World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
12173
World Ranking
4795
National Ranking
640

Wanxiang Che 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 Wanxiang Che 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: 215 publications — 52nd percentile

52% of scientists in this discipline score the same or lower.

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

Wanxiang Che 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 Wanxiang Che 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

Wanxiang Che is affiliated with the Harbin Institute of Technology in China. Their research primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications, and Management Science and Operations Research.

Their work covers a range of topics, notably:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Speech and Dialogue Systems
  • Semantic Web and Ontologies
  • Sentiment Analysis and Opinion Mining
  • Text Readability and Simplification

Wanxiang Che has contributed research to various publication venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • International Journal of Machine Learning and Cybernetics
  • Frontiers of Computer Science
  • IEEE/ACM Transactions on Audio Speech and Language Processing

Frequent co-authors collaborating with Wanxiang Che include:

  • Libo Qin
  • Dingzirui Wang
  • Qingfu Zhu
  • Longxu Dou
  • Qiguang Chen

Significant papers authored or co-authored by Wanxiang Che include:

  • Data augmentation approaches in natural language processing: A survey, 2022, AI Open
  • DCR-Net: A Deep Co-Interactive Relation Network for Joint Dialog Act Recognition and Sentiment Classification, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • From static to dynamic word representations: a survey, 2020, International Journal of Machine Learning and Cybernetics
  • Knowledge Graph Grounded Goal Planning for Open-Domain Conversation Generation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding, 2020, arXiv (Cornell University)

Best Publications

  • Pre-Training with Whole Word Masking for Chinese BERT

    Yiming Cui;Wanxiang Che;Ting Liu;Bing Qin

  • Revisiting Pre-Trained Models for Chinese Natural Language Processing

    Yiming Cui;Wanxiang Che;Ting Liu;Bing Qin

  • LTP: A Chinese Language Technology Platform

    Wanxiang Che;Zhenghua Li;Ting Liu

  • Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency.

    Shuhuai Ren;Yihe Deng;Kun He;Wanxiang Che

  • LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding

    Yang Xu;Yiheng Xu;Tengchao Lv;Lei Cui

  • Learning Semantic Hierarchies via Word Embeddings

    Ruiji Fu;Jiang Guo;Bing Qin;Wanxiang Che

  • Data Augmentation Approaches in Natural Language Processing: A Survey.

    Bohan Li;Yutai Hou;Wanxiang Che

  • A stack-propagation framework with token-level intent detection for spoken language understanding

    Libo Qin;Wanxiang Che;Yangming Li;Haoyang Wen

  • Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation

    Wanxiang Che;Yijia Liu;Yuxuan Wang;Bo Zheng

  • A Span-Extraction Dataset for Chinese Machine Reading Comprehension.

    Yiming Cui;Ting Liu;Wanxiang Che;Li Xiao

  • Cross-lingual Dependency Parsing Based on Distributed Representations

    Jiang Guo;Wanxiang Che;David Yarowsky;Haifeng Wang

  • Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network

    Yutai Hou;Wanxiang Che;Yongkui Lai;Zhihan Zhou

  • Convolution Neural Network for Relation Extraction

    Chunyang Liu;Wenbo Sun;Wenhan Chao;Wanxiang Che

  • Towards Conversational Recommendation over Multi-Type Dialogs

    Zeming Liu;Haifeng Wang;Zheng-Yu Niu;Hua Wu

  • Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting

    Sanyuan Chen;Yutai Hou;Yiming Cui;Wanxiang Che

  • Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding

    Yutai Hou;Yijia Liu;Wanxiang Che;Ting Liu

  • Revisiting Embedding Features for Simple Semi-supervised Learning

    Jiang Guo;Wanxiang Che;Haifeng Wang;Ting Liu

  • Sentence compression for aspect-based sentiment analysis

    Wanxiang Che;Yanyan Zhao;Honglei Guo;Zhong Su

  • A Co-Interactive Transformer for Joint Slot Filling and Intent Detection

    Libo Qin;Tailu Liu;Wanxiang Che;Bingbing Kang

  • Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing

    Yuxuan Wang;Wanxiang Che;Jiang Guo;Yijia Liu

  • CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP

    Libo Qin;Minheng Ni;Yue Zhang;Wanxiang Che

Frequent Co-Authors

Ting Liu
Ting Liu Harbin Institute of Technology
Bing Qin
Bing Qin Harbin Institute of Technology
Haifeng Wang
Haifeng Wang Baidu (China)
Hua Wu
Hua Wu Baidu (China)
Min Zhang
Min Zhang Tsinghua University
Yue Zhang
Yue Zhang Westlake University
Meishan Zhang
Meishan Zhang Harbin Institute of Technology
Furu Wei
Furu Wei Microsoft (United States)
Li Dong
Li Dong Microsoft (United States)
David Yarowsky
David Yarowsky Johns Hopkins University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Computer Science in the USA opens doors to a wide range of online degrees and career pathways in related fields. As technology influences every sector, professionals with diverse digital skills are increasingly in demand.

If you’re interested in digital security, consider an accredited online cyber security degree. This field focuses on protecting data and systems, an essential aspect across industries.

For those who wish to merge technology with infrastructure, construction degrees can provide the knowledge to manage complex projects, including smart building technology.

An criminal justice degree is another option, combining computer science with law enforcement to address issues like cybercrime and digital investigations.

Finally, those with an interest in business analytics may choose an accounting degree online. Modern accounting relies heavily on digital systems, making technical proficiency highly valuable.

Each of these pathways connects computer science with real-world applications, ensuring graduates remain relevant and adaptable in a rapidly evolving job market.

Best Scientists Citing Wanxiang Che

Trending Scientists

Recently Published Articles