World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
8996
World Ranking
8278
National Ranking
1082

Defu Lian 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 Defu Lian 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 292 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Defu Lian 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 Defu Lian sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Defu Lian is affiliated with the University of Science and Technology of China. Their research primarily falls within the field of Computer Science, with a significant focus on various subfields including Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Signal Processing.

The scientist's work extensively covers topics related to Recommender Systems and Techniques, Topic Modeling, Advanced Graph Neural Networks, Advanced Image and Video Retrieval Techniques, Natural Language Processing Techniques, Advanced Bandit Algorithms Research, and Domain Adaptation and Few-Shot Learning.

Defu Lian has authored numerous papers published in notable venues. Some recent publications include:

  • A Survey on Session-based Recommender Systems, 2021, ACM Computing Surveys
  • When large language models meet personalization: perspectives of challenges and opportunities, 2024, World Wide Web
  • Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Frequency-domain MLPs are More Effective Learners in Time Series Forecasting, 2023, arXiv (Cornell University)
  • HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization, 2022, Proceedings of the ACM Web Conference 2022

Throughout their career, Defu Lian has collaborated with a number of other researchers. Frequent co-authors include Enhong Chen, Zheng Liu, Xing Xie, Chenwang Wu, and Shitao Xiao.

The scientist's publications appear regularly in several recurring venues such as arXiv (Cornell University), ACM Transactions on Information Systems, IEEE Transactions on Knowledge and Data Engineering, Proceedings of the AAAI Conference on Artificial Intelligence, and Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.

Best Publications

  • Collaborative Knowledge Base Embedding for Recommender Systems

    Fuzheng Zhang;Nicholas Jing Yuan;Defu Lian;Xing Xie

  • GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation

    Defu Lian;Cong Zhao;Xing Xie;Guangzhong Sun

  • A Survey on Session-based Recommender Systems

    Shoujin Wang;Longbing Cao;Yan Wang;Quan Z. Sheng

  • M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

    Unknown

  • Geography-Aware Sequential Location Recommendation

    Defu Lian;Yongji Wu;Yong Ge;Xing Xie

  • Attention-based transactional context embedding for next-item recommendation

    Shoujin Wang;Liang Hu;Longbing Cao;Xiaoshui Huang

  • When large language models meet personalization: perspectives of challenges and opportunities

    Unknown

  • Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data

    Yingzi Wang;Nicholas Jing Yuan;Defu Lian;Linli Xu

  • C-Pack: Packed Resources For General Chinese Embeddings

    Unknown

  • MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

    Hao Wang;Tong Xu;Qi Liu;Defu Lian

  • Neural Memory Streaming Recommender Networks with Adversarial Training

    Qinyong Wang;Hongzhi Yin;Zhiting Hu;Defu Lian

  • Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection

    Yongji Wu;Defu Lian;Yiheng Xu;Le Wu

  • GeoMF++: Scalable Location Recommendation via Joint Geographical Modeling and Matrix Factorization

    Defu Lian;Kai Zheng;Yong Ge;Longbing Cao

  • We know how you live: exploring the spectrum of urban lifestyles

    Nicholas Jing Yuan;Fuzheng Zhang;Defu Lian;Kai Zheng

  • HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization

    Unknown

  • Content-Aware Collaborative Filtering for Location Recommendation Based on Human Mobility Data

    Defu Lian;Yong Ge;Fuzheng Zhang;Nicholas Jing Yuan

  • CEPR: A Collaborative Exploration and Periodically Returning Model for Location Prediction

    Defu Lian;Xing Xie;Vincent W. Zheng;Nicholas Jing Yuan

  • Binarized attributed network embedding

    Hong Yang;Shirui Pan;Peng Zhang;Ling Chen

  • Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

    Unknown

  • Scalable Content-Aware Collaborative Filtering for Location Recommendation

    Defu Lian;Yong Ge;Fuzheng Zhang;Nicholas Jing Yuan

  • Personalized Ranking with Importance Sampling

    Defu Lian;Qi Liu;Enhong Chen

  • GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph

    Junhan Yang;Zheng Liu;Shitao Xiao;Chaozhuo Li

  • Learning location naming from user check-in histories

    Defu Lian;Xing Xie

  • Discrete Deep Learning for Fast Content-Aware Recommendation

    Yan Zhang;Hongzhi Yin;Zi Huang;Xingzhong Du

  • Exploiting Dining Preference for Restaurant Recommendation

    Fuzheng Zhang;Nicholas Jing Yuan;Kai Zheng;Defu Lian

  • LightRec: A Memory and Search-Efficient Recommender System

    Defu Lian;Haoyu Wang;Zheng Liu;Jianxun Lian

Frequent Co-Authors

Xing Xie
Xing Xie Microsoft Research Asia (China)
Enhong Chen
Enhong Chen University of Science and Technology of China
Yong Ge
Yong Ge University of Arizona
Nicholas Jing Yuan
Nicholas Jing Yuan Microsoft (United States)
Qi Liu
Qi Liu University of Science and Technology of China
Tao Zhou
Tao Zhou University of Electronic Science and Technology of China
Kai Zheng
Kai Zheng University of Electronic Science and Technology of China
Yong Rui
Yong Rui Lenovo (China)
Longbing Cao
Longbing Cao University of Technology Sydney
Hongzhi Yin
Hongzhi Yin University of Queensland

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