World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
9966
World Ranking
5625
National Ranking
171

Guandong Xu 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 Guandong Xu 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: 361 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Guandong Xu 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 Guandong Xu 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Guandong Xu is affiliated with the University of Technology Sydney in Australia and has contributed extensively to research in Computer Science, with a focus on Artificial Intelligence and Information Systems among other subfields. Their work spans multiple areas such as Computer Vision and Pattern Recognition, Signal Processing, and Sociology and Political Science.

Their recent publications demonstrate a broad engagement with contemporary topics in data and technology. Notable papers include:

  • Future smart cities: requirements, emerging technologies, applications, challenges, and future aspects (2022, Cities)
  • Deep learning for misinformation detection on online social networks: a survey and new perspectives (2020, Social Network Analysis and Mining)
  • Constructing dummy query sequences to protect location privacy and query privacy in location-based services (2020, World Wide Web)
  • Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media (2022, World Wide Web)
  • A Location Privacy-Preserving System Based on Query Range Cover-Up or Location-Based Services (2020, IEEE Transactions on Vehicular Technology)

Guandong Xu's research frequently addresses areas related to privacy preservation, advanced machine learning techniques, and intelligent data processing for social media and urban environments.

Their work includes collaborations with several frequent co-authors, among whom are:

  • Qian Li
  • Xianzhi Wang
  • Hongxu Chen
  • Imran Razzak
  • Qing Li

Publication venues where Guandong Xu has published recurrently reflect their research breadth and include:

  • arXiv (Cornell University)
  • World Wide Web
  • ACM Transactions on Information Systems
  • IEEE Transactions on Knowledge and Data Engineering
  • Neurocomputing

Guandong Xu also has contributions in academic book publishing, including at least one book titled Knowledge Management and Acquisition for Intelligent Systems published by Springer Science+Business Media in 2023.

The scientist's main fields of study encompass:

  • Computer Science

With subfields of study including:

  • Artificial Intelligence
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Sociology and Political Science

Core topics of research involve:

  • Recommender Systems and Techniques
  • Advanced Graph Neural Networks
  • Topic Modeling
  • Privacy-Preserving Technologies in Data
  • Sentiment Analysis and Opinion Mining
  • Software Engineering Research
  • Complex Network Analysis Techniques

Best Publications

  • Improving automatic source code summarization via deep reinforcement learning

    Yao Wan;Zhou Zhao;Min Yang;Guandong Xu

  • Sequential recommender system based on hierarchical attention network

    Haochao Ying;Fuzhen Zhuang;Fuzheng Zhang;Yanchi Liu

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

    Shuiguang Deng;Longtao Huang;Guandong Xu;Xindong Wu

  • Personalized recommendation via cross-domain triadic factorization

    Liang Hu;Jian Cao;Guandong Xu;Longbing Cao

  • Algorithms and Techniques

    Guandong Xu;Yanchun Zhang;Lin Li

  • Big data analytics for preventive medicine

    Muhammad Imran Razzak;Muhammad Imran;Guandong Xu

  • Deep learning for misinformation detection on online social networks: a survey and new perspectives

    Rafiqul Islam;Shaowu Liu;Xianzhi Wang;Guandong Xu

  • Social network-based service recommendation with trust enhancement

    Shuiguang Deng;Shuiguang Deng;Longtao Huang;Longtao Huang;Guandong Xu

  • Online IS Education for the 21st Century

    Wu He;Guandong Xu;S. E. Kruck

  • Efficient Brain Tumor Segmentation With Multiscale Two-Pathway-Group Conventional Neural Networks

    Muhammad Imran Razzak;Muhammad Imran;Guandong Xu

  • Web Mining and Social Networking: Techniques and Applications

    Guandong Xu;Yanchun Zhang;Lin Li

  • Constructing dummy query sequences to protect location privacy and query privacy in location-based services

    Zongda Wu;Guiling Li;Shigen Shen;Xinze Lian

  • Refining Parkinson’s neurological disorder identification through deep transfer learning

    Amina Naseer;Monail Rani;Saeeda Naz;Muhammad Imran Razzak

  • Multi-modal attention network learning for semantic source code retrieval

    Yao Wan;Jingdong Shu;Yulei Sui;Guandong Xu

  • Deep Learning for Decision Making and the Optimization of Socially Responsible Investments and Portfolio

    Nhi N.Y. Vo;Xuezhong He;Shaowu Liu;Guandong Xu

  • Fuzzy Cognitive Diagnosis for Modelling Examinee Performance

    Qi Liu;Runze Wu;Enhong Chen;Guandong Xu

  • Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017

    Jana Diesner;Elena Ferrari;Guandong Xu

  • A Boundary-aware Neural Model for Nested Named Entity Recognition

    Changmeng Zheng;Yi Cai;Jingyun Xu;Ho-fung Leung

  • Deep modeling of group preferences for group-based recommendation

    Liang Hu;Jian Cao;Guandong Xu;Longbing Cao

  • Diversifying personalized recommendation with user-session context

    Liang Hu;Longbing Cao;Shoujin Wang;Guandong Xu

Frequent Co-Authors

Yanchun Zhang
Yanchun Zhang Victoria University
Longbing Cao
Longbing Cao University of Technology Sydney
Enhong Chen
Enhong Chen University of Science and Technology of China
Peter Dolog
Peter Dolog Aalborg University
Shuiguang Deng
Shuiguang Deng Zhejiang University
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Xiaofang Zhou
Xiaofang Zhou Hong Kong University of Science and Technology
Masaru Kitsuregawa
Masaru Kitsuregawa University of Tokyo
Xun Yi
Xun Yi RMIT University
Alfredo Cuzzocrea
Alfredo Cuzzocrea University of Calabria

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