World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
9877
World Ranking
6784
National Ranking
409

David C. Hogg 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 David C. Hogg 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: 188 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

David C. Hogg 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 David C. Hogg 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

David C. Hogg is affiliated with the University of Leeds in the United Kingdom. Their research spans multiple intersecting disciplines, primarily focusing on the fields of Computer Science and Medicine. Within these main fields, they have contributed extensively to Artificial Intelligence, Cardiology and Cardiovascular Medicine, and Computer Vision and Pattern Recognition, among other subfields.

Their research portfolio covers a range of topics, notably including:

  • Atrial Fibrillation Management and Outcomes
  • Adversarial Robustness in Machine Learning
  • Speech and Dialogue Systems
  • Semantic Web and Ontologies
  • Acute Ischemic Stroke Management
  • Acute Myocardial Infarction Research
  • Stroke Rehabilitation and Recovery

David C. Hogg's publication record includes research articles in various journals and venues. Some recent publications are:

  • Prediction of short-term atrial fibrillation risk using primary care electronic health records, 2023, published in Heart
  • The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer's disease and estimate 5-year risks of cognitive decline and dementia, 2022, BMC Neurology
  • Moving towards intelligent telemedicine: Computer vision measurement of human movement, 2022, Computers in Biology and Medicine
  • Predicting patient-level new-onset atrial fibrillation from population-based nationwide electronic health records: protocol of FIND-AF for developing a precision medicine prediction model using artificial intelligence, 2021, BMJ Open
  • Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery, 2023, The Cryosphere

The scientist collaborates frequently with several co-authors, including Ramesh Nadarajah, Jianhua Wu, Chris P Gale, Andrew J. Bulpitt, and Yoko M. Nakao. Their work is often published in venues such as arXiv (Cornell University), Heart, The Cryosphere, Open Heart, and BMC Neurology.

David C. Hogg's interdisciplinary work leverages artificial intelligence and computer vision techniques in medical applications, contributing to advancements in prediction models, telemedicine, and disease monitoring.

Best Publications

  • Model-based vision: a program to see a walking person

    David C. Hogg

  • Learning the distribution of object trajectories for event recognition

    Neil Johnson;David Hogg

  • British Machine Vision Conference (BMVC)

    Dima Damen;David Hogg

  • Learning flexible models from image sequences

    Adam Baumberg;David Hogg

  • Towards 3D hand tracking using a deformable model

    T. Heap;D. Hogg

  • An efficient method for contour tracking using active shape models

    A.M. Baumberg;D.C. Hogg

  • Learning Variable-Length Markov Models of Behavior

    Aphrodite Galata;Neil Johnson;David Hogg

  • Computer Vision and Pattern Recognition (CVPR)

    Dima Damen;David Hogg

  • Detecting Carried Objects in Short Video Sequences

    Dima Damen;David Hogg

  • Automated reconstruction of 3D models from real environments

    V. Sequeira;K. Ng;E. Wolfart;J.G.M. Gonçalves

  • The STRANDS Project: Long-Term Autonomy in Everyday Environments

    Nick Hawes;Christopher Burbridge;Ferdian Jovan;Lars Kunze

  • Wormholes in shape space: tracking through discontinuous changes in shape

    T. Heap;D. Hogg

  • Deeper Networks for Pavement Crack Detection

    Leo Pauly;Harriet Peel;Shan Luo;David Hogg

  • Detecting inexplicable behaviour

    Hannah M. Dee;David C. Hogg

  • Constructing qualitative event models automatically from video input

    Jonathan H. Fernyhough;Anthony G. Cohn;David C. Hogg

  • An integrated traffic and pedestrian model-based vision system

    Paolo Remagnino;Adam Baumberg;T. Grove;David C. Hogg

  • Statistical Models of Object Interaction

    R. J. Morris;D. C. Hogg

  • Improving Specificity in PDMs using a Hierarchical Approach.

    Tony Heap;David C. Hogg

  • Personalizing Human Video Pose Estimation

    James Charles;Tomas Pfister;Derek Magee;David Hogg

  • The acquisition and use of interaction behaviour models

    N. Johnson;A. Galata;D. Hogg

  • Automated 3D reconstruction of interiors with multiple scan views

    Vitor Sequeira;Kia C. Ng;Erik Wolfart;Joao G. M. Goncalves

  • Recognizing linked events: Searching the space of feasible explanations

    Dima Damen;David Hogg

Frequent Co-Authors

Anthony G. Cohn
Anthony G. Cohn University of Leeds
Dima Damen
Dima Damen University of Bristol
Iain D. Gilchrist
Iain D. Gilchrist University of Bristol
David C. Mason
David C. Mason University of Reading
Andrew Zisserman
Andrew Zisserman University of Oxford
Tomas Pfister
Tomas Pfister Google (United States)
Paolo Remagnino
Paolo Remagnino Durham University
Patric Jensfelt
Patric Jensfelt Royal Institute of Technology
Tom Duckett
Tom Duckett University of Lincoln
David J. Young
David J. Young University of New South Wales

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