World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
6346
World Ranking
11566
National Ranking
726

Jaume Bacardit 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 Jaume Bacardit 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: 136 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Jaume Bacardit 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 Jaume Bacardit 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Jaume Bacardit is affiliated with Newcastle University in the United Kingdom and has contributed extensively to the field of Medicine, with a particular focus on Rheumatology, Molecular Biology, Artificial Intelligence, Surgery, and Pharmacology.

Their research explores multiple topics, including:

  • Osteoarthritis Treatment and Mechanisms
  • Rheumatoid Arthritis Research and Therapies
  • Inflammatory mediators and NSAID effects
  • Animal Behavior and Welfare Studies
  • Meat and Animal Product Quality
  • Total Knee Arthroplasty Outcomes
  • Stock Market Forecasting Methods

Jaume Bacardit has published articles in a range of scientific venues. Frequent publication outlets include:

  • Osteoarthritis and Cartilage
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Annals of the Rheumatic Diseases
  • Scientific Reports
  • arXiv (Cornell University)

Some notable recent papers authored or co-authored by Jaume Bacardit are:

  • Single-cell multi-omics analysis of the immune response in COVID-19, 2021, Nature Medicine
  • Developmental cell programs are co-opted in inflammatory skin disease, 2021, Science
  • Blood and immune development in human fetal bone marrow and Down syndrome, 2021, Nature
  • Osteoarthritis endotype discovery via clustering of biochemical marker data, 2022, Annals of the Rheumatic Diseases
  • Automated recognition of postures and drinking behaviour for the detection of compromised health in pigs, 2020, Scientific Reports

The scientist has collaborated frequently with several researchers including:

  • M. Kloppenburg
  • I.K. Haugen
  • Francisco J. Blanco
  • Francis Bérenbaum
  • Anne-Christine Bay-Jensen

Best Publications

  • KEEL: a software tool to assess evolutionary algorithms for data mining problems

    J. Alcalá-Fdez;L. Sánchez;S. García;M. J. del Jesus

  • Decoding human fetal liver haematopoiesis

    Dorin-Mirel Popescu;Rachel A. Botting;Emily Stephenson;Kile Green

  • Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

    Anna Louise Swan;Ali Mobasheri;David Allaway;Susan Liddell

  • MRPR: A MapReduce solution for prototype reduction in big data classification

    Isaac Triguero;Daniel Peralta;Jaume Bacardit;Salvador García

  • The eukaryotic N-end rule pathway: conserved mechanisms and diverse functions

    Daniel J. Gibbs;Jaume Bacardit;Andreas Bachmair;Michael J. Holdsworth

  • Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data

    Enrico Glaab;Jaume Bacardit;Jonathan M. Garibaldi;Natalio Krasnogor

  • ROSEFW-RF

    Isaac Triguero;Sara del Río;Victoria López;Jaume Bacardit

  • Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets

    George W. Bassel;Enrico Glaab;Julietta Marquez;Michael J. Holdsworth

  • Improving the scalability of rule-based evolutionary learning

    Jaume Bacardit;Edmund K. Burke;Natalio Krasnogor

  • Data mining in learning classifier systems: comparing XCS with GAssist

    Jaume Bacardit;Martin V. Butz

  • Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning

    Jake Cowton;Ilias Kyriazakis;Jaume Bacardit

  • Data Mining in Learning Classifier Systems: Comparing XCS with GAssist.

    Jaume Bacardit;Martin V. Butz

  • Bloat control and generalization pressure using the minimum description length principle for a pittsburgh approach learning classifier system

    Jaume Bacardit;Josep Maria Garrell

  • Large-scale data mining using genetics-based machine learning

    Jaume Bacardit;Xavier Llorí

  • WeFold: a coopetition for protein structure prediction.

    George A. Khoury;Adam Liwo;Firas Khatib;Firas Khatib;Hongyi Zhou

  • A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women

    N. Lazzarini;J. Runhaar;A. C. Bay-Jensen;C. S. Thudium

  • Automated recognition of postures and drinking behaviour for the detection of compromised health in pigs

    Ali Alameer;Ilias Kyriazakis;Jaume Bacardit

  • Automatic recognition of feeding and foraging behaviour in pigs using deep learning

    Ali Alameer;Ilias Kyriazakis;Hillary A. Dalton;Amy L. Miller

  • Evolving multiple discretizations with adaptive intervals for a Pittsburgh rule-based learning classifier system

    Jaume Bacardit;Josep Maria Garrell

  • Automated Alphabet Reduction for Protein Datasets

    Jaume Bacardit;Michael Stout;Jonathan D. Hirst;Alfonso Valencia

  • Bloat Control and Generalization Pressure Using the Minimum Description Length Principle for a Pittsburgh Approach Learning Classifier System.

    Jaume Bacardit;Josep Maria Garrell i Guiu

  • GECCO ’14: Proceedings of the 2014 conference on Genetic and evolutionary computation

    C Igel;DV Arnold;C Gagne;E Popovici

Frequent Co-Authors

Natalio Krasnogor
Natalio Krasnogor Newcastle University
Ali Mobasheri
Ali Mobasheri University of Oulu
Muzlifah Haniffa
Muzlifah Haniffa Newcastle University
Sarah A. Teichmann
Sarah A. Teichmann University of Cambridge
Harrie Weinans
Harrie Weinans Utrecht University
Sam Behjati
Sam Behjati Wellcome Sanger Institute
Martin V. Butz
Martin V. Butz University of Tübingen
Jonathan D. Hirst
Jonathan D. Hirst University of Nottingham
John Loughlin
John Loughlin Newcastle University
Aviv Regev
Aviv Regev Genentech

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