World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
19964
World Ranking
3012
National Ranking
407

Shenghua Gao 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 Shenghua Gao 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: 161 publications — 31st percentile

31% of scientists in this discipline score the same or lower.

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

Shenghua Gao 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 Shenghua Gao 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: 61 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Shenghua Gao is affiliated with ShanghaiTech University in China, with a research focus primarily in the field of Computer Science. Their work spans several subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Computer Graphics and Computer-Aided Design, and Molecular Biology.

The scientist has contributed substantially to topics such as Human Pose and Action Recognition, Advanced Vision and Imaging, Anomaly Detection Techniques and Applications, Video Surveillance and Tracking Methods, 3D Shape Modeling and Analysis, Domain Adaptation and Few-Shot Learning, and Advanced Neural Network Applications.

Shenghua Gao's recent papers include:

  • "Appearance-Motion Memory Consistency Network for Video Anomaly Detection," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "DeepPROTACs is a deep learning-based targeted degradation predictor for PROTACs," 2022, Nature Communications
  • "Future Frame Prediction Network for Video Anomaly Detection," 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "AS-MLP: An Axial Shifted MLP Architecture for Vision," 2021, arXiv (Cornell University)
  • "Normal graph: Spatial temporal graph convolutional networks based prediction network for skeleton based video anomaly detection," 2020, Neurocomputing

The frequent co-authors who have collaborated with Shenghua Gao include Weixin Luo, Dongze Lian, Wen Liu, Yanyu Xu, and Kang Zhou.

Regarding publication venues, Shenghua Gao has frequently published in arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the AAAI Conference on Artificial Intelligence, Neurocomputing, and the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Best Publications

  • CE-Net: Context Encoder Network for 2D Medical Image Segmentation

    Zaiwang Gu;Jun Cheng;Huazhu Fu;Kang Zhou

  • PCANet: A Simple Deep Learning Baseline for Image Classification?

    Tsung-Han Chan;Kui Jia;Shenghua Gao;Jiwen Lu

  • Single-Image Crowd Counting via Multi-Column Convolutional Neural Network

    Yingying Zhang;Desen Zhou;Siqin Chen;Shenghua Gao

  • Future Frame Prediction for Anomaly Detection - A New Baseline

    Wen Liu;Weixin Luo;Dongze Lian;Shenghua Gao

  • A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework

    Weixin Luo;Wen Liu;Shenghua Gao

  • Local features are not lonely – Laplacian sparse coding for image classification

    Shenghua Gao;Ivor Wai-Hung Tsang;Liang-Tien Chia;Peilin Zhao

  • Remembering history with convolutional LSTM for anomaly detection

    Weixin Luo;Wen Liu;Shenghua Gao

  • Kernel sparse representation for image classification and face recognition

    Shenghua Gao;Ivor Wai-Hung Tsang;Liang-Tien Chia

  • Laplacian Sparse Coding, Hypergraph Laplacian Sparse Coding, and Applications

    Shenghua Gao;Ivor Wai-Hung Tsang;Liang-Tien Chia

  • Region-Based Saliency Detection and Its Application in Object Recognition

    Zhixiang Ren;Shenghua Gao;Liang-Tien Chia;Ivor Wai-Hung Tsang

  • Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis

    Wen Liu;Zhixin Piao;Jie Min;Wenhan Luo

  • Encoding Crowd Interaction with Deep Neural Network for Pedestrian Trajectory Prediction

    Yanyu Xu;Zhixin Piao;Shenghua Gao

  • Gaze Prediction in Dynamic 360° Immersive Videos

    Yanyu Xu;Yanbing Dong;Junru Wu;Zhengzhong Sun

  • Face Aging with Identity-Preserved Conditional Generative Adversarial Networks

    Xu Tang;Zongwei Wang;Weixin Luo;Shenghua Gao

  • Single Sample Face Recognition via Learning Deep Supervised Autoencoders

    S. Gao;Y. Zhang;K. Jia;J. Lu

  • Sparse Representation With Kernels

    Shenghua Gao;I. W. Tsang;Liang-Tien Chia

  • Structured3D: A Large Photo-Realistic Dataset for Structured 3D Modeling

    Jia Zheng;Junfei Zhang;Jing Li;Rui Tang

  • Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement

    Zehao Yu;Shenghua Gao

  • Video Anomaly Detection with Sparse Coding Inspired Deep Neural Networks

    Weixin Luo;Wen Liu;Dongze Lian;Jinhui Tang

  • Learning to Parse Wireframes in Images of Man-Made Environments

    Kun Huang;Yifan Wang;Zihan Zhou;Tianjiao Ding

  • Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization

    Shenghua Gao;Ivor Wai-Hung Tsang;Yi Ma

  • Density Map Regression Guided Detection Network for RGB-D Crowd Counting and Localization

    Dongze Lian;Jing Li;Jia Zheng;Weixin Luo

Frequent Co-Authors

Jiang Liu
Jiang Liu Southern University of Science and Technology
Jun Cheng
Jun Cheng University of Chinese Academy of Sciences
Liang-Tien Chia
Liang-Tien Chia Nanyang Technological University
Yi Ma
Yi Ma University of Hong Kong
Jingyi Yu
Jingyi Yu ShanghaiTech University
Ivor W. Tsang
Ivor W. Tsang Agency for Science, Technology and Research
Yitian Zhao
Yitian Zhao Chinese Academy of Sciences
Huazhu Fu
Huazhu Fu Agency for Science, Technology and Research
Kui Jia
Kui Jia South China University of Technology
Jinhui Tang
Jinhui Tang Nanjing University of Science and Technology

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

Pursuing Computer Science in the USA opens doors to a broad array of online degrees and career opportunities. Many students opt for the fastest computer science degree programs, which allow quicker entry into the workforce through accelerated online coursework.

Those interested in applying their tech skills to environmental solutions may explore related fields. For instance, understanding what can you do with an environmental science major can reveal interdisciplinary paths that blend computer science expertise with environmental impact.

Engineering disciplines are also increasingly accessible online. If sustainability is your goal, an environmental engineering bachelor's degree online offers a high-demand alternative. For those aiming for advanced roles in technology and design, the cheapest online master's mechanical engineering programs combine flexibility and affordability.

Each of these degrees provides valuable skills that can lead to rewarding, future-ready careers in diverse, high-growth sectors.

Best Scientists Citing Shenghua Gao

Trending Scientists

Recently Published Articles