World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
12331
World Ranking
3283
National Ranking
440

Huamin Qu 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 Huamin Qu 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+

This scientist: 250 publications — 62nd percentile

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

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

Huamin Qu 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 Huamin Qu 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+

This scientist: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Huamin Qu is affiliated with the Hong Kong University of Science and Technology in China. Their research primarily focuses on computer science, with extensive work in the areas of computer vision and pattern recognition, artificial intelligence, sociology and political science, human-computer interaction, and computer science applications.

Their work encompasses several subfields including:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Sociology and Political Science
  • Human-Computer Interaction
  • Computer Science Applications

Huamin Qu's principal topics of research cover data visualization and analytics, video analysis and summarization, data analysis with R, explainable artificial intelligence (XAI), advanced text analysis techniques, topic modeling, and online learning and analytics.

  • Data Visualization and Analytics
  • Video Analysis and Summarization
  • Data Analysis with R
  • Explainable Artificial Intelligence (XAI)
  • Advanced Text Analysis Techniques
  • Topic Modeling
  • Online Learning and Analytics

Frequently collaborating with other researchers, Huamin Qu has coauthored multiple papers with Yong Wang, Haotian Li, Aoyu Wu, Xingbo Wang, and Wai Tong.

  • Yong Wang
  • Haotian Li
  • Aoyu Wu
  • Xingbo Wang
  • Wai Tong

The scientist's publications appear regularly in venues such as arXiv (Cornell University), IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Proceedings of the ACM on Human-Computer Interaction, and the CHI Conference on Human Factors in Computing Systems.

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • Computer Graphics Forum
  • Proceedings of the ACM on Human-Computer Interaction
  • CHI Conference on Human Factors in Computing Systems

Recent papers include the following:

  • AI4VIS: Survey on Artificial Intelligence Approaches for Data Visualization, 2021, IEEE Transactions on Visualization and Computer Graphics
  • DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models, 2020, IEEE Transactions on Visualization and Computer Graphics
  • A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization, 2021, IEEE Transactions on Visualization and Computer Graphics
  • M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis, 2022, arXiv (Cornell University)
  • EmotionCues: Emotion-Oriented Visual Summarization of Classroom Videos, 2020, IEEE Transactions on Visualization and Computer Graphics

Best Publications

  • TextFlow: Towards Better Understanding of Evolving Topics in Text

    Weiwei Cui;Shixia Liu;Li Tan;Conglei Shi

  • Geometry-Based Edge Clustering for Graph Visualization

    Weiwei Cui;Hong Zhou;Huamin Qu;Pak Chung Wong

  • Context preserving dynamic word cloud visualization

    Weiwei Cui;Yingcai Wu;Shixia Liu;Furu Wei

  • Context-Preserving, Dynamic Word Cloud Visualization

    Weiwei Cui;Yingcai Wu;Shixia Liu;Furu Wei

  • Visual clustering in parallel coordinates

    Hong Zhou;Xiaoru Yuan;Huamin Qu;Weiwei Cui

  • RuleMatrix: Visualizing and Understanding Classifiers with Rules

    Yao Ming;Huamin Qu;Enrico Bertini

  • OpinionSeer: Interactive Visualization of Hotel Customer Feedback

    Yingcai Wu;Furu Wei;Shixia Liu;Norman Au

  • Whisper: Tracing the Spatiotemporal Process of Information Diffusion in Real Time

    Nan Cao;Yu-Ru Lin;Xiaohua Sun;D. Lazer

  • Big-Data Visualization

    Daniel Keim;Huamin Qu;Kwan-Liu Ma

  • Understanding Hidden Memories of Recurrent Neural Networks

    Yao Ming;Shaozu Cao;Ruixiang Zhang;Zhen Li

  • Scattering Points in Parallel Coordinates

    Xiaoru Yuan;Peihong Guo;He Xiao;Hong Zhou

  • FacetAtlas: Multifaceted Visualization for Rich Text Corpora

    Nan Cao;Jimeng Sun;Yu-Ru Lin;D Gotz

  • SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations

    Dongyu Liu;Di Weng;Yuhong Li;Jie Bao

  • DICON: Interactive Visual Analysis of Multidimensional Clusters

    Nan Cao;D. Gotz;J. Sun;Huamin Qu

  • A Multiscale and Hierarchical Feature Extraction Method for Terrestrial Laser Scanning Point Cloud Classification

    Zhen Wang;Liqiang Zhang;Tian Fang;P. Takis Mathiopoulos

  • Visualizing Mobility of Public Transportation System

    Wei Zeng;Chi-Wing Fu;Stefan Mueller Arisona;Alexander Erath

  • Visual Analysis of Topic Competition on Social Media

    Panpan Xu;Yingcai Wu;Enxun Wei;Tai-Quan Peng

  • Edge bundling in information visualization

    Hong Zhou;Panpan Xu;Xiaoru Yuan;Huamin Qu

  • VisMOOC: Visualizing video clickstream data from Massive Open Online Courses

    Conglei Shi;Siwei Fu;Qing Chen;Huamin Qu

  • AI4VIS: Survey on Artificial Intelligence Approaches for Data Visualization.

    Aoyu Wu;Yun Wang;Xinhuan Shu;Dominik Moritz

  • Visual Analysis of the Air Pollution Problem in Hong Kong

    Huamin Qu;Wing-Yi Chan;Anbang Xu;Kai-Lun Chung

Frequent Co-Authors

Yingcai Wu
Yingcai Wu Zhejiang University
Lionel M. Ni
Lionel M. Ni Hong Kong University of Science and Technology (Guangzhou)
Shixia Liu
Shixia Liu Tsinghua University
Nan Cao
Nan Cao Tongji University
Qiong Luo
Qiong Luo Hong Kong University of Science and Technology
Arie E. Kaufman
Arie E. Kaufman Stony Brook University
Chi-Wing Fu
Chi-Wing Fu Chinese University of Hong Kong
Bongshin Lee
Bongshin Lee Microsoft (United States)
Min Chen
Min Chen South China University of Technology
Yangqiu Song
Yangqiu Song Hong Kong University of Science and Technology

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