World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
29656
World Ranking
5997
National Ranking
362

Amos Storkey 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 Amos Storkey 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: 209 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Amos Storkey 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 Amos Storkey 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Amos Storkey is affiliated with the University of Edinburgh in the United Kingdom. Their research spans multiple fields, primarily focusing on Computer Science and Medicine. Within these broad disciplines, Storkey has significantly contributed to subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Ophthalmology, and Biomedical Engineering.

The scientist's work is oriented around several main topics, including Domain Adaptation and Few-Shot Learning, Retinal Imaging and Analysis, Advanced Neural Network Applications, Machine Learning and Data Classification, Retinal Diseases and Treatments, Adversarial Robustness in Machine Learning, and Multimodal Machine Learning Applications.

Storkey has published numerous papers, with some recent examples illustrating the diversity of their research interests. These include:

  • "Meta-Learning in Neural Networks: A Survey" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Obstructing Classification via Projection" (2021), published in Dagstuhl Research Online Publication Server
  • "Large-Scale Study of Curiosity-Driven Learning" (2025), published on arXiv (Cornell University)
  • "Accuracy of Automated Computer-Aided Diagnosis for Stroke Imaging: A Critical Evaluation of Current Evidence" (2022), published in Stroke
  • "Neural Architecture Search without Training" (2020), published on arXiv (Cornell University)

The publication venues where Storkey most frequently appears include arXiv (Cornell University), with 49 papers, alongside multiple contributions to the British Journal of Ophthalmology, IEEE Transactions on Pattern Analysis and Machine Intelligence, Dagstuhl Research Online Publication Server, and Stroke.

Collaboration is also a noticeable aspect of Storkey's research, with frequent co-authors including Justin Engelmann, Miguel O. Bernabéu, Joanna M. Wardlaw, Elliot J. Crowley, and Grant Mair, each having coauthored multiple papers with Storkey.

Best Publications

  • Advances in Neural Information Processing Systems 25

    Yichuan Zhang;Charles Sutton;Amos Storkey;Zoubin Ghahramani

  • Meta-Learning in Neural Networks: A Survey.

    Timothy M Hospedales;Antreas Antoniou;Paul Micaelli;Amos J. Storkey

  • Data Augmentation Generative Adversarial Networks

    Antreas Antoniou;Amos J. Storkey;Harrison Edwards

  • Advances in Neural Information Processing Systems 19 (NIPS 2006)

    Enrico Simonotto;Heather Whalley;Stephen Lawrie;Lawrence Murray

  • Exploration by random network distillation

    Yuri Burda;Harrison Edwards;Amos J. Storkey;Oleg Klimov

  • The 2005 PASCAL visual object classes challenge

    Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

  • Probabilistic inference for solving discrete and continuous state Markov Decision Processes

    Marc Toussaint;Amos Storkey

  • Large-Scale Study of Curiosity-Driven Learning

    Yuri Burda;Harrison Edwards;Deepak Pathak;Amos J. Storkey

  • Censoring Representations with an Adversary

    Harrison Edwards;Amos Storkey

  • Three Factors Influencing Minima in SGD

    Stanislaw Jastrzebski;Zachary Kenton;Devansh Arpit;Nicolas Ballas

  • ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16

    Amos Storkey

  • Towards a Neural Statistician

    Harrison Edwards;Amos J. Storkey

  • How to train your MAML

    Antreas Antoniou;Harrison Edwards;Amos J. Storkey

  • Extracting Motion Primitives from Natural Handwriting Data

    Ben H. Williams;Marc Toussaint;Amos J. Storkey

  • When Training and Test Sets are Different: Characterising Learning Transfer

    Amos J Storkey

  • Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks

    Antreas Antoniou;Amos J. Storkey;Harrison Edwards

  • Neural Information Processing Systems (NIPS)

    Xiaocheng Shang;Zhanxing Zhu;Benedict Leimkuhler;Amos Storkey

  • Test–retest reliability of structural brain networks from diffusion MRI

    Colin R. Buchanan;Cyril R. Pernet;Krzysztof J. Gorgolewski;Amos J. Storkey

  • Training Deep Convolutional Neural Networks to Play Go

    Christopher Clark;Amos Storkey

  • CINIC-10 Is Not ImageNet or CIFAR-10

    Luke Nicholas Darlow;Elliot J. Crowley;Antreas Antoniou;Amos J. Storkey

  • Neural Architecture Search without Training

    Joseph Mellor;Jack Turner;Amos Storkey;Elliot J. Crowley

Frequent Co-Authors

Mark E. Bastin
Mark E. Bastin University of Edinburgh
Michael F. P. O'Boyle
Michael F. P. O'Boyle University of Edinburgh
Cyril Pernet
Cyril Pernet Copenhagen University Hospital
Krzysztof J. Gorgolewski
Krzysztof J. Gorgolewski Stanford University
Yoshua Bengio
Yoshua Bengio University of Montreal
Robert G. Mann
Robert G. Mann University of Edinburgh
Marc Toussaint
Marc Toussaint Technical University of Berlin
Nicolas Ballas
Nicolas Ballas Facebook (United States)
Nigel Hambly
Nigel Hambly University of Edinburgh
Stephen M. Lawrie
Stephen M. Lawrie University of Edinburgh

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