World's Best Scientists 2026 revealed!
Verónica Bolón-Canedo

Verónica Bolón-Canedo

D-Index & Metrics

Computer Science

D-Index
36
Citations
8054
World Ranking
11043
National Ranking
181

Verónica Bolón-Canedo 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 Verónica Bolón-Canedo 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: 148 publications — 26th percentile

26% of scientists in this discipline score the same or lower.

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

Verónica Bolón-Canedo 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 Verónica Bolón-Canedo 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Verónica Bolón-Canedo is affiliated with the University of A Coruña in Spain and focuses primarily on research in computer science. Their work spans a range of topics within this broad field, with a significant emphasis on artificial intelligence and machine learning.

The main areas of study and research include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Molecular Biology
  • Computer Networks and Communications

The scientist's research interests are reflected in their coverage of topics such as:

  • Machine Learning and Data Classification
  • Face and Expression Recognition
  • Neural Networks and Applications
  • Imbalanced Data Classification Techniques
  • Anomaly Detection Techniques and Applications
  • Sentiment Analysis and Opinion Mining
  • Domain Adaptation and Few-Shot Learning

Verónica Bolón-Canedo has published extensively, with a total of 88 publications categorized under computer science. The frequent venues for their work include:

  • SSRN Electronic Journal
  • Neurocomputing
  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • Pattern Recognition

Among recent papers authored or co-authored, the following stand out:

  • "A review of green artificial intelligence: Towards a more sustainable future" (2024, Neurocomputing)
  • "Spatial-temporal feature-based End-to-end Fourier network for 3D sign language recognition" (2024, Expert Systems with Applications)
  • "How important is data quality? Best classifiers vs best features" (2021, Neurocomputing)
  • "Do all roads lead to Rome? Studying distance measures in the context of machine learning" (2023, Pattern Recognition)
  • "Fast anomaly detection with locality-sensitive hashing and hyperparameter autotuning" (2022, Information Sciences)

Collaboration is an important aspect of Verónica Bolón-Canedo's work. The most frequent co-authors include:

  • Laura Morán-Fernández
  • Amparo Alonso-Betanzos
  • Beatriz Remeseiro
  • Eva Blanco-Mallo
  • Brais Cancela

Best Publications

  • A review of feature selection methods on synthetic data

    Verónica Bolón-Canedo;Noelia Sánchez-Maroño;Amparo Alonso-Betanzos

  • A review of feature selection methods in medical applications.

    Beatriz Remeseiro;Veronica Bolon-Canedo

  • A review of microarray datasets and applied feature selection methods

    V. Bolón-Canedo;N. Sánchez-Maroño;A. Alonso-Betanzos;J. M. Benítez

  • Ensembles for feature selection: A review and future trends

    Verónica Bolón-Canedo;Amparo Alonso-Betanzos

  • Feature selection for high-dimensional data

    Unknown

  • Recent advances and emerging challenges of feature selection in the context of big data

    V. Bolón-Canedo;N. Sánchez-Maroño;A. Alonso-Betanzos

  • Ensemble feature selection: Homogeneous and heterogeneous approaches

    Borja Seijo-Pardo;Iago Porto-Díaz;Verónica Bolón-Canedo;Amparo Alonso-Betanzos

  • Feature selection and classification in multiple class datasets

    V. Bolón-Canedo;N. Sánchez-Maroño;A. Alonso-Betanzos

  • An ensemble of filters and classifiers for microarray data classification

    V. BolóN-Canedo;N. SáNchez-MaroñO;A. Alonso-Betanzos

  • Distributed feature selection

    V. Bolón-Canedo;N. Sánchez-Maroño;A. Alonso-Betanzos

  • Fast-mRMR: Fast Minimum Redundancy Maximum Relevance Algorithm for High-Dimensional Big Data

    Sergio Ramírez-Gallego;Iago Lastra;David Martínez-Rego;Verónica Bolón-Canedo

  • Data discretization: taxonomy and big data challenge

    Sergio Ramírez-Gallego;Salvador García;Héctor Mouriño-Talín;David Martínez-Rego;David Martínez-Rego

  • Feature selection in image analysis: a survey

    Verónica Bolón-Canedo;Beatriz Remeseiro

  • Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the “i-ROP” System and Image Features Associated With Expert Diagnosis

    Esra Ataer-Cansizoglu;Veronica Bolon-Canedo;J. Peter Campbell;Alican Bozkurt

  • Expert Diagnosis of Plus Disease in Retinopathy of Prematurity From Computer-Based Image Analysis.

    J. Peter Campbell;Esra Ataer-Cansizoglu;Veronica Bolon-Canedo;Alican Bozkurt

  • An Information Theory-Based Feature Selection Framework for Big Data Under Apache Spark

    Sergio Ramirez-Gallego;Hector Mourino-Talin;David Martinez-Rego;Veronica Bolon-Canedo

  • Data classification using an ensemble of filters

    V. Bolón-Canedo;N. Sánchez-Maroño;A. Alonso-Betanzos

  • A framework for cost-based feature selection

    Verónica Bolón-Canedo;Iago Porto-Díaz;Noelia Sánchez-Maroño;Amparo Alonso-Betanzos

  • On developing an automatic threshold applied to feature selection ensembles

    Borja Seijo-Pardo;Verónica Bolón-Canedo;Amparo Alonso-Betanzos

  • Centralized vs. distributed feature selection methods based on data complexity measures

    L. Morán-Fernández;V. Bolón-Canedo;A. Alonso-Betanzos

  • On the use of feature selection to improve the detection of sea oil spills in SAR images

    David Mera;Veronica Bolon-Canedo;J.M. Cotos;Amparo Alonso-Betanzos

  • Big-Data Analysis, Cluster Analysis, and Machine-Learning Approaches.

    Amparo Alonso-Betanzos;Verónica Bolón-Canedo

Frequent Co-Authors

Amparo Alonso-Betanzos
Amparo Alonso-Betanzos University of A Coruña
Jayashree Kalpathy-Cramer
Jayashree Kalpathy-Cramer Harvard University
Deniz Erdogmus
Deniz Erdogmus Northeastern University
Francisco Herrera
Francisco Herrera University of Granada
José Manuel Benítez
José Manuel Benítez University of Granada
João Gama
João Gama University of Porto
Kristin P. Bennett
Kristin P. Bennett Rensselaer Polytechnic Institute
Isabelle Guyon
Isabelle Guyon University of Paris-Saclay
Jose C. Principe
Jose C. Principe University of Florida
Salvador García
Salvador García University of Granada

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