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Hai-Tao Zheng

Hai-Tao Zheng

Hai-Tao Zheng 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 Hai-Tao Zheng 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+

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

Hai-Tao Zheng 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 Hai-Tao Zheng 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+

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

Overview

Hai-Tao Zheng is affiliated with Tsinghua University in China. Their research primarily focuses on the field of Computer Science, with extensive work in several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications, and Signal Processing.

The scientist has contributed to research covering multiple key topics:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Domain Adaptation and Few-Shot Learning
  • Advanced Graph Neural Networks
  • Adversarial Robustness in Machine Learning

Hai-Tao Zheng has published extensively, with a notable presence in prominent academic venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SSRN Electronic Journal
  • IEEE Transactions on Knowledge and Data Engineering
  • 2022 International Joint Conference on Neural Networks (IJCNN)

Their recent papers illustrate a diverse research scope and collaboration with other scholars. Selected recent works include:

  • "Parameter-efficient fine-tuning of large-scale pre-trained language models," 2023, Nature Machine Intelligence
  • "Modeling Relation Paths for Knowledge Graph Completion," 2020, IEEE Transactions on Knowledge and Data Engineering
  • "Are we ready for a new paradigm shift? A survey on visual deep MLP," 2022, Patterns
  • "The effect of institutional ownership on listed companies' tax avoidance strategies," 2020, Applied Economics
  • "OpenPrompt: An Open-source Framework for Prompt-learning," 2021, arXiv (Cornell University)

Hai-Tao Zheng frequently collaborates with a number of co-authors. Among the most frequent are:

  • Yangning Li
  • Yinghui Li
  • Ying Shen
  • Ben Y. Zhao
  • Shirong Ma

Best Publications

  • ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

    Ningning Ma;Xiangyu Zhang;Hai-Tao Zheng;Jian Sun

  • Parameter-efficient fine-tuning of large-scale pre-trained language models

    Unknown

  • Few-NERD: A Few-shot Named Entity Recognition Dataset

    Ning Ding;Guangwei Xu;Yulin Chen;Xiaobin Wang

  • OpenPrompt: An Open-source Framework for Prompt-learning

    Ning Ding;Shengding Hu;Weilin Zhao;Yulin Chen

  • Modeling Relation Paths for Knowledge Graph Completion

    Ying Shen;Ning Ding;Hai-Tao Zheng;Yaliang Li

  • Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

    Unknown

  • Exploiting noun phrases and semantic relationships for text document clustering

    Hai-Tao Zheng;Bo-Yeong Kang;Hong-Gee Kim

  • Applying policy network theory to policy-making in China: the case of urban health insurance reform.

    Haitao Zheng;Martin De Jong;Joop Koppenjan

  • Prompt-Learning for Fine-Grained Entity Typing.

    Ning Ding;Yulin Chen;Xu Han;Guangwei Xu

  • An ontology-based approach to learnable focused crawling

    Hai-Tao Zheng;Bo-Yeong Kang;Hong-Gee Kim

  • CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding

    Dong Wang;Ning Ding;Piji Li;Haitao Zheng

  • Byte Segment Neural Network for Network Traffic Classification

    Rui Li;Xi Xiao;Shiguang Ni;Haitao Zheng

  • Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge.

    Ziran Li;Ning Ding;Zhiyuan Liu;Haitao Zheng

  • An Ontology-Based Bayesian Network Approach for Representing Uncertainty in Clinical Practice Guidelines

    Hai-Tao Zheng;Bo-Yeong Kang;Hong-Gee Kim

  • EBSNN: Extended Byte Segment Neural Network for Network Traffic Classification

    Xi Xiao;Wentao Xiao;Rui Li;Xiapu Luo

  • A semantic similarity measure based on information distance for ontology alignment

    Yong Jiang;Xinmin Wang;Hai-Tao Zheng

  • Event Detection with Trigger-Aware Lattice Neural Network.

    Ning Ding;Ziran Li;Zhiyuan Liu;Haitao Zheng

  • MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

    Unknown

  • Deterministic Constructions of Binary Measurement Matrices From Finite Geometry

    Shu-Tao Xia;Xin-Ji Liu;Yong Jiang;Hai-Tao Zheng

  • Clickbait Convolutional Neural Network

    Hai-Tao Zheng;Jin-Yuan Chen;Xin Yao;Arun Kumar Sangaiah

  • Prototypical Representation Learning for Relation Extraction

    Ning Ding;Xiaobin Wang;Yao Fu;Guangwei Xu

  • The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection

    Zibo Lin;Deng Cai;Yan Wang;Xiaojiang Liu

  • TRSDL: Tag-Aware Recommender System Based on Deep Learning–Intelligent Computing Systems

    Nan Liang;Hai-Tao Zheng;Jin-Yuan Chen;Arun Kumar Sangaiah

  • Sparks and Deterministic Constructions of Binary Measurement Matrices from Finite Geometry

    Shu-Tao Xia;Xin-Ji Liu;Yong Jiang;Hai-Tao Zheng

Frequent Co-Authors

Arun Kumar Sangaiah
Arun Kumar Sangaiah National Yunlin University of Science and Technology
Ying Shen
Ying Shen Sun Yat-sen University
Yaliang Li
Yaliang Li Alibaba Group (China)
Dong Wang
Dong Wang Dalian University of Technology
Rui Zhang
Rui Zhang National University of Singapore
Juanzi Li
Juanzi Li Tsinghua University
Shuming Shi
Shuming Shi Tencent (China)
Jian Sun
Jian Sun Megvii
Xiapu Luo
Xiapu Luo Hong Kong Polytechnic University

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