World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
79
Citations
36241
World Ranking
1123
National Ranking
160

Zhiyuan Liu 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 Zhiyuan Liu 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: 251 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Zhiyuan Liu 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 Zhiyuan Liu 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: 79 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Overview

Zhiyuan Liu is a researcher affiliated with Tsinghua University in China. Their main area of academic contribution lies within the field of Computer Science, with a substantial focus on Artificial Intelligence and related subdomains.

Their recent scholarly output includes several papers published in notable venues. These include:

  • "Graph neural networks: A review of methods and applications" (2020) published in AI Open
  • "Pre-trained models: Past, present and future" (2021) published in AI Open
  • "Parameter-efficient fine-tuning of large-scale pre-trained language models" (2023) published in Nature Machine Intelligence
  • "KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation" (2021) published in Transactions of the Association for Computational Linguistics
  • "PTR: Prompt Tuning with Rules for Text Classification" (2022) published in AI Open

Zhiyuan Liu has co-authored extensively with several prominent researchers. Frequent collaborators include Maosong Sun, Yankai Lin, Zhengyan Zhang, Yujia Qin, and Chaojun Xiao.

Publications are distributed across prominent venues, with a significant number appearing in:

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

Zhiyuan Liu's research covers a variety of topics within Computer Science, with emphasis on:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Advanced Graph Neural Networks
  • Domain Adaptation and Few-Shot Learning
  • Speech Recognition and Synthesis
  • Complex Network Analysis Techniques

Additional contributions include authoring two books published by Morgan & Claypool Publishers: "Introduction to Graph Neural Networks" (2020) and "Network Embedding: Theories, Methods, and Applications" (2021).

Best Publications

  • Graph Neural Networks: A Review of Methods and Applications

    Jie Zhou;Ganqu Cui;Shengding Hu;Zhengyan Zhang

  • Learning entity and relation embeddings for knowledge graph completion

    Yankai Lin;Zhiyuan Liu;Maosong Sun;Yang Liu

  • ERNIE: Enhanced Language Representation with Informative Entities

    Zhengyan Zhang;Xu Han;Zhiyuan Liu;Xin Jiang

  • Neural Relation Extraction with Selective Attention over Instances

    Yankai Lin;Shiqi Shen;Zhiyuan Liu;Huanbo Luan

  • Network representation learning with rich text information

    Cheng Yang;Zhiyuan Liu;Deli Zhao;Maosong Sun

  • Pre-Trained Models: Past, Present and Future

    Xu Han;Zhengyan Zhang;Ning Ding;Yuxian Gu

  • A C-LSTM Neural Network for Text Classification

    Chunting Zhou;Chonglin Sun;Zhiyuan Liu;Francis C. M. Lau

  • Representation learning of knowledge graphs with entity descriptions

    Ruobing Xie;Zhiyuan Liu;Jia Jia;Huanbo Luan

  • PTR: Prompt Tuning with Rules for Text Classification

    Unknown

  • KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation

    Xiaozhi Wang;Tianyu Gao;Zhaocheng Zhu;Zhengyan Zhang

  • Modeling Relation Paths for Representation Learning of Knowledge Bases

    Yankai Lin;Zhiyuan Liu;Huanbo Luan;Maosong Sun

  • FewRel: A Large-Scale Supervised Few-shot Relation Classification Dataset with State-of-the-Art Evaluation.

    Xu Han;Hao Zhu;Pengfei Yu;Ziyun Wang

  • End-to-End Neural Ad-hoc Ranking with Kernel Pooling

    Chenyan Xiong;Zhuyun Dai;Jamie Callan;Zhiyuan Liu

  • Relation Classification via Multi-Level Attention CNNs

    Linlin Wang;Zhu Cao;Gerard de Melo;Zhiyuan Liu

  • Topical word embeddings

    Yang Liu;Zhiyuan Liu;Tat-Seng Chua;Maosong Sun

  • DocRED: A Large-Scale Document-Level Relation Extraction Dataset.

    Yuan Yao;Deming Ye;Peng Li;Xu Han

  • Automatic Keyphrase Extraction via Topic Decomposition

    Zhiyuan Liu;Wenyi Huang;Yabin Zheng;Maosong Sun

  • A Unified Model for Word Sense Representation and Disambiguation

    Xinxiong Chen;Zhiyuan Liu;Maosong Sun

  • Clustering to Find Exemplar Terms for Keyphrase Extraction

    Zhiyuan Liu;Peng Li;Yabin Zheng;Maosong Sun

  • Adaptive Graph Encoder for Attributed Graph Embedding

    Ganqu Cui;Jie Zhou;Cheng Yang;Zhiyuan Liu

  • Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification

    Tianyu Gao;Xu Han;Zhiyuan Liu;Maosong Sun

  • Neural Sentiment Classification with User and Product Attention

    Huimin Chen;Maosong Sun;Cunchao Tu;Yankai Lin

Frequent Co-Authors

Maosong Sun
Maosong Sun Tsinghua University
Yankai Lin
Yankai Lin Tencent (China)
Ruobing Xie
Ruobing Xie Tencent (China)
Xu Han
Xu Han Tsinghua University
Juanzi Li
Juanzi Li Tsinghua University
Qun Liu
Qun Liu Huawei Technologies (China)
Jamie Callan
Jamie Callan Carnegie Mellon University
Hanwang Zhang
Hanwang Zhang Nanyang Technological University
Tat-Seng Chua
Tat-Seng Chua National University of Singapore
Minlie Huang
Minlie Huang Tsinghua University

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