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Computer Science
USA
2026

D-Index & Metrics

Best Female Scientists

D-Index
140
Citations
265476
World Ranking
233
National Ranking
146

Computer Science

D-Index
139
Citations
236605
World Ranking
67
National Ranking
39

Li Fei-Fei 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 Li Fei-Fei 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: 409 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Li Fei-Fei 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 Li Fei-Fei 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: 139 D-Index — 100th percentile

100% 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 United States Leader Award
  • 2025 - Research.com Best Female Scientists Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award

Overview

Li Fei-Fei is affiliated with Stanford University in the United States, specializing in the field of computer science. Their research contributions encompass a broad range of topics within this domain, with a particular focus on artificial intelligence and computer vision.

The scientist's main fields of study include:

  • Computer Science

Within this primary domain, their subfields of study are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Computer Networks and Communications
  • Mechanical Engineering

Their research addresses several topics, notable among these are:

  • Multimodal Machine Learning Applications
  • Robot Manipulation and Learning
  • Reinforcement Learning in Robotics
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Topic Modeling
  • Adversarial Robustness in Machine Learning

Li Fei-Fei has authored numerous scientific papers, with recent works including:

  • "On the Opportunities and Risks of Foundation Models," 2021, arXiv (Cornell University)
  • "Advances, challenges and opportunities in creating data for trustworthy AI," 2022, Nature Machine Intelligence
  • "Illuminating the dark spaces of healthcare with ambient intelligence," 2020, Nature
  • "U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation," 2024, arXiv (Cornell University)
  • "Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Frequent coauthors working with Li Fei-Fei include:

  • Ehsan Adeli
  • Silvio Savarese
  • Roberto Martín-Martín
  • Jiajun Wu
  • Chengshu Li

Regarding publication venues, their contributions are most often found in:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Nature Machine Intelligence
  • Medical Physics
  • SSRN Electronic Journal

Best Publications

  • ImageNet: A large-scale hierarchical image database

    Jia Deng;Wei Dong;Richard Socher;Li-Jia Li

  • ImageNet Large Scale Visual Recognition Challenge

    Olga Russakovsky;Jia Deng;Hao Su;Jonathan Krause

  • Perceptual Losses for Real-Time Style Transfer and Super-Resolution

    Justin Johnson;Alexandre Alahi;Li Fei-Fei

  • Large-Scale Video Classification with Convolutional Neural Networks

    Andrej Karpathy;George Toderici;Sanketh Shetty;Thomas Leung

  • Deep visual-semantic alignments for generating image descriptions

    Andrej Karpathy;Li Fei-Fei

  • Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

    Ranjay Krishna;Yuke Zhu;Oliver Groth;Justin Johnson

  • A Bayesian hierarchical model for learning natural scene categories

    L. Fei-Fei;P. Perona

  • Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories

    Li Fei-Fei;R. Fergus;P. Perona

  • Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories

    Li Fei-Fei;Rob Fergus;Pietro Perona

  • 3D Object Representations for Fine-Grained Categorization

    Jonathan Krause;Michael Stark;Jia Deng;Li Fei-Fei

  • Social LSTM: Human Trajectory Prediction in Crowded Spaces

    Alexandre Alahi;Kratarth Goel;Vignesh Ramanathan;Alexandre Robicquet

  • One-shot learning of object categories

    Li Fei-Fei;R. Fergus;P. Perona

  • Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words

    Juan Carlos Niebles;Hongcheng Wang;Li Fei-Fei

  • On the Opportunities and Risks of Foundation Models.

    Rishi Bommasani;Drew A. Hudson;Ehsan Adeli;Russ Altman

  • Large-scale Video Classification with Convolutional Neural Networks

    Andrej Karpathy;George Toderici;Sanketh Shetty;Thomas Leung

  • Progressive Neural Architecture Search

    Chenxi Liu;Barret Zoph;Maxim Neumann;Jonathon Shlens

  • Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

    Agrim Gupta;Justin Johnson;Li Fei-Fei;Silvio Savarese

  • CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

    Justin Johnson;Bharath Hariharan;Laurens van der Maaten;Li Fei-Fei

  • Target-driven visual navigation in indoor scenes using deep reinforcement learning

    Yuke Zhu;Roozbeh Mottaghi;Eric Kolve;Joseph J. Lim

  • DenseCap: Fully Convolutional Localization Networks for Dense Captioning

    Justin Johnson;Andrej Karpathy;Li Fei-Fei

  • ImageNet Large Scale Visual Recognition Challenge

    Olga Russakovsky;Jia Deng;Hao Su;Jonathan Krause

Frequent Co-Authors

Yuke Zhu
Yuke Zhu The University of Texas at Austin
Diane M. Beck
Diane M. Beck University of Illinois at Urbana-Champaign
Li-Jia Li
Li-Jia Li Stanford University
Alexandre Alahi
Alexandre Alahi École Polytechnique Fédérale de Lausanne
Jia Deng
Jia Deng Princeton University
Animesh Garg
Animesh Garg University of Toronto
Juan Carlos Niebles
Juan Carlos Niebles Stanford University
Michael S. Bernstein
Michael S. Bernstein Stanford University
Silvio Savarese
Silvio Savarese Stanford University
Arnold Milstein
Arnold Milstein Stanford University

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