World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
14178
World Ranking
5003
National Ranking
672

Wenjie Li 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 Wenjie Li 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: 289 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Wenjie Li 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 Wenjie Li 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: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Overview

Wenjie Li is affiliated with Hong Kong Polytechnic University in China and has contributed extensively to the field of computer science, with a primary focus on artificial intelligence. Their research interests span several subfields, including artificial intelligence, computer vision and pattern recognition, computational mechanics, information systems, and molecular biology.

The scientist's work covers a range of topics such as topic modeling, natural language processing techniques, multimodal machine learning applications, speech and dialogue systems, advanced text analysis techniques, advanced graph neural networks, and recommender systems and techniques. These areas reflect their engagement with cutting-edge developments in both theoretical and applied aspects of computer science.

Wenjie Li's frequent collaborators include Yongqi Li, Ziqiang Cao, Yi Cheng, Jiashuo Wang, and Yefeng Zheng, indicating a consistent partnership network for producing research outputs.

The researcher has published across several prominent venues, with multiple contributions in arXiv (Cornell University), SSRN Electronic Journal, Proceedings of the AAAI Conference on Artificial Intelligence, ACM Transactions on Information Systems, and IEEE Transactions on Neural Networks and Learning Systems. This diversity of publication venues suggests a broad dissemination of their work in both pre-print and peer-reviewed contexts.

Some of their recent publications are as follows:

  • The Nexus between Environmental Corporate Social Responsibility, Green Intellectual Capital and Green Innovation towards Business Sustainability: An Empirical Analysis of Chinese Automobile Manufacturing Firms, 2023, International Journal of Environmental Research and Public Health
  • What and how driving consumer engagement and purchase intention in officer live streaming? A two-factor theory perspective, 2022, Electronic Commerce Research and Applications
  • Biodegradation and detoxification of neonicotinoid insecticide thiamethoxam by white-rot fungus Phanerochaete chrysosporium, 2021, Journal of Hazardous Materials
  • Query-Oriented Multi-Document Summarization via Unsupervised Deep Learning, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • DailyDialog: A Manually Labelled Multi-Turn Dialogue Dataset, 2025, TIB Data Manager

Best Publications

  • RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

    Hongwei Wang;Fuzheng Zhang;Jialin Wang;Miao Zhao

  • Knowledge Graph Convolutional Networks for Recommender Systems

    Hongwei Wang;Miao Zhao;Xing Xie;Wenjie Li

  • DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

    Yanran Li;Hui Su;Xiaoyu Shen;Wenjie Li

  • Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

    Hongwei Wang;Fuzheng Zhang;Mengdi Zhang;Jure Leskovec

  • Social Collaborative Filtering by Trust

    Bo Yang;Yu Lei;Jiming Liu;Wenjie Li

  • Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

    Hongwei Wang;Fuzheng Zhang;Miao Zhao;Wenjie Li

  • Mode regularized generative adversarial networks

    Tong Che;Yanran Li;Athul Paul Jacob;Athul Paul Jacob;Yoshua Bengio

  • Faithful to the Original: Fact Aware Neural Abstractive Summarization

    Ziqiang Cao;Furu Wei;Wenjie Li;Sujian Li

  • Extractive Summarization Using Supervised and Semi-Supervised Learning

    Kam-Fai Wong;Mingli Wu;Wenjie Li

  • Maximum-Likelihood Augmented Discrete Generative Adversarial Networks

    Tong Che;Yanran Li;Ruixiang Zhang;R Devon Hjelm

  • Applying regression models to query-focused multi-document summarization

    You Ouyang;Wenjie Li;Sujian Li;Qin Lu

  • Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization

    Ziqiang Cao;Wenjie Li;Sujian Li;Furu Wei

  • Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach

    Jingjing Xu;Xu Sun;Qi Zeng;Xiaodong Zhang

  • A novel neural topic model and its supervised extension

    Ziqiang Cao;Sujian Li;Yang Liu;Wenjie Li

  • Learning Summary Prior Representation for Extractive Summarization

    Ziqiang Cao;Furu Wei;Sujian Li;Wenjie Li

  • A Conditional Variational Framework for Dialog Generation

    Xiaoyu Shen;Hui Su;Yanran Li;Wenjie Li

  • Extractive Summarization using Inter- and Intra- Event Relevance

    Wenjie Li;Mingli Wu;Qin Lu;Wei Xu

  • Query-sensitive mutual reinforcement chain and its application in query-oriented multi-document summarization

    Furu Wei;Wenjie Li;Qin Lu;Yanxiang He

  • Component-Enhanced Chinese Character Embeddings

    Yanran Li;Wenjie Li;Fei Sun;Sujian Li

  • Exploring High-Order User Preference on the Knowledge Graph for Recommender Systems

    Hongwei Wang;Fuzheng Zhang;Jialin Wang;Miao Zhao

  • Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach

    Jingjing Xu;Xu Sun;Qi Zeng;Xuancheng Ren

  • Corpus Exploitation from Wikipedia for Ontology Construction

    Gaoying Cui;Qin Lu;Wenjie Li;Yi-Rong Chen

Frequent Co-Authors

Qin Lu
Qin Lu Hong Kong Polytechnic University
Kam-Fai Wong
Kam-Fai Wong Chinese University of Hong Kong
Sujian Li
Sujian Li Peking University
Furu Wei
Furu Wei Microsoft (United States)
Dawei Song
Dawei Song The Open University
Yu Lei
Yu Lei The University of Texas at Arlington
Xu Sun
Xu Sun Peking University
Ruifeng Xu
Ruifeng Xu Harbin Institute of Technology
Houfeng Wang
Houfeng Wang Peking University
Minyi Guo
Minyi Guo Shanghai Jiao Tong University

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