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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
1875
National Ranking
41

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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