World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
13160
World Ranking
4762
National Ranking
636

Jun Xu 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 Jun Xu 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: 361 publications — 83rd percentile

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

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

Jun Xu 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 Jun Xu 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

Jun Xu is affiliated with Renmin University of China and specializes in Computer Science, with a primary focus on Artificial Intelligence. Their research spans subfields including Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Management Science and Operations Research. The scientist's work also covers diverse topics such as Topic Modeling, Recommender Systems and Techniques, Natural Language Processing Techniques, Advanced Graph Neural Networks, Advanced Bandit Algorithms Research, Multimodal Machine Learning Applications, and Speech and Dialogue Systems.

The scientist has published extensively, with a significant number of contributions to venues such as arXiv (Cornell University), ACM Transactions on Information Systems, SSRN Electronic Journal, Frontiers of Computer Science, and IET conference proceedings.

Recent papers authored or coauthored by Jun Xu include:

  • Knowledge Graph Grounded Goal Planning for Open-Domain Conversation Generation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Deep Network for the Automatic Segmentation and Quantification of Intracranial Hemorrhage on CT, 2021, Frontiers in Neuroscience

Jun Xu frequently collaborates with researchers such as Ji-Rong Wen, Xiao Zhang, Zihua Si, Zhenhua Dong, and Zhongxiang Sun.

In addition to journal and conference papers, Jun Xu has book publications including:

  • The Future and FinTech, 2021, published by World Scientific

Best Publications

  • MSR-VTT: A Large Video Description Dataset for Bridging Video and Language

    Jun Xu;Tao Mei;Ting Yao;Yong Rui

  • AdaRank: a boosting algorithm for information retrieval

    Jun Xu;Hang Li

  • Adapting ranking SVM to document retrieval

    Yunbo Cao;Jun Xu;Tie-Yan Liu;Hang Li

  • LETOR: A benchmark collection for research on learning to rank for information retrieval

    Tao Qin;Tie-Yan Liu;Jun Xu;Hang Li

  • Text matching as image recognition

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • LETOR: Benchmark Dataset for Research on Learning to Rank for Information Retrieval

    Tie-Yan Liu;Jun Xu;Tao Qin;Wenying Xiong

  • Learning Hierarchical Representation Model for NextBasket Recommendation

    Pengfei Wang;Jiafeng Guo;Yanyan Lan;Jun Xu

  • A deep architecture for semantic matching with multiple positional sentence representations

    Shengxian Wan;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Multivariate Time Series Imputation with Generative Adversarial Networks

    Yonghong Luo;Xiangrui Cai;Ying Zhang;Jun Xu

  • DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Text Matching as Image Recognition

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Semantic Matching in Search

    Hang Li;Jun Xu

  • Uncovering ChatGPT’s Capabilities in Recommender Systems

    Unknown

  • Learning Multimodal Attention LSTM Networks for Video Captioning

    Jun Xu;Ting Yao;Yongdong Zhang;Tao Mei

  • Directly optimizing evaluation measures in learning to rank

    Jun Xu;Tie-Yan Liu;Min Lu;Hang Li

  • Semantic Matching in Search

    Unknown

  • Match-SRNN: modeling the recursive matching structure with spatial RNN

    Shengxian Wan;Yanyan Lan;Jun Xu;Jiafeng Guo

  • Clinical Named Entity Recognition Using Deep Learning Models.

    Yonghui Wu;Min Jiang;Jun Xu;Degui Zhi

  • A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations

    Shengxian Wan;Yanyan Lan;Jiafeng Guo;Jun Xu

  • A Study of Neural Word Embeddings for Named Entity Recognition in Clinical Text.

    Yonghui Wu;Jun Xu;Min Jiang;Yaoyun Zhang

  • A Study of MatchPyramid Models on Ad-hoc Retrieval.

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval

    Liang Pang;Jun Xu;Qingyao Ai;Yanyan Lan

  • Regularized latent semantic indexing

    Quan Wang;Jun Xu;Hang Li;Nick Craswell

  • Reinforcement Learning to Rank with Markov Decision Process

    Zeng Wei;Jun Xu;Yanyan Lan;Jiafeng Guo

  • A probabilistic model for bursty topic discovery in microblogs

    Xiaohui Yan;Jiafeng Guo;Yanyan Lan;Jun Xu

  • Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN

    Shengxian Wan;Yanyan Lan;Jun Xu;Jiafeng Guo

  • Learning to Control the Specificity in Neural Response Generation

    Ruqing Zhang;Jiafeng Guo;Yixing Fan;Yanyan Lan

  • Deep Learning for Matching in Search and Recommendation

    Jun Xu;Xiangnan He;Hang Li

  • Modeling Diverse Relevance Patterns in Ad-hoc Retrieval

    Yixing Fan;Jiafeng Guo;Yanyan Lan;Jun Xu

Frequent Co-Authors

Xueqi Cheng
Xueqi Cheng Chinese Academy of Sciences
Yanyan Lan
Yanyan Lan Chinese Academy of Sciences
Jiafeng Guo
Jiafeng Guo Chinese Academy of Sciences
Hang Li
Hang Li ByteDance
Ji-Rong Wen
Ji-Rong Wen Renmin University of China
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Nianwen Xue
Nianwen Xue Brandeis University
Nick Craswell
Nick Craswell Microsoft (United States)
Fei Sun
Fei Sun Institute Of Computing Technology
Jun Guo
Jun Guo Beijing University of Posts and Telecommunications

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