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Computer Science

D-Index
56
Citations
57654
World Ranking
3927
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1863

Alexey Dosovitskiy 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 Alexey Dosovitskiy 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: 70 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

Alexey Dosovitskiy 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 Alexey Dosovitskiy 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: 56 D-Index — 72nd percentile

72% 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

  • 2025 - Research.com Rising Stars Award

Overview

Alexey Dosovitskiy is affiliated with Google in the United States and has contributed extensively to the field of computer science, particularly in computer vision and pattern recognition. Their research spans several subfields including artificial intelligence, computer graphics and computer-aided design, environmental engineering, and aerospace engineering.

The scientist's work focuses on a range of main topics including:

  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Advanced Vision and Imaging
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Computer Graphics and Visualization Techniques
  • Generative Adversarial Networks and Image Synthesis

Alexey Dosovitskiy has a strong publication record with papers frequently appearing in venues such as:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Robotics and Automation Letters

Key recent papers include:

  • An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, 2020, arXiv (Cornell University)
  • MLP-Mixer: An all-MLP Architecture for Vision, 2021, arXiv (Cornell University)
  • Object-Centric Learning with Slot Attention, 2020, arXiv (Cornell University)
  • Do Vision Transformers See Like Convolutional Neural Networks?, 2021, arXiv (Cornell University)
  • Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Throughout their career, Dosovitskiy has collaborated frequently with several co-authors, including:

  • Thomas Kipf (6 collaborations)
  • Klaus Greff (5 collaborations)
  • Jakob Uszkoreit (5 collaborations)
  • Dirk Weissenborn (4 collaborations)
  • Aravindh Mahendran (4 collaborations)

Best Publications

  • An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

    Alexey Dosovitskiy;Lucas Beyer;Alexander Kolesnikov;Dirk Weissenborn

  • FlowNet: Learning Optical Flow with Convolutional Networks

    Alexey Dosovitskiy;Philipp Fischery;Eddy Ilg;Philip Hausser

  • Striving for Simplicity: The All Convolutional Net

    Jost Tobias Springenberg;Alexey Dosovitskiy;Thomas Brox;Martin A. Riedmiller

  • FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

    Eddy Ilg;Nikolaus Mayer;Tonmoy Saikia;Margret Keuper

  • A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

    Nikolaus Mayer;Eddy Ilg;Philip Hausser;Philipp Fischer

  • CARLA: An Open Urban Driving Simulator

    Alexey Dosovitskiy;Germán Ros;Felipe Codevilla;Antonio M. López

  • MLP-Mixer: An all-MLP Architecture for Vision

    Ilya Tolstikhin;Neil Houlsby;Alexander Kolesnikov;Lucas Beyer

  • Learning agile and dynamic motor skills for legged robots

    Jemin Hwangbo;Joonho Lee;Alexey Dosovitskiy;Dario Bellicoso

  • NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections

    Ricardo Martin-Brualla;Noha Radwan;Mehdi S. M. Sajjadi;Jonathan T. Barron

  • End-to-End Driving Via Conditional Imitation Learning

    Felipe Codevilla;Matthias Miiller;Antonio Lopez;Vladlen Koltun

  • FlowNet: Learning Optical Flow with Convolutional Networks

    Philipp Fischer;Alexey Dosovitskiy;Eddy Ilg;Philip Häusser

  • Discriminative Unsupervised Feature Learning with Convolutional Neural Networks

    Alexey Dosovitskiy;Jost Tobias Springenberg;Martin Riedmiller;Thomas Brox

  • Generating Images with Perceptual Similarity Metrics based on Deep Networks

    Alexey Dosovitskiy;Thomas Brox

  • Learning to generate chairs with convolutional neural networks

    Alexey Dosovitskiy;Jost Tobias Springenberg;Thomas Brox

  • Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs

    Maxim Tatarchenko;Alexey Dosovitskiy;Thomas Brox

  • Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks

    Alexey Dosovitskiy;Philipp Fischer;Jost Tobias Springenberg;Martin Riedmiller

  • Inverting Visual Representations with Convolutional Networks

    Alexey Dosovitskiy;Thomas Brox

  • DeMoN: Depth and Motion Network for Learning Monocular Stereo

    Benjamin Ummenhofer;Huizhong Zhou;Jonas Uhrig;Nikolaus Mayer

  • Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space

    Anh Nguyen;Jeff Clune;Yoshua Bengio;Alexey Dosovitskiy

  • On Evaluation of Embodied Navigation Agents

    Peter Anderson;Angel X. Chang;Devendra Singh Chaplot;Alexey Dosovitskiy

  • Object-Centric Learning with Slot Attention

    Francesco Locatello;Dirk Weissenborn;Thomas Unterthiner;Aravindh Mahendran

Frequent Co-Authors

Thomas Brox
Thomas Brox University of Freiburg
Vladlen Koltun
Vladlen Koltun Apple (United States)
Jost Tobias Springenberg
Jost Tobias Springenberg University of Freiburg
Rene Ranftl
Rene Ranftl Intel (United States)
Davide Scaramuzza
Davide Scaramuzza University of Zurich
Daniel Cremers
Daniel Cremers Technical University of Munich
Martin Riedmiller
Martin Riedmiller DeepMind (United Kingdom)
Antonio M. López
Antonio M. López Autonomous University of Barcelona

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