World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
60
Citations
15021
World Ranking
1618
National Ranking
267

Computer Science

D-Index
61
Citations
16407
World Ranking
3045
National Ranking
410

Ping 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 Ping 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: 921 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Ping 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 Ping 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: 60 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Overview

Ping Zhang is affiliated with Beijing University of Posts and Telecommunications in China. Their research primarily focuses on the fields of Engineering and Computer Science, with substantial contributions within the subfields of Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Aerospace Engineering, and Computer Vision and Pattern Recognition.

The main topics covered in their work include:

  • Advanced Wireless Communication Technologies
  • Indoor and Outdoor Localization Technologies
  • IoT and Edge/Fog Computing
  • Wireless Signal Modulation Classification
  • Advanced MIMO Systems Optimization
  • UAV Applications and Optimization
  • Wireless Communication Security Techniques

Ping Zhang's recent publications demonstrate a focus on next-generation communication networks and applications of machine learning. Notable papers include:

  • Toward Wisdom-Evolutionary and Primitive-Concise 6G: A New Paradigm of Semantic Communication Networks, 2021, Engineering
  • Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts, 2020, Science China Information Sciences
  • Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images, 2021, Nature Biomedical Engineering
  • Nonlinear Transform Source-Channel Coding for Semantic Communications, 2022, IEEE Journal on Selected Areas in Communications
  • AoI-Energy-Aware UAV-Assisted Data Collection for IoT Networks: A Deep Reinforcement Learning Method, 2021, IEEE Internet of Things Journal

Frequent coauthors include:

  • Xiaodong Xu
  • Kai Niu
  • Zhiyong Feng
  • Xiaoqi Qin
  • Shujun Han

Publications are often found in a range of venues, with the most frequent being:

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

Best Publications

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

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

  • Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds

    Xinchen Lyu;Hui Tian;Cigdem Sengul;Ping Zhang

  • ConFi: Convolutional Neural Networks Based Indoor Wi-Fi Localization Using Channel State Information

    Hao Chen;Yifan Zhang;Wei Li;Xiaofeng Tao

  • Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

    Kang Zhang;Xiaohong Liu;Jie Xu;Jie Xu;Jin Yuan

  • Nonlinear Transform Source-Channel Coding for Semantic Communications

    Unknown

  • Toward Wisdom-Evolutionary and Primitive-Concise 6G:A New Paradigm of Semantic Communication Networks

    Ping Zhang;Wenjun Xu;Hui Gao;Kai Niu

  • Energy-Efficient Admission of Delay-Sensitive Tasks for Mobile Edge Computing

    Xinchen Lyu;Hui Tian;Wei Ni;Yan Zhang

  • Cooperative Task Offloading in Three-Tier Mobile Computing Networks: An ADMM Framework

    Yue Wang;Xiaofeng Tao;Xuefei Zhang;Ping Zhang

  • Outage Performance for Cognitive Relay Networks with Underlay Spectrum Sharing

    Unknown

  • Outage performance of relay-assisted cognitive-radio system under spectrum-sharing constraints

    Y. Guo;G. Kang;N. Zhang;W. Zhou

  • Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

    Unknown

  • Wireless Deep Video Semantic Transmission

    Unknown

  • Spatio-Temporal Wireless Traffic Prediction With Recurrent Neural Network

    Chen Qiu;Yanyan Zhang;Zhiyong Feng;Ping Zhang

  • A vision from the future: beyond 3G TDD

    Ping Zhang;Xiaofeng Tao;Jianhua Zhang;Ying Wang

  • AoI-Energy-Aware UAV-assisted Data Collection for IoT Networks: A Deep Reinforcement Learning Method

    Mengying Sun;Xiaodong Xu;Xiaoqi Qin;Ping Zhang

  • Automatic Modulation Classification of Overlapped Sources Using Multiple Cumulants

    Sai Huang;Yuanyuan Yao;Zhiqing Wei;Zhiyong Feng

  • Joint Communication, Sensing, and Computation Enabled 6G Intelligent Machine System

    Unknown

  • Cooperative Caching in Wireless P2P Networks: Design, Implementation, and Evaluation

    Jing Zhao;Ping Zhang;Guohong Cao;C.R. Das

  • WITT: A Wireless Image Transmission Transformer for Semantic Communications

    Unknown

  • A generalized QS-CDMA system and the design of new spreading codes

    Biqi Long;Ping Zhang;Jiandong Hu

  • 5G PRS-Based Sensing: A Sensing Reference Signal Approach for Joint Sensing and Communication System

    Unknown

  • 3-D MIMO: How Much Does It Meet Our Expectations Observed From Channel Measurements?

    Jianhua Zhang;Yuxiang Zhang;Yawei Yu;Ruijie Xu

  • A survey of security issues in Cognitive Radio Networks

    Jianwu Li;Zebing Feng;Zhiyong Feng;Ping Zhang

  • A Data-Driven Architecture for Personalized QoE Management in 5G Wireless Networks

    Ying Wang;Peilong Li;Lei Jiao;Zhou Su

  • Recent advances on TD-SCDMA in China

    Bo Li;Dongliang Xie;Shiduan Cheng;Junliang Chen

  • Outage Probability of Decode-and-Forward Cognitive Relay in Presence of Primary User's Interference

    Wei Xu;Jianhua Zhang;Ping Zhang;Chintha Tellambura

  • Stochastic Online Learning for Mobile Edge Computing: Learning from Changes

    Qimei Cui;Zhenzhen Gong;Wei Ni;Yanzhao Hou

  • An effective approach to 5G: Wireless network virtualization

    Zhiyong Feng;Chen Qiu;Zebing Feng;Zhiqing Wei

Frequent Co-Authors

Zhiyong Feng
Zhiyong Feng Beijing University of Posts and Telecommunications
Xiaofeng Tao
Xiaofeng Tao Beijing University of Posts and Telecommunications
Hui Tian
Hui Tian Beijing University of Posts and Telecommunications
Wei Ni
Wei Ni Edith Cowan University
Yuzhen Huang
Yuzhen Huang Hong Kong University of Science and Technology
Miao Pan
Miao Pan University of Houston
Ren Ping Liu
Ren Ping Liu University of Technology Sydney
Zhu Han
Zhu Han University of Houston
Shuguang Cui
Shuguang Cui Chinese University of Hong Kong, Shenzhen
Changsheng You
Changsheng You Southern University of Science and Technology

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