World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
8899
World Ranking
6491
National Ranking
865

Rui Yan 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 Rui Yan 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: 197 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Rui Yan 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 Rui Yan 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Rui Yan is affiliated with Renmin University of China and has an extensive publication record primarily in the field of Computer Science, with a focus on Artificial Intelligence. Their research covers several subfields including Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Neurology.

The main topics of Rui Yan's work include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Speech and Dialogue Systems
  • Advanced Text Analysis Techniques
  • Multimodal Machine Learning Applications
  • Neurological Disorders and Treatments
  • AI in Service Interactions

They have contributed scholarly articles to various publication venues. The most frequent venues for their work include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SSRN Electronic Journal
  • ACM Transactions on Information Systems
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Rui Yan has collaborated with several notable co-authors, including:

  • Dongyan Zhao
  • Xiuying Chen
  • Shen Gao
  • Chongyang Tao
  • Mingzhe Li

Among their recent papers are:

  • "Temporal trends in the prevalence of Parkinson's disease from 1980 to 2023: a systematic review and meta-analysis" (2024, The Lancet Healthy Longevity)
  • "Projections for prevalence of Parkinson's disease and its driving factors in 195 countries and territories to 2050: modelling study of Global Burden of Disease Study 2021" (2025, BMJ)
  • "Low-Resource Knowledge-Grounded Dialogue Generation" (2020, arXiv (Cornell University))
  • "Metrnl Alleviates Lipid Accumulation by Modulating Mitochondrial Homeostasis in Diabetic Nephropathy" (2023, Diabetes)
  • "MISC: A Mixed Strategy-Aware Model integrating COMET for Emotional Support Conversation" (2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers))

The diversity of Rui Yan's publications spans artificial intelligence methodologies applied to both computational systems and biomedical contexts, demonstrating interdisciplinary integration between technology and health sciences.

Best Publications

  • Style Transfer in Text: Exploration and Evaluation

    Zhenxin Fu;Xiaoye Tan;Nanyun Peng;Dongyan Zhao

  • Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

    Yuting Wu;Xiao Liu;Yansong Feng;Zheng Wang

  • Natural Language Inference by Tree-Based Convolution and Heuristic Matching

    Lili Mou;Rui Men;Ge Li;Yan Xu

  • Learning to Respond with Deep Neural Networks for Retrieval-Based Human-Computer Conversation System

    Rui Yan;Yiping Song;Hua Wu

  • Plan-And-Write: Towards Better Automatic Storytelling

    Lili Yao;Nanyun Peng;Ralph M. Weischedel;Kevin Knight

  • How Transferable are Neural Networks in NLP Applications

    Lili Mou;Zhao Meng;Rui Yan;Ge Li

  • Multi-view Response Selection for Human-Computer Conversation

    Xiangyang Zhou;Daxiang Dong;Hua Wu;Shiqi Zhao

  • Evolutionary timeline summarization: a balanced optimization framework via iterative substitution

    Rui Yan;Xiaojun Wan;Jahna Otterbacher;Liang Kong

  • Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation

    Lili Mou;Yiping Song;Rui Yan;Ge Li

  • RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems

    Chongyang Tao;Lili Mou;Dongyan Zhao;Rui Yan

  • Citation count prediction: learning to estimate future citations for literature

    Rui Yan;Jie Tang;Xiaobing Liu;Dongdong Shan

  • CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling

    Ning Miao;Hao Zhou;Lili Mou;Rui Yan

  • Get The Point of My Utterance! Learning Towards Effective Responses with Multi-Head Attention Mechanism

    Chongyang Tao;Shen Gao;Mingyue Shang;Wei Wu

  • One Time of Interaction May Not Be Enough: Go Deep with an Interaction-over-Interaction Network for Response Selection in Dialogues.

    Chongyang Tao;Wei Wu;Can Xu;Wenpeng Hu

  • How to Make Context More Useful? An Empirical Study on Context-Aware Neural Conversational Models

    Zhiliang Tian;Rui Yan;Lili Mou;Yiping Song

  • Knowledge-Grounded Dialogue Generation with Pre-trained Language Models

    Xueliang Zhao;Wei Wu;Can Xu;Chongyang Tao

  • Multi-Representation Fusion Network for Multi-Turn Response Selection in Retrieval-Based Chatbots

    Chongyang Tao;Wei Wu;Can Xu;Wenpeng Hu

  • Tweet Recommendation with Graph Co-Ranking

    Rui Yan;Mirella Lapata;Xiaoming Li

  • To better stand on the shoulder of giants

    Rui Yan;Congrui Huang;Jie Tang;Yan Zhang

  • Timeline Generation through Evolutionary Trans-Temporal Summarization

    Rui Yan;Liang Kong;Congrui Huang;Xiaojun Wan

  • OVERCOMING CATASTROPHIC FORGETTING FOR CONTINUAL LEARNING VIA MODEL ADAPTATION

    Wenpeng Hu;Zhou Lin;Bing Liu;Chongyang Tao

Frequent Co-Authors

Dongyan Zhao
Dongyan Zhao Peking University
Yansong Feng
Yansong Feng Peking University
Lili Mou
Lili Mou University of Alberta
Lidong Bing
Lidong Bing Carnegie Mellon University
Lu Zhang
Lu Zhang Peking University
Bing Liu
Bing Liu University of Illinois at Chicago
Zhaochun Ren
Zhaochun Ren Shandong University
Mirella Lapata
Mirella Lapata University of Edinburgh
Xiaohua Hu
Xiaohua Hu Drexel University
Nanyun Peng
Nanyun Peng University of California, Los Angeles

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