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D-Index & Metrics

Computer Science

D-Index
77
Citations
184969
World Ranking
1225
National Ranking
648

Demis Hassabis 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 Demis Hassabis 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: 124 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Demis Hassabis 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 Demis Hassabis 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: 77 D-Index — 91st percentile

91% 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

  • 2018 - Fellow of the Royal Society, United Kingdom
  • 2017 - Fellow of the Royal Academy of Engineering (UK)

Overview

Demis Hassabis is affiliated with Google in the United States and has a research focus concentrated primarily within Computer Science and Biochemistry, Genetics and Molecular Biology. Their scholarly output encompasses significant contributions to the fields of Artificial Intelligence and Molecular Biology, among various other interdisciplinary domains.

Their research spans several subfields of study, including:

  • Artificial Intelligence
  • Molecular Biology
  • Materials Chemistry
  • Economics and Econometrics
  • Cognitive Neuroscience

Within these domains, Hassabis has engaged extensively with topics such as:

  • Protein Structure and Dynamics
  • Sports Analytics and Performance
  • Artificial Intelligence in Games
  • Machine Learning in Bioinformatics
  • Enzyme Structure and Function
  • Reinforcement Learning in Robotics
  • Topic Modeling

Frequent co-authors collaborating with Hassabis include Pushmeet Kohli, John Jumper, Andrew Senior, Nenad Tomašev, and Tim Green, reflecting teamwork in varied research efforts.

Hassabis's work has appeared across several notable publication venues, with multiple papers featured in:

  • arXiv (Cornell University)
  • Nature
  • Zenodo (CERN European Organization for Nuclear Research)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Science

Among recent significant papers are the following:

  • Highly accurate protein structure prediction with AlphaFold, 2021, Nature
  • Accurate structure prediction of biomolecular interactions with AlphaFold 3, 2024, Nature
  • AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models, 2021, Nucleic Acids Research
  • Protein complex prediction with AlphaFold-Multimer, 2021, bioRxiv (Cold Spring Harbor Laboratory)
  • Improved protein structure prediction using potentials from deep learning, 2020, Nature

Hassabis has received recognition including fellowships from distinguished bodies:

  • Fellow of the Royal Society, United Kingdom, 2018
  • Fellow of the Royal Academy of Engineering (UK), 2017

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

  • Mastering the game of Go without human knowledge

    David Silver;Julian Schrittwieser;Karen Simonyan;Ioannis Antonoglou

  • AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

    Mihaly Varadi;Stephen Anyango;Mandar Deshpande;Sreenath Nair

  • Overcoming catastrophic forgetting in neural networks

    James Kirkpatrick;Razvan Pascanu;Neil C. Rabinowitz;Joel Veness

  • A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.

    David Silver;Thomas Hubert;Julian Schrittwieser;Ioannis Antonoglou

  • Protein complex prediction with AlphaFold-Multimer

    Richard Evans;Michael O'Neill;Alexander Pritzel;Natasha Antropova

  • 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

  • International evaluation of an AI system for breast cancer screening.

    Scott Mayer McKinney;Marcin Sieniek;Varun Godbole;Jonathan Godwin

  • Highly accurate protein structure prediction for the human proteome

    Kathryn Tunyasuvunakool;Jonas Adler;Zachary Wu;Tim Green

  • Clinically applicable deep learning for diagnosis and referral in retinal disease

    Jeffrey De Fauw;Joseph R. Ledsam;Bernardino Romera-Paredes;Stanislav Nikolov

  • Mastering Atari, Go, chess and shogi by planning with a learned model

    Julian Schrittwieser;Ioannis Antonoglou;Thomas Hubert;Karen Simonyan

  • Hybrid computing using a neural network with dynamic external memory

    Alex Graves;Greg Wayne;Malcolm Reynolds;Tim Harley

  • Neuroscience-Inspired Artificial Intelligence.

    Demis Hassabis;Dharshan Kumaran;Christopher Summerfield;Matthew Botvinick

  • The Future of Memory: Remembering, Imagining, and the Brain

    Daniel L. Schacter;Donna Rose Addis;Demis Hassabis;Victoria C. Martin

  • Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

    David Silver;Thomas Hubert;Julian Schrittwieser;Ioannis Antonoglou

  • Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

    Unknown

  • Using Imagination to Understand the Neural Basis of Episodic Memory

    Demis Hassabis;Dharshan Kumaran;Eleanor A. Maguire

  • Human-level performance in 3D multiplayer games with population-based reinforcement learning

    Max Jaderberg;Wojciech M. Czarnecki;Iain Dunning;Luke Marris

Frequent Co-Authors

Dharshan Kumaran
Dharshan Kumaran Google (United States)
Eleanor A. Maguire
Eleanor A. Maguire University College London
Matthew Botvinick
Matthew Botvinick Yale University
Koray Kavukcuoglu
Koray Kavukcuoglu DeepMind (United Kingdom)
David Silver
David Silver DeepMind (United Kingdom)
Charles Blundell
Charles Blundell DeepMind (United Kingdom)
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
Oriol Vinyals
Oriol Vinyals DeepMind (United Kingdom)
Timothy P. Lillicrap
Timothy P. Lillicrap University College London
Joel Z. Leibo
Joel Z. Leibo DeepMind (United Kingdom)

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