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

D-Index & Metrics

Computer Science

D-Index
122
Citations
69596
World Ranking
137
National Ranking
17

Stan Z. Li 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 Stan Z. Li 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: 613 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.

Stan Z. Li 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 Stan Z. Li 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: 122 D-Index — 99th percentile

99% 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
  • 2009 - IEEE Fellow For contributions to face recognition, pattern recognition and computer vision

Overview

Stan Z. Li is affiliated with Westlake University in China and has a research background spanning computer science and biochemistry, genetics, and molecular biology. Their scholarly work encompasses a blend of theoretical and applied topics, notably at the intersection of artificial intelligence and molecular biology.

Their research output includes a substantial number of publications, reflecting contributions to both foundational computational methods and domain-specific applications. Key recent papers include:

  • "A Survey on Generative Diffusion Models" (2024) published in IEEE Transactions on Knowledge and Data Engineering
  • "Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study" (2020) published in IEEE Transactions on Image Processing
  • "SimVP: Simpler yet Better Video Prediction" (2022) presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation" (2022) presented in the Proceedings of the ACM Web Conference 2022
  • "Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive" (2021) published in IEEE Transactions on Knowledge and Data Engineering

Their collaborative work often involves frequent co-authors such as Zhangyang Gao, Zelin Zang, Lirong Wu, and Cheng Tan. These collaborations reflect sustained scholarly relationships across multiple projects and studies.

Stan Z. Li's work has been disseminated through various prominent publication venues, notable among these are:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • Briefings in Bioinformatics

They have also contributed to books published by Morgan & Claypool Publishers, including titles such as "Multi-Modal Face Presentation Attack Detection" (2020) and "Advances in Face Presentation Attack Detection" (2023).

Their expertise spans several subfields within computer science and biology, including:

  • Molecular Biology
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Signal Processing

Within their research topics, the scientist has extensively addressed areas such as:

  • Machine Learning in Bioinformatics
  • Advanced Graph Neural Networks
  • Protein Structure and Dynamics
  • Face recognition and analysis
  • Domain Adaptation and Few-Shot Learning
  • Computational Drug Discovery Methods
  • Biometric Identification and Security

Stan Z. Li has been recognized as an IEEE Fellow since 2009 for contributions to face recognition, pattern recognition, and computer vision.

Best Publications

  • Handbook of Face Recognition

    Stan Z. Li;Anil K. Jain

  • Markov Random Field Modeling in Image Analysis

    Stan Z. Li

  • Markov random field models in computer vision

    Stan Z. Li

  • Person re-identification by Local Maximal Occurrence representation and metric learning

    Shengcai Liao;Yang Hu;Xiangyu Zhu;Stan Z. Li

  • Learning Face Representation from Scratch

    Dong Yi;Zhen Lei;Shengcai Liao;Stan Z. Li

  • Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection

    Shifeng Zhang;Cheng Chi;Yongqiang Yao;Zhen Lei

  • Markov Random Field Modeling in Computer Vision

    S. Z. Li

  • Single-Shot Refinement Neural Network for Object Detection

    Shifeng Zhang;Longyin Wen;Xiao Bian;Zhen Lei

  • Deep Metric Learning for Person Re-identification

    Dong Yi;Zhen Lei;Shengcai Liao;Stan Z. Li

  • Face Alignment Across Large Poses: A 3D Solution

    Xiangyu Zhu;Zhen Lei;Xiaoming Liu;Hailin Shi

  • Learning spatially localized, parts-based representation

    S.Z. Li;Xin Wen Hou;Hong Jiang Zhang;Qian Sheng Cheng

  • A face antispoofing database with diverse attacks

    Zhiwei Zhang;Junjie Yan;Sifei Liu;Zhen Lei

  • Face recognition by support vector machines

    Guodong Guo;S.Z. Li;Kapluk Chan

  • Learning multi-scale block local binary patterns for face recognition

    Shengcai Liao;Xiangxin Zhu;Zhen Lei;Lun Zhang

  • Illumination Invariant Face Recognition Using Near-Infrared Images

    S.Z. Li;RuFeng Chu;ShengCai Liao;Lun Zhang

  • Facial expression recognition from near-infrared videos

    Guoying Zhao;Xiaohua Huang;Matti Taini;Stan Z. Li

  • FloatBoost learning and statistical face detection

    S.Z. Li;Zhenqiu Zhang

  • Face recognition using the nearest feature line method

    S.Z. Li;Juwei Lu

  • Content-based audio classification and retrieval by support vector machines

    Guodong Guo;S.Z. Li

  • S^3FD: Single Shot Scale-Invariant Face Detector

    Shifeng Zhang;Xiangyu Zhu;Zhen Lei;Hailin Shi

  • Face Alignment in Full Pose Range: A 3D Total Solution

    Xiangyu Zhu;Xiaoming Liu;Zhen Lei;Stan Z. Li

Frequent Co-Authors

Zhen Lei
Zhen Lei Chinese Academy of Sciences
Shengcai Liao
Shengcai Liao United Arab Emirates University
Dong Yi
Dong Yi Winsense Co., Ltd.
Shifeng Zhang
Shifeng Zhang Beijing Forestry University
Junjie Yan
Junjie Yan SenseTime
Longyin Wen
Longyin Wen ByteDance
Guodong Guo
Guodong Guo West Virginia University
Ran He
Ran He Chinese Academy of Sciences
Sergio Escalera
Sergio Escalera University of Barcelona

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

Online degrees in Computer Science offer incredible flexibility and accessibility for students around the world. Those concerned about tuition costs can explore cheap online colleges that offer high-quality programs without breaking the bank.

If your academic record isn’t perfect, don’t worry—there are excellent universities for low gpa that understand students take different paths to reach their goals.

Beyond traditional tech careers, a Computer Science degree can intersect with diverse fields. For example, careers in environmental technology are growing. If you’re curious about interdisciplinary possibilities, check out the range of opportunities described in what jobs can you get with an environmental science degree.

Want to join the workforce sooner? Consider enrolling in one of the fastest computer science degree options, allowing you to complete your studies at an accelerated pace and launch your tech career quickly.

Best Scientists Citing Stan Z. Li

Trending Scientists

Recently Published Articles