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Lutgarde M. C. Buydens

Lutgarde M. C. Buydens

D-Index & Metrics

Engineering and Technology

D-Index
62
Citations
16225
World Ranking
1877
National Ranking
41

Lutgarde M. C. Buydens 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 Lutgarde M. C. Buydens 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: 222 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Lutgarde M. C. Buydens 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 Lutgarde M. C. Buydens 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: 62 D-Index — 81st percentile

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

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

Research.com Recognitions

  • 2016 - Member of Academia Europaea

Overview

Lutgarde M. C. Buydens is affiliated with Radboud University in the Netherlands. Their research primarily spans the domain of Environmental Science, with significant contributions across related subfields including Environmental Chemistry, Water Science and Technology, Nature and Landscape Conservation, and Physical and Theoretical Chemistry.

Their scholarly output covers multiple topics related to ecosystem and chemical dynamics in natural environments. Notable areas of focus include:

  • Soil and Water Nutrient Dynamics
  • Hydrology and Watershed Management Studies
  • Fish Ecology and Management Studies
  • Various Chemistry Research Topics

Recent publications showcase work in both hydrology and analytical chemistry. These papers are:

  • "BaHys-A Bayesian Modeling Framework for Long-Term Concentration-Discharge Hysteresis: A Case Study on Chloride," published in 2024 in Water Resources Research
  • "Chemometrics and intelligent laboratory systems Analytica Chimica Acta," published in 2024 in Analytica Chimica Acta

Frequent coauthors collaborating with Lutgarde M. C. Buydens include:

  • Maria Cairoli
  • Francisco Souza
  • Gerard J. Stroomberg
  • Geert Postma
  • Jeroen Jansen

They have contributed research across multiple prestigious venues, with publications listed in:

  • Water Resources Research
  • Analytica Chimica Acta

Recognition in the scientific community includes being named a Member of Academia Europaea in 2016.

Best Publications

  • Self- and Super-organizing Maps in R: The kohonen Package

    Ron Wehrens;Lutgarde M. C. Buydens

  • The bootstrap: a tutorial

    Ron Wehrens;Hein Putter;Lutgarde M.C Buydens

  • Using support vector machines for time series prediction

    U Thissen;R van Brakel;A.P de Weijer;W.J Melssen

  • NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review.

    Agnieszka Smolinska;Lionel Blanchet;Lionel Blanchet;Lutgarde M.C. Buydens;Sybren S. Wijmenga

  • Convolutional neural networks for vibrational spectroscopic data analysis

    Jacopo Acquarelli;Twan van Laarhoven;Jan Gerretzen;Thanh N. Tran

  • Triple-negative breast cancer: Present challenges and new perspectives

    Franca Podo;Lutgarde M.C. Buydens;Hadassa Degani;Riet Hilhorst

  • Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel

    B. Üstün;W.J. Melssen;L.M.C. Buydens

  • Possibilities of visible–near-infrared spectroscopy for the assessment of soil contamination in river floodplains

    L Kooistra;R Wehrens;R.S.E.W Leuven;L.M.C Buydens

  • Supervised Kohonen networks for classification problems

    Willem Melssen;Ron Wehrens;Lutgarde Buydens

  • Determination of optimal support vector regression parameters by genetic algorithms and simplex optimization

    B. Üstün;W.J. Melssen;M. Oudenhuijzen;L.M.C. Buydens

  • Interpretation of variable importance in Partial Least Squares with Significance Multivariate Correlation (sMC)

    Thanh N. Tran;Thanh N. Tran;Nelson Lee Afanador;Nelson Lee Afanador;Lutgarde M.C. Buydens;Lionel Blanchet

  • Multivariate calibration with least-squares support vector machines

    Uwe Thissen;Bülent Üstün;Willem J. Melssen;Lutgarde M. C. Buydens

  • Using artificial neural networks for solving chemical problems Part I. Multi-layer feed-forward networks

    J.R.M. Smits;W.J. Melssen;L.M.C. Buydens;G. Kateman

  • Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains.

    L Kooistra;E.A.L Salas;J.G.P.W Clevers;R Wehrens

  • Visualisation and interpretation of Support Vector Regression models.

    B. Üstün;W.J. Melssen;L.M.C. Buydens

  • Development of robust calibration models in near infra-red spectrometric applications

    H. Swierenga;F. Wülfert;O.E. de Noord;A.P. de Weijer

  • Tracing the geographical origin of honeys based on volatile compounds profiles assessment using pattern recognition techniques

    I. Stanimirova;B. Üstün;T. Cajka;K. Riddelova

  • Multiproject-multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy.

    Juan M. García-Gómez;Jan Luts;Margarida Julià-Sapé;Patrick Krooshof

  • Improvement of PLS model transferability by robust wavelength selection

    H. Swierenga;P.J. de Groot;A.P. de Weijer;M.W.J. Derksen

  • KNN-kernel density-based clustering for high-dimensional multivariate data

    Thanh N. Tran;Ron Wehrens;Lutgarde M. C. Buydens

Frequent Co-Authors

Arend Heerschap
Arend Heerschap Radboud University
Beata Walczak
Beata Walczak University of Silesia
Ron A. Wevers
Ron A. Wevers Radboud University
Wolfgang Buchberger
Wolfgang Buchberger Johannes Kepler University of Linz
Romà Tauler
Romà Tauler Spanish National Research Council
Federico Marini
Federico Marini Sapienza University of Rome
Yvan Vander Heyden
Yvan Vander Heyden Vrije Universiteit Brussel
Paul J. Worsfold
Paul J. Worsfold Plymouth University
Leo Koenderman
Leo Koenderman Utrecht University
Theo M. Luider
Theo M. Luider Erasmus University Rotterdam

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