World's Best Scientists 2026 revealed!
María José del Jesus

María José del Jesus

D-Index & Metrics

Computer Science

D-Index
42
Citations
10143
World Ranking
8239
National Ranking
114

María José del Jesus 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 María José del Jesus 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: 156 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

María José del Jesus 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 María José del Jesus 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

María José del Jesus is affiliated with the University of Jaén in Spain and has contributed extensively to the field of computer science, with a total of 47 publications primarily focused on artificial intelligence and its intersections with other subfields.

Their research covers several subfields including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Information Systems
  • Plant Science

Key topics in their body of work include:

  • Data Stream Mining Techniques
  • Anomaly Detection Techniques and Applications
  • Time Series Analysis and Forecasting
  • Data Mining Algorithms and Applications
  • Generative Adversarial Networks and Image Synthesis
  • Smart Agriculture and AI
  • Domain Adaptation and Few-Shot Learning

María José del Jesus has multiple recent papers that reflect the diversity of their research interests. Notable publications include:

  • "An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges" (2020, Neurocomputing)
  • "Analysis of clustering methods for crop type mapping using satellite imagery" (2022, Neurocomputing)
  • "EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search" (2020, Integrated Computer-Aided Engineering)
  • "FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams" (2020, IEEE Transactions on Fuzzy Systems)
  • "ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders" (2021, Information Sciences)

Their frequent coauthors include:

  • Antonio J. Rivera
  • Francisco Charte
  • María Dolores Pérez-Godoy
  • David Elizondo
  • C. J. Carmona

In terms of publication venues, María José del Jesus often publishes in:

  • Neurocomputing
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Information Fusion
  • Integrated Computer-Aided Engineering

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

  • A proposal on reasoning methods in fuzzy rule-based classification systems

    Oscar Cordón;María José del Jesus;Francisco Herrera

  • Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches

    Alberto FernáNdez;Victoria LóPez;Mikel Galar;MaríA José Del Jesus

  • A practical tutorial on autoencoders for nonlinear feature fusion: taxonomy, models, software and guidelines

    David Charte;Francisco Charte;Salvador García;María José del Jesus

  • An overview on subgroup discovery: foundations and applications

    Franciso Herrera;Cristóbal José Carmona;Pedro González;María José del Jesus

  • A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets

    Alberto Fernández;Salvador García;María José del Jesus;Francisco Herrera

  • Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction

    J. Casillas;O. Cordon;M.J. del Jesus;F. Herrera

  • Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks

    Alberto Fernández;Sara del Río;Victoria López;Abdullah Bawakid

  • Addressing imbalance in multilabel classification: Measures and random resampling algorithms

    Francisco Charte;Antonio J. Rivera;María José del Jesus;Francisco Herrera;Francisco Herrera

  • KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

    Isaac Triguero;Sergio González;Jose M. Moyano;Salvador García

  • MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

    Francisco Charte;Antonio J. Rivera;María José del Jesus;Francisco Herrera;Francisco Herrera

  • Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets

    Alberto Fernández;María José del Jesus;Francisco Herrera

  • Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?

    Alberto Fernandez;Francisco Herrera;Oscar Cordon;Maria Jose del Jesus

  • Web usage mining to improve the design of an e-commerce website: OrOliveSur.com

    C. J. Carmona;S. Ramírez-Gallego;F. Torres;E. Bernal

  • Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems

    J. Casillas;O. Cordón;M. J. Del Jesus;F. Herrera

  • Induction of fuzzy-rule-based classifiers with evolutionary boosting algorithms

    M.J. del Jesus;F. Hoffmann;L.J. Navascues;L. Sanchez

  • Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges

    Alberto Fernández;Victoria López;María José del Jesus;Francisco Herrera;Francisco Herrera

  • Genetic Learning of Fuzzy Rule-Based Classification Systems Cooperating with Fuzzy Reasoning Methods

    Oscar Cordón;María José del Jesus;Francisco Herrera

  • MOGUL: A Methodology to Obtain Genetic Fuzzy Rule-Based Systems under the Iterative Rule Learning Approach*

    O. Cordón;M. J. del Jesus;F. Herrera;M. Lozano

  • Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data

    C. Romero;P. González;S. Ventura;M. J. del Jesus

Frequent Co-Authors

Francisco Herrera
Francisco Herrera University of Granada
Alberto Fernández
Alberto Fernández University of Granada
Oscar Cordón
Oscar Cordón University of Granada
Salvador García
Salvador García University of Granada
Julián Luengo
Julián Luengo University of Granada
José Manuel Benítez
José Manuel Benítez University of Granada
Sebastián Ventura
Sebastián Ventura University of Córdoba
Mykola Pechenizkiy
Mykola Pechenizkiy Eindhoven University of Technology
Francesco Marcelloni
Francesco Marcelloni University of Pisa
Manuel Lozano
Manuel Lozano University of Granada

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