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Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
73
Citations
198172
World Ranking
1530
National Ranking
86

Koray Kavukcuoglu 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 Koray Kavukcuoglu 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: 96 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Koray Kavukcuoglu 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 Koray Kavukcuoglu 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: 73 D-Index — 89th percentile

89% 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 Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award

Overview

Koray Kavukcuoglu is a researcher affiliated with DeepMind in the United Kingdom. Their work spans several interdisciplinary fields, primarily focusing on computer science and biochemistry, genetics, and molecular biology. Their research integrates artificial intelligence techniques with biological sciences, particularly in protein structure and dynamics.

The scientist's main fields of study include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology

Within these fields, their research covers several subfields such as:

  • Artificial Intelligence
  • Molecular Biology
  • Materials Chemistry
  • Nuclear and High Energy Physics
  • Information Systems

Their primary research topics involve:

  • Protein Structure and Dynamics
  • Topic Modeling
  • Natural Language Processing Techniques
  • Machine Learning in Bioinformatics
  • Enzyme Structure and Function
  • Machine Learning and Data Classification
  • Plant biochemistry and biosynthesis

Koray Kavukcuoglu has authored several influential papers that have appeared in prominent publication venues. Notable recent papers include:

  • Highly accurate protein structure prediction with AlphaFold, 2021, Nature
  • Bootstrap your own latent: A new approach to self-supervised Learning, 2020, arXiv (Cornell University)
  • Improved protein structure prediction using potentials from deep learning, 2020, Nature
  • Highly accurate protein structure prediction for the human proteome, 2021, Nature
  • Magnetic control of tokamak plasmas through deep reinforcement learning, 2022, Nature

The frequent publication venues for their work are:

  • arXiv (Cornell University)
  • Nature
  • Proteins Structure Function and Bioinformatics
  • Science

The scientific collaborations of Koray Kavukcuoglu have included several notable co-authors, reflecting the interdisciplinary and collaborative nature of their research. Frequent co-authors are:

  • Demis Hassabis
  • Oriol Vinyals
  • Pushmeet Kohli
  • Laurent Sifre
  • John Jumper

Best Publications

  • Highly accurate protein structure prediction with AlphaFold

    John M. Jumper;Richard O. Evans;Alexander Pritzel;Tim Green

  • Human-level control through deep reinforcement learning

    Volodymyr Mnih;Koray Kavukcuoglu;David Silver;Andrei A. Rusu

  • Mastering the game of Go with deep neural networks and tree search

    David Silver;Aja Huang;Christopher J. Maddison;Arthur Guez

  • Natural Language Processing (Almost) from Scratch

    Ronan Collobert;Jason Weston;Léon Bottou;Michael Karlen

  • Playing Atari with Deep Reinforcement Learning

    Volodymyr Mnih;Koray Kavukcuoglu;David Silver;Alex Graves

  • Asynchronous methods for deep reinforcement learning

    Volodymyr Mnih;Adrià Puigdomènech Badia;Mehdi Mirza;Alex Graves

  • Spatial transformer networks

    Max Jaderberg;Karen Simonyan;Andrew Zisserman;Koray Kavukcuoglu

  • Matching networks for one shot learning

    Oriol Vinyals;Charles Blundell;Timothy Lillicrap;Koray Kavukcuoglu

  • WaveNet: A Generative Model for Raw Audio

    Aäron van den Oord;Sander Dieleman;Heiga Zen;Karen Simonyan

  • Neural Discrete Representation Learning

    Aaron van den Oord;Oriol Vinyals;koray kavukcuoglu

  • Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

    Jean-Bastien Grill;Florian Strub;Florent Altché;Corentin Tallec

  • Grandmaster level in StarCraft II using multi-agent reinforcement learning.

    Oriol Vinyals;Igor Babuschkin;Wojciech M. Czarnecki;Michaël Mathieu

  • Improved protein structure prediction using potentials from deep learning

    Andrew W. Senior;Richard Evans;John Jumper;James Kirkpatrick

  • Recurrent Models of Visual Attention

    Volodymyr Mnih;Nicolas Heess;Alex Graves;koray kavukcuoglu

  • Highly accurate protein structure prediction for the human proteome

    Kathryn Tunyasuvunakool;Jonas Adler;Zachary Wu;Tim Green

  • What is the best multi-stage architecture for object recognition?

    Kevin Jarrett;Koray Kavukcuoglu;Marc'Aurelio Ranzato;Yann LeCun

  • Convolutional networks and applications in vision

    Yann LeCun;Koray Kavukcuoglu;Clement Farabet

  • Weight Uncertainty in Neural Network

    Charles Blundell;Julien Cornebise;Koray Kavukcuoglu;Daan Wierstra

  • Conditional image generation with PixelCNN decoders

    Aäron van den Oord;Nal Kalchbrenner;Oriol Vinyals;Lasse Espeholt

  • Torch7: A Matlab-like Environment for Machine Learning

    Ronan Collobert;Koray Kavukcuoglu;Clément Farabet

  • Weight Uncertainty in Neural Networks

    Charles Blundell;Julien Cornebise;Koray Kavukcuoglu;Daan Wierstra

Frequent Co-Authors

Karen Simonyan
Karen Simonyan DeepMind (United Kingdom)
Volodymyr Mnih
Volodymyr Mnih DeepMind (United Kingdom)
Alex Graves
Alex Graves Google (United States)
Oriol Vinyals
Oriol Vinyals DeepMind (United Kingdom)
David Silver
David Silver DeepMind (United Kingdom)
Aaron van den Oord
Aaron van den Oord Google (United States)
Nal Kalchbrenner
Nal Kalchbrenner Google (United States)
Yann LeCun
Yann LeCun Facebook (United States)
Demis Hassabis
Demis Hassabis Google (United States)
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA

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