World's Best Scientists 2026 revealed!
Award Badge
Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
89
Citations
47671
World Ranking
633
National Ranking
90

Xindong Wu 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 Xindong Wu 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: 642 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Xindong Wu 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 Xindong Wu 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: 89 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2023 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award
  • 2012 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2011 - IEEE Fellow For contributions to artificial intelligence applications in power systems

Overview

Xindong Wu is affiliated with Hefei University of Technology in China. Their research spans a broad range of topics within computer science, particularly focusing on artificial intelligence, information systems, and computer vision and pattern recognition. This work is also connected to management science, operations research, and signal processing.

Their main research areas include advanced graph neural networks, topic modeling, recommender systems and techniques, data mining algorithms and applications, rough sets and fuzzy logic, text and document classification technologies, and natural language processing techniques.

Xindong Wu has contributed extensively to several publication venues, with the highest number of their works appearing in:

  • IEEE Transactions on Knowledge and Data Engineering
  • arXiv (Cornell University)
  • ACM Transactions on Knowledge Discovery from Data
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • Information Sciences

Examples of recent papers that feature their work include:

  • Unifying Large Language Models and Knowledge Graphs: A Roadmap (2024), published in IEEE Transactions on Knowledge and Data Engineering
  • Short Text Topic Modeling Techniques, Applications, and Performance: A Survey (2020), published in IEEE Transactions on Knowledge and Data Engineering
  • A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction (2020), published in IEEE Transactions on Knowledge and Data Engineering
  • A Comprehensive Survey on Automatic Knowledge Graph Construction (2023), published in ACM Computing Surveys
  • Causality-based Feature Selection (2020), published in ACM Computing Surveys

Frequent coauthors collaborating with Xindong Wu include Youxi Wu, Yan Li, Yi Zhu, Lei Li, and Chenyang Bu.

Their recognition includes the Fellow of the American Association for the Advancement of Science (AAAS) awarded in 2012, and IEEE Fellow status granted in 2011 for contributions to artificial intelligence applications in power systems.

Best Publications

  • Top 10 algorithms in data mining

    Xindong Wu;Vipin Kumar;J. Ross Quinlan;Joydeep Ghosh

  • Object Detection With Deep Learning: A Review

    Zhong-Qiu Zhao;Peng Zheng;Shou-Tao Xu;Xindong Wu

  • Data mining with big data

    Xindong Wu;Xingquan Zhu;Gong-Qing Wu;Wei Ding

  • General Tensor Discriminant Analysis and Gabor Features for Gait Recognition

    Dacheng Tao;Xuelong Li;Xindong Wu;S.J. Maybank

  • Class noise vs. attribute noise: a quantitative study of their impacts

    Xingquan Zhu;Xindong Wu

  • Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval

    Dacheng Tao;Xiaoou Tang;Xuelong Li;Xindong Wu

  • The Top Ten Algorithms in Data Mining

    Xindong Wu;Vipin Kumar

  • 10 CHALLENGING PROBLEMS IN DATA MINING RESEARCH

    Qiang Yang;Xindong Wu

  • Efficient mining of both positive and negative association rules

    Xindong Wu;Chengqi Zhang;Shichao Zhang

  • Geometric Mean for Subspace Selection

    Dacheng Tao;Xuelong Li;Xindong Wu;S.J. Maybank

  • Supervised tensor learning

    Dacheng Tao;Xuelong Li;Weiming Hu;S. Maybank

  • Visual-Textual Joint Relevance Learning for Tag-Based Social Image Search

    Yue Gao;Meng Wang;Zheng-Jun Zha;Jialie Shen

  • Multimodal Graph-Based Reranking for Web Image Search

    Meng Wang;Hao Li;Dacheng Tao;Ke Lu

  • Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection

    Xiaofeng Zhu;Xuelong Li;Shichao Zhang;Chunhua Ju

  • Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining

    Pavel Berkhin;Rich Caruana;Xindong Wu

  • On Deep Learning for Trust-Aware Recommendations in Social Networks

    Shuiguang Deng;Longtao Huang;Guandong Xu;Xindong Wu

  • Online Feature Selection with Streaming Features

    Xindong Wu;Kui Yu;Wei Ding;Hao Wang

  • Eliminating class noise in large datasets

    Xingquan Zhu;Xindong Wu;Qijun Chen

  • Proceedings of the 2001 IEEE International Conference on Data Mining

    Nick Cercone;Tsau Young Lin;Xindong Wu

  • Short Text Topic Modeling Techniques, Applications, and Performance: A Survey

    Jipeng Qiang;Zhenyu Qian;Yun Li;Yunhao Yuan

  • Synthesizing high-frequency rules from different data sources

    Xindong Wu;Shichao Zhang

Frequent Co-Authors

Xingquan Zhu
Xingquan Zhu Florida Atlantic University
Wei Ding
Wei Ding University of Massachusetts Boston
Chengqi Zhang
Chengqi Zhang Hong Kong Polytechnic University
Dacheng Tao
Dacheng Tao Nanyang Technological University
Meng Wang
Meng Wang Hefei University of Technology
Xuelong Li
Xuelong Li China Telecom (China)
Victor S. Sheng
Victor S. Sheng Texas Tech University
Stephen J. Maybank
Stephen J. Maybank Birkbeck, University of London
Jian Pei
Jian Pei Duke University
Xiaohua Hu
Xiaohua Hu Drexel 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

If you're interested in Computer Science but concerned about previous academic performance, consider exploring universities for low gpa. Many online colleges offer flexible admissions policies, making high-quality education more accessible.

For those looking to fast-track their studies, accelerated cs degree programs are available online. These programs are designed to help you complete your degree in less time, allowing you to enter the workforce more quickly.

Computer Science also pairs well with other fields, expanding your career opportunities. For example, with interests in sustainability or technology’s role in environmental stewardship, you might consider an environmental engineering degree online. Careers can range from environmental software designer to data analyst.

Wondering about job prospects with interdisciplinary skills? Explore what can you do with an environmental science major for ideas on how a science background combined with computer skills can open doors in research, policy, and technology-driven roles.

Best Scientists Citing Xindong Wu

Trending Scientists

Recently Published Articles