World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
25896
World Ranking
5975
National Ranking
75

Pierre Geurts publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Pierre Geurts sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 178 publications — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Pierre Geurts D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Pierre Geurts sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Pierre Geurts is affiliated with the University of Liège in Belgium and has a focused research profile primarily within the domain of Computer Science. Their research output covers various subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Cognitive Neuroscience, and Molecular Biology.

The main topics of Pierre Geurts' research include:

  • Machine Learning and Data Classification
  • Neural Networks and Applications
  • Domain Adaptation and Few-Shot Learning
  • Aesthetic Perception and Analysis
  • Explainable Artificial Intelligence (XAI)
  • Music and Audio Processing
  • Diverse Musicological Studies

Frequent co-authors collaborating with Pierre Geurts are:

  • Walter Daelemans
  • Mike Kestemont
  • Vân Anh Huynh-Thu
  • Karine Lasaracina
  • Matthia Sabatelli

The scientist has published notably in these venues:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Machine Learning
  • Open Repository and Bibliography (University of Liège)
  • Data Mining and Knowledge Discovery

Recent publications include:

  • "Can local explanation techniques explain linear additive models?" (2023) in Data Mining and Knowledge Discovery
  • "Transfer Learning with Style Transfer between the Photorealistic and Artistic Domain" (2021) in Electronic Imaging
  • "Recent Advances in Bioimage Analysis Methods for Detecting Skeletal Deformities in Biomedical and Aquaculture Fish Species" (2023) in Biomolecules
  • "Optimizing model-agnostic random subspace ensembles" (2023) in Machine Learning
  • "From global to local MDI variable importances for random forests and when they are Shapley values" (2021) in arXiv (Cornell University)

In addition to articles and conference papers, Pierre Geurts has contributed to book literature with a publication titled Artificial Intelligence and Machine Learning released by Springer Science+Business Media in 2020.

Best Publications

  • Extremely randomized trees

    Pierre Geurts;Damien Ernst;Louis Wehenkel

  • SCENIC: single-cell regulatory network inference and clustering.

    Sara Aibar;Carmen Bravo González-Blas;Thomas Moerman;Vân Anh Huynh-Thu

  • Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

    Vân Anh Huynh-Thu;Alexandre Irrthum;Louis Wehenkel;Pierre Geurts

  • Tree-Based Batch Mode Reinforcement Learning

    Damien Ernst;Pierre Geurts;Louis Wehenkel

  • Understanding variable importances in forests of randomized trees

    Gilles Louppe;Louis Wehenkel;Antonio Sutera;Pierre Geurts

  • Pattern Extraction for Time Series Classification

    Pierre Geurts

  • Random subwindows for robust image classification

    R. Maree;P. Geurts;J. Piater;L. Wehenkel

  • Supervised learning with decision tree-based methods in computational and systems biology

    Pierre Geurts;Alexandre Irrthum;Louis Wehenkel

  • Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

    Ching-Wei Wang;Cheng-Ta Huang;Meng-Che Hsieh;Chung-Hsing Li

  • dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data.

    Vân Anh Huynh-Thu;Pierre Geurts

  • Collaborative analysis of multi-gigapixel imaging data using Cytomine

    Raphaël Marée;Loïc Rollus;Benjamin Stévens;Renaud Hoyoux

  • MicroRNAs profiling in murine models of acute and chronic asthma: a relationship with mRNAs targets.

    Nancy Garbacki;Emmanuel Di Valentin;Vân Anh Huynh-Thu;Pierre Geurts

  • Proteomic mass spectra classification using decision tree based ensemble methods

    Pierre Geurts;Marianne Fillet;Dominique De Seny;Marie-Alice Meuwis

  • Ensembles on random patches

    Gilles Louppe;Pierre Geurts

  • Discovery of new rheumatoid arthritis biomarkers using the surface‐enhanced laser desorption/ionization time‐of‐flight mass spectrometry ProteinChip approach

    Dominique de Seny;Marianne Fillet;Marie-Alice Meuwis;Pierre Geurts

  • Comparison of Deep Transfer Learning Strategies for Digital Pathology

    Romain Mormont;Pierre Geurts;Raphael Maree

  • Statistical interpretation of machine learning-based feature importance scores for biomarker discovery

    Vân Anh Huynh-Thu;Yvan Saeys;Louis Wehenkel;Pierre Geurts

  • Automated processing of zebrafish imaging data - a survey

    Ralf Mikut;Thomas Dickmeis;Wolfgang Driever;Pierre Geurts

  • Estimation of rotor angles of synchronous machines using artificial neural networks and local PMU-based quantities

    Alberto Del Angel;Pierre Geurts;Damien Ernst;Mevludin Glavic

  • Cerebral functional connectivity periodically (de)synchronizes with anatomical constraints

    Raphaël Liégeois;Erik Ziegler;Christophe Phillips;Pierre Geurts

  • DMFSGD: a decentralized matrix factorization algorithm for network distance prediction

    Yongjun Liao;Wei Du;Pierre Geurts;Guy Leduc

Frequent Co-Authors

Louis Wehenkel
Louis Wehenkel University of Liège
Damien Ernst
Damien Ernst University of Liège
Christophe Phillips
Christophe Phillips University of Liège
Yvan Saeys
Yvan Saeys Ghent University
Marie-Paule Merville
Marie-Paule Merville University of Liège
Marianne Fillet
Marianne Fillet University of Liège
Vincent Bours
Vincent Bours University of Liège
Christine Bastin
Christine Bastin University of Liège
Justus Piater
Justus Piater University of Innsbruck
Marco Wiering
Marco Wiering University of Groningen

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