel Awareness, 2020, IEEE Transactions on Wireless Communications
  • Accelerating DNN Training in Wireless Federated Edge Learning Systems, 2020, IEEE Journal on Selected Areas in Communications
  • Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding Design for Multiuser MIMO Systems, 2020, IEEE Transactions on Wireless Communications
  • AUV-Aided Energy-Efficient Data Collection in Underwater Acoustic Sensor Networks, 2020, IEEE Internet of Things Journal
  • RIS-Assisted Communication Radar Coexistence: Joint Beamforming Design and Analysis, 2022, IEEE Journal on Selected Areas in Communications

Collaborations have been notable with several frequent coauthors, including:

  • Yunlong Cai
  • Qiyu Hu
  • Guangyi Zhang
  • Yinghui He

Overall, their work demonstrates a sustained engagement with wireless communications, federated edge learning, and multiuser MIMO systems, contributing across a broad spectrum of interconnected topics within computer science and engineering.

Best Publications

  • Collaborative Cloud and Edge Computing for Latency Minimization

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

  • Joint Offloading and Trajectory Design for UAV-Enabled Mobile Edge Computing Systems

    Qiyu Hu;Yunlong Cai;Guanding Yu;Zhijin Qin

  • Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading

    Jinke Ren;Guanding Yu;Yunlong Cai;Yinghui He

  • Joint Mode Selection and Resource Allocation for Device-to-Device Communications

    Guanding Yu;Lukai Xu;Daquan Feng;Rui Yin

  • On cognitive radio networks with opportunistic power control strategies in fading channels

    Yan Chen;Guanding Yu;Zhaoyang Zhang;Hsiao-hwa Chen

  • Deep-Learning-Based Wireless Resource Allocation With Application to Vehicular Networks

    Le Liang;Hao Ye;Guanding Yu;Geoffrey Ye Li

  • RIS-Assisted Communication Radar Coexistence: Joint Beamforming Design and Analysis

    Unknown

  • Joint Spectrum and Power Allocation for D2D Communications Underlaying Cellular Networks

    Rui Yin;Caijun Zhong;Guanding Yu;Zhaoyang Zhang

  • Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding Design for Multiuser MIMO Systems

    Qiyu Hu;Yunlong Cai;Qingjiang Shi;Kaidi Xu

  • Scheduling for Cellular Federated Edge Learning With Importance and Channel Awareness

    Jinke Ren;Yinghui He;Dingzhu Wen;Guanding Yu

  • Accelerating DNN Training in Wireless Federated Edge Learning Systems

    Jinke Ren;Guanding Yu;Guangyao Ding

  • D2D Communications Meet Mobile Edge Computing for Enhanced Computation Capacity in Cellular Networks

    Yinghui He;Jinke Ren;Guanding Yu;Yunlong Cai

  • An Edge-Computing Based Architecture for Mobile Augmented Reality

    Jinke Ren;Yinghui He;Guan Huang;Guanding Yu

  • Pricing-Based Interference Coordination for D2D Communications in Cellular Networks

    Rui Yin;Guanding Yu;Huazi Zhang;Zhaoyang Zhang

  • AUV-Aided Energy-Efficient Data Collection in Underwater Acoustic Sensor Networks

    Xiaoxiao Zhuo;Meiyan Liu;Yan Wei;Guanding Yu

  • LBT-Based Adaptive Channel Access for LTE-U Systems

    Rui Yin;Guanding Yu;Amine Maaref;Geoffrey Ye Li

  • Cellular Meets WiFi: Traffic Offloading or Resource Sharing?

    Qimei Chen;Guanding Yu;Hangguan Shan;Amine Maaref

  • Mode Switching for Energy-Efficient Device-to-Device Communications in Cellular Networks

    Daquan Feng;Guanding Yu;Cong Xiong;Yi Yuan-Wu

  • Graph Embedding-Based Wireless Link Scheduling With Few Training Samples

    Mengyuan Lee;Guanding Yu;Geoffrey Ye Li

  • Cross-Layer Performance Analysis of Two-Hop Wireless Links with Adaptive Modulation

    Peng Cheng;Guanding Yu;Zhaoyang Zhang;Huiling Jia

  • Multi-Objective Energy-Efficient Resource Allocation for Multi-RAT Heterogeneous Networks

    Guanding Yu;Yuhuan Jiang;Lukai Xu;Geoffrey Ye Li

Frequent Co-Authors

Zhaoyang Zhang
Zhaoyang Zhang Zhejiang University
Geoffrey Ye Li
Geoffrey Ye Li Imperial College London
Yunlong Cai
Yunlong Cai Zhejiang University
Peng Cheng
Peng Cheng Zhejiang University
Caijun Zhong
Caijun Zhong Zhejiang University
Hsiao-Hwa Chen
Hsiao-Hwa Chen National Cheng Kung University
Hangguan Shan
Hangguan Shan Zhejiang University
Zhi Ding
Zhi Ding University of California, Davis
Qingjiang Shi
Qingjiang Shi Tongji University
Yang Xu
Yang Xu Zhejiang University

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Related Online Degrees & Career Pathways

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Additionally, pursuing a competency based masters degree can provide a practical, skills-focused approach. This format allows students to progress at their own pace by demonstrating mastery of key competencies, ideal for professionals wanting to hone specific expertise in the engineering domain.

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