World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
5199
World Ranking
12136
National Ranking
769

Adam Prügel-Bennett 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 Adam Prügel-Bennett 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: 150 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Adam Prügel-Bennett 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 Adam Prügel-Bennett 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: 34 D-Index — 16th percentile

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

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

Overview

Adam Prügel-Bennett is affiliated with the University of Southampton in the United Kingdom. Their research spans predominantly within Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Ocean Engineering, and Oceanography.

The scientist has published extensively across various venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • ePrints Soton (University of Southampton)
  • Journal of Field Robotics
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Robotics and Automation Letters

Notable recent papers illustrate a concentration on advanced machine learning approaches applied to imagery and robotics, particularly in underwater environments. Selected papers include:

  • "FMix: Enhancing Mixed Sample Data Augmentation" (2020) published in arXiv (Cornell University)
  • "Learning features from georeferenced seafloor imagery with location guided autoencoders" (2020) published in Journal of Field Robotics
  • "Guiding Labelling Effort for Efficient Learning With Georeferenced Images" (2022) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Leveraging Metadata in Representation Learning With Georeferenced Seafloor Imagery" (2021) published in IEEE Robotics and Automation Letters
  • "GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation" (2022) published in Field Robotics

The main topics underpinning their work encompass a range of areas from machine learning methods to underwater technology and image analysis. These topics include:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Industrial Vision Systems and Defect Detection
  • Generative Adversarial Networks and Image Synthesis
  • Underwater Vehicles and Communication Systems
  • Underwater Acoustics Research
  • Advanced Image and Video Retrieval Techniques

The scientist collaborates frequently with several co-authors. Most common collaborators are:

  • Xiaohao Cai
  • Jonathon Hare
  • Halil Ibrahim Aysel
  • Ruixiao Zhang
  • Takaki Yamada

Best Publications

  • SVM Parameter Optimization using Grid Search and Genetic Algorithm to Improve Classification Performance

    Iwan Syarif;Adam Prugel-Bennett;Gary Wills

  • Analysis of genetic algorithms using statistical mechanics.

    Adam Prügel-Bennett;Jonathan L. Shapiro

  • Novel centroid selection approaches for KMeans-clustering based recommender systems

    Sobia Zahra;Mustansar Ali Ghazanfar;Asra Khalid;Muhammad Awais Azam

  • Unsupervised Clustering Approach for Network Anomaly Detection

    Iwan Syarif;Adam Prugel-Bennett;Gary B. Wills

  • Automatic gait recognition using area-based metrics

    Jeff P. Foster;Mark S. Nixon;Adam Prügel-Bennett

  • A Scalable, Accurate Hybrid Recommender System

    Mustansar Ali Ghazanfar;Adam Prugel-Bennett

  • Learning to count objects in natural images for visual question answering

    Yan Zhang;Jonathon S. Hare;Adam Prügel-Bennett

  • Analysis of synfire chains

    M Herrmann;J A Hertz;A Prügel-Bennett

  • Genetic drift in genetic algorithm selection schemes

    A. Rogers;A. Prugel-Bennett

  • Application of bagging, boosting and stacking to intrusion detection

    Iwan Syarif;Ed Zaluska;Adam Prugel-Bennett;Gary Wills

  • Leveraging clustering approaches to solve the gray-sheep users problem in recommender systems

    Mustansar Ali Ghazanfar;Adam Prügel-Bennett

  • The dynamics of a genetic algorithm for simple random Ising systems

    Adam Prügel-Bennett;Jonathan L. Shapiro

  • FMix: Enhancing Mixed Sample Data Augmentation

    Ethan Harris;Antonia Marcu;Matthew Painter;Mahesan Niranjan

  • Benefits of a Population: Five Mechanisms That Advantage Population-Based Algorithms

    Adam Prügel-Bennett

  • Modelling the Dynamics of a Steady State Genetic Algorithm

    Alex Rogers;Adam Prügel-Bennett

  • An Improved Switching Hybrid Recommender System Using Naive Bayes Classifier and Collaborative Filtering

    Mustansar Ali Ghazanfar;Adam Prugel-Bennett

  • Modelling Evolving Populations

    Adam Prügel-Bennett

  • When a genetic algorithm outperforms hill-climbing

    Adam Prügel-Bennett

  • Training HMM structure with genetic algorithm for biological sequence analysis

    Kyoung-Jae Won;Adam Prügel-Bennett;Anders Krogh

  • On the Landscape of Combinatorial Optimization Problems

    Mohammad-H. Tayarani-N.;Adam Prugel-Bennett

  • A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms

    Jonathan Shapiro;Adam Prügel-Bennett;Magnus Rattray

Frequent Co-Authors

Mark S. Nixon
Mark S. Nixon University of Southampton
Alex Rogers
Alex Rogers University of Oxford
Anders Krogh
Anders Krogh University of Copenhagen
Gary Wills
Gary Wills University of Southampton
Jonathan W. Essex
Jonathan W. Essex University of Southampton
mc schraefel
mc schraefel University of Southampton
Magnus Rattray
Magnus Rattray University of Manchester
Nicholas R. Jennings
Nicholas R. Jennings Loughborough University
Nigel Shadbolt
Nigel Shadbolt University of Oxford
Stefan B. Williams
Stefan B. Williams University of Sydney

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