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Engineering and Technology
Poland
2026

D-Index & Metrics

Chemistry

D-Index
59
Citations
12998
World Ranking
10095
National Ranking
33

Engineering and Technology

D-Index
59
Citations
12604
World Ranking
2347
National Ranking
3

Beata Walczak 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 Beata Walczak 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: 172 publications — 36th percentile

36% of scientists in this discipline score the same or lower.

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

Beata Walczak 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 Beata Walczak 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: 59 D-Index — 77th percentile

77% 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

  • 2026 - Research.com Engineering and Technology in Poland Leader Award
  • 2025 - Research.com Engineering and Technology in Poland Leader Award

Overview

Beata Walczak is affiliated with the University of Silesia in Poland and has contributed extensively to the fields of Chemistry, Agricultural and Biological Sciences, and Medicine. Their research primarily focuses on Analytical Chemistry, with significant work also conducted in Molecular Biology, Artificial Intelligence, Biochemistry, and Food Science.

Walczak's research covers several main topics including:

  • Spectroscopy and Chemometric Analyses
  • Phytochemicals and Antioxidant Activities
  • Metaheuristic Optimization Algorithms Research
  • Pesticide Residue Analysis and Safety
  • Heavy Metals in Plants
  • Identification and Quantification in Food
  • Tea Polyphenols and Effects

Their frequent publication venues consist of:

  • Chemometrics and Intelligent Laboratory Systems
  • Journal of Food Composition and Analysis
  • Journal of Chemometrics
  • LWT
  • Food Control

Some recent papers authored by Walczak include:

  • Authentication of honeybush and rooibos herbal teas based on their elemental composition (2020, Food Control)
  • High-temperature oxidation reduces the bitterness of honeybush infusions depending on changes in phenolic composition (2020, LWT)
  • Combining class-modelling and discriminant methods for improvement of products authentication (2022, Chemometrics and Intelligent Laboratory Systems)
  • Class-modelling of overlapping classes. A two-step authentication approach (2021, Analytica Chimica Acta)
  • Different strategies for class model optimization. A comparative study (2020, Talanta)

Frequently collaborating coauthors include:

  • Dalene de Beer
  • Elizabeth Joubert
  • Zuzanna Małyjurek
  • Beata Zawisza
  • Federico Marini

Best Publications

  • Particle swarm optimization (PSO). A tutorial

    Federico Marini;Beata Walczak

  • Rough sets theory

    B. Walczak;D.L. Massart

  • Robust statistics in data analysis — A review: Basic concepts

    M. Daszykowski;K. Kaczmarek;K. Kaczmarek;Y. Vander Heyden;B. Walczak

  • Representative subset selection

    M. Daszykowski;Beata Walczak;Desire Massart

  • Looking for natural patterns in data: Part 1. Density-based approach

    M. Daszykowski;Beata Walczak;Desire Massart

  • Noise suppression and signal compression using the wavelet packet transform

    Beata Walczak;Desire Massart

  • Artificial neural networks in classification of NIR spectral data: Design of the training set

    W. Wu;B. Walczak;D.L. Massart;S. Heuerding

  • Comparison of regularized discriminant analysis linear discriminant analysis and quadratic discriminant analysis applied to NIR data

    W. Wu;Y. Mallet;B. Walczak;W. Penninckx

  • A comparison of two algorithms for warping of analytical signals

    V. Pravdova;Beata Walczak;Desire Massart

  • Dealing with missing data - Part II

    Beata Walczak;Desire Massart

  • Wavelets in chemistry.

    Beata Walczak

  • The Radial Basis Functions — Partial Least Squares approach as a flexible non-linear regression technique

    B. Walczak;D.L. Massart

  • TOMCAT: A MATLAB toolbox for multivariate calibration techniques

    Michał Daszykowski;Sven Serneels;Krzysztof Kaczmarek;Piet Van Espen

  • Optimization of signal denoising in discrete wavelet transform

    L. Pasti;B. Walczak;D.L. Massart;P. Reschiglian

  • Raman spectroscopy as a process analytical technology (PAT) tool for the in-line monitoring and understanding of a powder blending process.

    T.R.M. De Beer;C. Bodson;B. Dejaegher;B. Walczak

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

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

  • The use of CART and multivariate regression trees for supervised and unsupervised feature selection

    F. Questier;R. Put;D. Coomans;D. Coomans;B. Walczak

  • Chemometrics in analytical chemistry—part II: modeling, validation, and applications

    Richard G. Brereton;Jeroen Jansen;João Lopes;Federico Marini

  • Comparison of multivariate methods based on latent vectors and methods based on wavelength selection for the analysis of near-infrared spectroscopic data

    D. Jouan-Rimbaud;B. Walczak;D.L. Massart

  • Dealing with missing values and outliers in principal component analysis

    I. Stanimirova;M. Daszykowski;B. Walczak

  • Application of Wavelet Packet Transform in Pattern Recognition of Near-IR Data

    Beata Walczak;and Bas van den Bogaert;Desiré Luc Massart

Frequent Co-Authors

Desire L. Massart
Desire L. Massart Vrije Universiteit Brussel
Federico Marini
Federico Marini Sapienza University of Rome
Elizabeth Joubert
Elizabeth Joubert Stellenbosch University
Lutgarde M. C. Buydens
Lutgarde M. C. Buydens Radboud University
Paul J. Worsfold
Paul J. Worsfold Plymouth University
Gert Lubec
Gert Lubec Paracelsus Medical University
Ronei J. Poppi
Ronei J. Poppi State University of Campinas
Romà Tauler
Romà Tauler Spanish National Research Council
Yvan Vander Heyden
Yvan Vander Heyden Vrije Universiteit Brussel

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