World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
18650
World Ranking
2728
National Ranking
25

Michel Verleysen 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 Michel Verleysen 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: 493 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Michel Verleysen 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 Michel Verleysen 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: 63 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2015 - IEEE Fellow For contributions to high-dimensional analysis and manifold learning

Overview

Michel Verleysen is affiliated with Université Catholique de Louvain in Belgium. Their research primarily falls within the field of Computer Science, with significant contributions to several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience, and Media Technology.

The main research topics covered by Michel Verleysen's work include:

  • Face and Expression Recognition
  • Neural Networks and Applications
  • Video Surveillance and Tracking Methods
  • Advanced Clustering Algorithms Research
  • Blind Source Separation Techniques
  • EEG and Brain-Computer Interfaces
  • Data Visualization and Analytics

Michel Verleysen has been published frequently in venues such as:

  • arXiv (Cornell University)
  • Neurocomputing
  • ESANN 2021 proceedings
  • SSRN Electronic Journal
  • PLoS ONE

Notable recent papers include:

  • "Dynamics of the perception and EEG signals triggered by tonic warm and cool stimulation" (2020) published in PLoS ONE
  • "LASSO multi-objective learning algorithm for feature selection" (2020) published in Soft Computing
  • "Semi-supervised t-SNE with multi-scale neighborhood preservation" (2023) published in Neurocomputing
  • "Fast Multiscale Neighbor Embedding" (2020) published in IEEE Transactions on Neural Networks and Learning Systems
  • "The Flow of Trust: A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications" (2023) published in IEEE Computer Graphics and Applications

Frequent collaborators in their research include:

  • Cyril de Bodt
  • John A. Lee
  • Pierre Lambert
  • Edouard Couplet
  • Dounia Mulders

Michel Verleysen was recognized as an IEEE Fellow in 2015 for contributions to high-dimensional analysis and manifold learning.

Best Publications

  • Unique in the Crowd: The privacy bounds of human mobility

    Yves Alexandre De Montjoye;Yves Alexandre De Montjoye;César A. Hidalgo;César A. Hidalgo;César A. Hidalgo;Michel Verleysen;Vincent D. Blondel;Vincent D. Blondel

  • Nonlinear Dimensionality Reduction

    John A. Lee;Michel Verleysen

  • Classification in the Presence of Label Noise: A Survey

    Benoit Frenay;Michel Verleysen

  • The curse of dimensionality in data mining and time series prediction

    Michel Verleysen;Damien François

  • Nonlinear dimensionality reduction

    Michel Verleysen;John Aldo Lee

  • The Concentration of Fractional Distances

    Damien Francois;Vincent Wertz;Michel Verleysen

  • Quality assessment of dimensionality reduction: Rank-based criteria

    John A. Lee;Michel Verleysen

  • K nearest neighbours with mutual information for simultaneous classification and missing data imputation

    Pedro J. García-Laencina;José-Luis Sancho-Gómez;Aníbal R. Figueiras-Vidal;Michel Verleysen

  • Mutual information for the selection of relevant variables in spectrometric nonlinear modelling

    Fabrice Rossi;Amaury Lendasse;Damien François;Vincent Wertz

  • Weighted Conditional Random Fields for Supervised Interpatient Heartbeat Classification

    G. de Lannoy;D. Francois;J. Delbeke;M. Verleysen

  • Clustering Smart Card Data for Urban Mobility Analysis

    Mohamed K. El Mahrsi;Etienne Come;Latifa Oukhellou;Michel Verleysen

  • Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis

    John Aldo Lee;Amaury Lendasse;Michel Verleysen

  • Image compression by self-organized Kohonen map

    C. Amerijckx;M. Verleysen;P. Thissen;J.-D. Legat

  • Non-linear financial time series forecasting application to the Bel 20 stock market index

    Amaury Lendasse;Eric de Bodt;Vincent Wertz;Michel Verleysen

  • Feature selection for interpatient supervised heart beat classification

    G. Doquire;G. De Lannoy;D. François;M. Verleysen

  • Resampling methods for parameter-free and robust feature selection with mutual information

    D. François;F. Rossi;V. Wertz;M. Verleysen

  • A robust nonlinear projection method

    John Aldo Lee;Amaury Lendasse;Nicolas Donckers;Michel Verleysen

  • On the Kernel Widths in Radial-Basis Function Networks

    Nabil Benoudjit;Michel Verleysen

  • Letters: Mutual information-based feature selection for multilabel classification

    Gauthier Doquire;Michel Verleysen

  • Representation of functional data in neural networks

    Fabrice Rossi;Nicolas Delannay;Brieuc Conan-Guez;Michel Verleysen

  • A robust non-linear projection method.

    John Aldo Lee;Amaury Lendasse;Nicolas Donckers;Michel Verleysen

  • Multivariate statistics process control for dimensionality reduction in structural assessment

    L. E. Mujica;J. Vehi;M. Ruiz;Michel Verleysen

Frequent Co-Authors

John Aldo Lee
John Aldo Lee Université Catholique de Louvain
Amaury Lendasse
Amaury Lendasse University of Houston
Christian Jutten
Christian Jutten Grenoble Alpes University
Thomas Villmann
Thomas Villmann Hochschule Mittweida
Barbara Hammer
Barbara Hammer Bielefeld University
André Mouraux
André Mouraux Université Catholique de Louvain
Daniel A. Keim
Daniel A. Keim University of Konstanz
Erkki Oja
Erkki Oja Aalto University
César A. Hidalgo
César A. Hidalgo Harvard University
Luc Vandendorpe
Luc Vandendorpe Université Catholique de Louvain

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