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D-Index
39
Citations
5758
World Ranking
693
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106

Computer Science

D-Index
41
Citations
6457
World Ranking
8908
National Ranking
3791

Yanjie Fu publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yanjie Fu sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 250 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Yanjie Fu D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Yanjie Fu sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Yanjie Fu is a researcher affiliated with Arizona State University in the United States. Their work predominantly falls under the broader field of Computer Science, with a focus on several specialized subfields including Artificial Intelligence, Transportation, Information Systems, Signal Processing, and Computer Vision and Pattern Recognition.

The researcher has contributed extensively to various topics such as:

  • Human Mobility and Location-Based Analysis
  • Machine Learning and Data Classification
  • Advanced Graph Neural Networks
  • Recommender Systems and Techniques
  • Topic Modeling
  • Traffic Prediction and Management Techniques
  • Domain Adaptation and Few-Shot Learning

Yanjie Fu's publication record is significant, with a strong presence in well-known venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Transactions on Intelligent Systems and Technology
  • ACM Transactions on Knowledge Discovery from Data

Several notable papers authored or co-authored by Yanjie Fu are:

  • Coupled Layer-wise Graph Convolution for Transportation Demand Prediction, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting, 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning, 2022, Proceedings of the ACM Web Conference 2022
  • Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting, 2023, Proceedings of the AAAI Conference on Artificial Intelligence
  • Automated Feature Selection: A Reinforcement Learning Perspective, 2021, IEEE Transactions on Knowledge and Data Engineering

Their frequent collaborators include:

  • Dongjie Wang
  • Kunpeng Liu
  • Pengyang Wang
  • Hui Xiong
  • Yuanchun Zhou

Best Publications

  • A Neural Influence Diffusion Model for Social Recommendation

    Le Wu;Peijie Sun;Yanjie Fu;Richang Hong

  • Learning geographical preferences for point-of-interest recommendation

    Bin Liu;Yanjie Fu;Zijun Yao;Hui Xiong

  • Dynamic and Multi-faceted Spatio-temporal Deep Learning for Traffic Speed Forecasting

    Liangzhe Han;Bowen Du;Leilei Sun;Yanjie Fu

  • A General Geographical Probabilistic Factor Model for Point of Interest Recommendation

    Bin Liu;Hui Xiong;Spiros Papadimitriou;Yanjie Fu

  • Coupled Layer-wise Graph Convolution for Transportation Demand Prediction.

    Junchen Ye;Leilei Sun;Bowen Du;Yanjie Fu

  • Service Usage Classification with Encrypted Internet Traffic in Mobile Messaging Apps

    Yanjie Fu;Hui Xiong;Xinjiang Lu;Jin Yang

  • Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning

    Unknown

  • Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network

    Junchen Ye;Leilei Sun;Bowen Du;Yanjie Fu

  • Station Site Optimization in Bike Sharing Systems

    Junming Liu;Qiao Li;Meng Qu;Weiwei Chen

  • Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach

    Le Wu;Yonghui Yang;Kun Zhang;Richang Hong

  • SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation.

    Le Wu;Peijie Sun;Richang Hong;Yanjie Fu

  • Sparse Real Estate Ranking with Online User Reviews and Offline Moving Behaviors

    Yanjie Fu;Yong Ge;Yu Zheng;Zijun Yao

  • Exploiting geographic dependencies for real estate appraisal: a mutual perspective of ranking and clustering

    Yanjie Fu;Hui Xiong;Yong Ge;Zijun Yao

  • POI Recommendation: A Temporal Matching between POI Popularity and User Regularity

    Zijun Yao;Yanjie Fu;Bin Liu;Yanchi Liu

  • Representing urban functions through zone embedding with human mobility patterns

    Zijun Yao;Yanjie Fu;Bin Liu;Wangsu Hu

  • Fake News Detection with Deep Diffusive Network Model.

    Jiawei Zhang;Limeng Cui;Yanjie Fu;Fisher B. Gouza

  • Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes

    Pengfei Wang;Yanjie Fu;Guannan Liu;Wenqing Hu

  • Intelligent bus routing with heterogeneous human mobility patterns

    Yanchi Liu;Chuanren Liu;Nicholas Jing Yuan;Lian Duan

  • Dual Learning for Explainable Recommendation: Towards Unifying User Preference Prediction and Review Generation

    Peijie Sun;Le Wu;Kun Zhang;Yanjie Fu

  • A Hierarchical Attention Model for Social Contextual Image Recommendation

    Le Wu;Lei Chen;Richang Hong;Yanjie Fu

  • Joint Representation Learning for Multi-Modal Transportation Recommendation

    Hao Liu;Ting Li;Renjun Hu;Yanjie Fu

Frequent Co-Authors

Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Yong Ge
Yong Ge University of Arizona
Charu C. Aggarwal
Charu C. Aggarwal IBM (United States)
Richang Hong
Richang Hong Hefei University of Technology
Wei Fan
Wei Fan Tencent (China)
Yu Zheng
Yu Zheng Jingdong (China)
Enhong Chen
Enhong Chen University of Science and Technology of China
Chang-Tien Lu
Chang-Tien Lu Virginia Tech
Dan Lin
Dan Lin University of Missouri
Sajal K. Das
Sajal K. Das Missouri University of Science and Technology

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