World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
74
Citations
22711
World Ranking
707
National Ranking
111

Computer Science

D-Index
82
Citations
27259
World Ranking
960
National Ranking
141

Yong 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 Yong 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: 491 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Yong 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 Yong 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: 74 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Overview

Yong Li is affiliated with Tsinghua University in China and has an extensive publication record in the domains of computer science and engineering. Their research output spans 560 publications in computer science and 308 in engineering, highlighting a multidisciplinary approach to technological challenges.

Their work has delved into a variety of subfields including artificial intelligence, transportation, computer networks and communications, computer vision and pattern recognition, and information systems.

  • Artificial Intelligence
  • Transportation
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems

Yong Li's research topics reflect a focus on complex systems and data-driven applications. The main topics covered in their work are human mobility and location-based analysis, recommender systems and techniques, traffic prediction and management techniques, advanced graph neural networks, topic modeling, privacy-preserving technologies in data, and caching and content delivery.

  • Human Mobility and Location-Based Analysis
  • Recommender Systems and Techniques
  • Traffic Prediction and Management Techniques
  • Advanced Graph Neural Networks
  • Topic Modeling
  • Privacy-Preserving Technologies in Data
  • Caching and Content Delivery

Several recent publications by Yong Li exemplify their engagement with graph neural networks, traffic prediction, and computer vision methodologies:

  • A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions (2023), ACM Transactions on Recommender Systems
  • Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution (2022), ACM Transactions on Knowledge Discovery from Data
  • Scene Segmentation With Dual Relation-Aware Attention Network (2020), IEEE Transactions on Neural Networks and Learning Systems
  • Graph Neural Networks for Recommender System (2022), Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • Latency Minimization for D2D-Enabled Partial Computation Offloading in Mobile Edge Computing (2020), IEEE Transactions on Vehicular Technology

Frequent co-authors of Yong Li include Depeng Jin, Chen Gao, Huandong Wang, Fengli Xu, and Tong Li, indicating collaboration across a network of researchers.

  • Depeng Jin
  • Chen Gao
  • Huandong Wang
  • Fengli Xu
  • Tong Li

Their research has been disseminated through various prominent publication venues, such as arXiv, ACM Transactions on Intelligent Systems and Technology, ACM Transactions on Knowledge Discovery from Data, SSRN Electronic Journal, and IEEE Transactions on Knowledge and Data Engineering.

  • arXiv (Cornell University)
  • ACM Transactions on Intelligent Systems and Technology
  • ACM Transactions on Knowledge Discovery from Data
  • SSRN Electronic Journal
  • IEEE Transactions on Knowledge and Data Engineering

Yong Li has also contributed to book publications, notably with Springer Science+Business Media. Among the titles is Geoinformatics in Sustainable Ecosystem and Society, published in 2020.

Best Publications

  • A survey of millimeter wave communications (mmWave) for 5G: opportunities and challenges

    Yong Niu;Yong Li;Depeng Jin;Li Su

  • Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures

    Xueshi Hou;Yong Li;Min Chen;Di Wu

  • DeepMove: Predicting Human Mobility with Attentional Recurrent Networks

    Jie Feng;Yong Li;Chao Zhang;Funing Sun

  • Software-Defined Network Function Virtualization: A Survey

    Yong Li;Min Chen

  • System architecture and key technologies for 5G heterogeneous cloud radio access networks

    Mugen Peng;Yong Li;Zhongyuan Zhao;Chonggang Wang

  • Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution

    Fuxian Li;Jie Feng;Huan Yan;Guangyin Jin

  • Sequential Recommendation with Graph Neural Networks

    Jianxin Chang;Chen Gao;Yu Zheng;Yiqun Hui

  • Wearable 2.0: Enabling Human-Cloud Integration in Next Generation Healthcare Systems

    Min Chen;Yujun Ma;Yong Li;Di Wu

  • Multi-behavior Recommendation with Graph Convolutional Networks

    Bowen Jin;Chen Gao;Xiangnan He;Depeng Jin

  • Software-Defined and Virtualized Future Mobile and Wireless Networks: A Survey

    Mao Yang;Yong Li;Depeng Jin;Lieguang Zeng

  • Security and Privacy in Device-to-Device (D2D) Communication: A Review

    Michael Haus;Muhammad Waqas;Aaron Yi Ding;Yong Li

  • Disentangling User Interest and Conformity for Recommendation with Causal Embedding

    Yu Zheng;Chen Gao;Xiang Li;Xiangnan He

  • On the computation offloading at ad hoc cloudlet: architecture and service modes

    Min Chen;Yixue Hao;Yong Li;Chin-Feng Lai

  • Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach

    Fengli Xu;Yuyun Lin;Jiaxin Huang;Di Wu

  • iDoctor: Personalized and professionalized medical recommendations based on hybrid matrix factorization

    Yin Zhang;Min Chen;Dijiang Huang;Di Wu

  • Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

    Fengli Xu;Yong Li;Huandong Wang;Pengyu Zhang

  • DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis

    Ziqian Lin;Jie Feng;Ziyang Lu;Yong Li

  • Social-aware D2D communications: qualitative insights and quantitative analysis

    Yong Li;Ting Wu;Pan Hui;Depeng Jin

  • Coalitional Games for Resource Allocation in the Device-to-Device Uplink Underlaying Cellular Networks

    Yong Li;Depeng Jin;Jian Yuan;Zhu Han

  • A Survey of Millimeter Wave (mmWave) Communications for 5G: Opportunities and Challenges.

    Yong Niu;Yong Li;Depeng Jin;Li Su

  • Latency Minimization for D2D-Enabled Partial Computation Offloading in Mobile Edge Computing

    Umber Saleem;Yu Liu;Sobia Jangsher;Xiaoming Tao

  • Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

    Huandong Wang;Fengli Xu;Yong Li;Pengyu Zhang

Frequent Co-Authors

Depeng Jin
Depeng Jin Tsinghua University
Pan Hui
Pan Hui Hong Kong University of Science and Technology
Sheng Chen
Sheng Chen University of Southampton
Min Chen
Min Chen South China University of Technology
Sasu Tarkoma
Sasu Tarkoma University of Helsinki
Xiangnan He
Xiangnan He University of Science and Technology of China
Zhaocheng Wang
Zhaocheng Wang Tsinghua University
Zhu Han
Zhu Han University of Houston
Vassilis Kostakos
Vassilis Kostakos University of Melbourne
Athanasios V. Vasilakos
Athanasios V. Vasilakos University of Agder

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Related Online Degrees & Career Pathways

For students pursuing Electronics and Electrical Engineering, expanding skills through related online degrees can open diverse career opportunities. A bachelor's degree in project management is highly valuable for engineers aiming to lead complex technical projects, combining technical expertise with leadership skills.

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For those interested in education technology within engineering fields, pursuing online masters in instructional design equips graduates to develop effective training programs, benefiting companies that require ongoing employee development.

Competency is key in technical careers. Competency based masters degrees focus on mastering specific skills at an individual's own pace, providing practical knowledge that can directly impact engineering roles and career advancement.

Exploring these pathways alongside a foundation in Electronics and Electrical Engineering helps build a versatile skill set for today’s dynamic job market.

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