World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
75
Citations
31743
World Ranking
1382
National Ranking
187

Hanqing Lu 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 Hanqing Lu 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: 634 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.

Hanqing Lu 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 Hanqing Lu 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: 75 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Overview

Hanqing Lu is affiliated with the Chinese Academy of Sciences in China and primarily works within the fields of Computer Science and Engineering. Their research has a notable focus on Computer Vision and Pattern Recognition, including subfields such as Artificial Intelligence and Cognitive Neuroscience.

The scientist's work covers a range of topics, prominently featuring:

  • Video Surveillance and Tracking Methods
  • Face and Expression Recognition
  • Functional Brain Connectivity Studies
  • Gait Recognition and Analysis
  • Advanced Computing and Algorithms
  • Advanced Neuroimaging Techniques and Applications
  • Advanced Image and Video Retrieval Techniques

Hanqing Lu has published several papers in various scientific venues. Notable recent papers include:

  • Pyramid Spatial-Temporal Aggregation for Video-based Person Re-Identification, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Multi-kernel fuzzy clustering based on auto-encoder for fMRI functional network, 2020, Expert Systems with Applications
  • Multi-atlas classification of autism spectrum disorder with hinge loss trained deep architectures: ABIDE I results, 2021, Applied Soft Computing
  • Edge-AI-Driven Framework with Efficient Mobile Network Design for Facial Expression Recognition, 2023, ACM Transactions on Embedded Computing Systems
  • Improved deep convolutional embedded clustering with re-selectable sample training, 2022, Pattern Recognition

Frequent publication venues for Hanqing Lu include:

  • Pattern Recognition
  • Expert Systems with Applications
  • Multimedia Systems
  • Multimedia Tools and Applications
  • arXiv (Cornell University)

Several co-authors have collaborated extensively with Hanqing Lu, including:

  • Xia Geng
  • Shaohua Wan
  • Hui Wei
  • Juanjuan Tu
  • Xuecheng Hua

Best Publications

  • Dual Attention Network for Scene Segmentation

    Jun Fu;Jing Liu;Haijie Tian;Yong Li

  • Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

    Lei Shi;Yifan Zhang;Jian Cheng;Hanqing Lu

  • Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks

    Lei Shi;Yifan Zhang;Jian Cheng;Hanqing Lu

  • Skeleton-Based Action Recognition With Shift Graph Convolutional Network

    Ke Cheng;Yifan Zhang;Xiangyu He;Weihan Chen

  • Skeleton-Based Action Recognition With Directed Graph Neural Networks

    Lei Shi;Yifan Zhang;Jian Cheng;Hanqing Lu

  • Unsupervised feature selection using nonnegative spectral analysis

    Zechao Li;Yi Yang;Jing Liu;Xiaofang Zhou

  • Face detection using improved LBP under Bayesian framework

    Hongliang Jin;Qingshan Liu;Hanqing Lu;Xiaofeng Tong

  • A nonlinear approach for face sketch synthesis and recognition

    Qingshan Liu;Xiaoou Tang;Hongliang Jin;Hanqing Lu

  • Solving the small sample size problem of LDA

    Rui Huang;Qingshan Liu;Hanqing Lu;Songde Ma

  • Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set

    Si Liu;Zheng Song;Guangcan Liu;Changsheng Xu

  • Street-to-shop: cross-scenario clothing retrieval via parts alignment and auxiliary set

    Si Liu;Zheng Song;Meng Wang;Changsheng Xu

  • Robust Structured Subspace Learning for Data Representation

    Zechao Li;Jing Liu;Jinhui Tang;Hanqing Lu

  • EgoGesture: A New Dataset and Benchmark for Egocentric Hand Gesture Recognition

    Yifan Zhang;Congqi Cao;Jian Cheng;Hanqing Lu

  • Clustering-Guided Sparse Structural Learning for Unsupervised Feature Selection

    Zechao Li;Jing Liu;Yi Yang;Xiaofang Zhou

  • Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition

    Ke Cheng;Yifan Zhang;Congqi Cao;Lei Shi

  • Hi, magic closet, tell me what to wear!

    Si Liu;Jiashi Feng;Zheng Song;Tianzhu Zhang

  • A Real-Time Hand Gesture Recognition Method

    Yikai Fang;Kongqiao Wang;Jian Cheng;Hanqing Lu

  • CoupleNet: Coupling Global Structure with Local Parts for Object Detection

    Yousong Zhu;Chaoyang Zhao;Jinqiao Wang;Xu Zhao

  • Improving kernel Fisher discriminant analysis for face recognition

    Qingshan Liu;Hanqing Lu;Songde Ma

  • Image annotation via graph learning

    Jing Liu;Mingjing Li;Qingshan Liu;Hanqing Lu

Frequent Co-Authors

Jinqiao Wang
Jinqiao Wang Chinese Academy of Sciences
Jing Liu
Jing Liu Chinese Academy of Sciences
Jian Cheng
Jian Cheng Chinese Academy of Sciences
Qingshan Liu
Qingshan Liu Nanjing University of Information Science and Technology
Changsheng Xu
Changsheng Xu Chinese Academy of Sciences
Zechao Li
Zechao Li Nanjing University of Science and Technology
Ling-Yu Duan
Ling-Yu Duan Peking University
Qi Tian
Qi Tian Huawei Technologies (China)
Si Liu
Si Liu Beihang University
Tianzhu Zhang
Tianzhu Zhang University of Science and Technology of China

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