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Desire L. Massart

D-Index & Metrics

Discipline name D-Index World Ranking National Ranking Publications Citations
Chemistry 97 1440 20 705 42043

Desire L. Massart publications per year

The chart shows the history of publications by Desire L. Massart between 1963 and 2011, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Desire L. Massart published across 49 years, from 1963 to 2011, averaging 17.2 papers a year. Output peaked at 58 publications in 1998. 7 of the 843 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 1963 to 2011. Vertical axis: number of publications, 0 to 58. Peak 58 publications in 1998. 1963: 1 publication 1964: 0 publications 1965: 1 publication 1966: 0 publications 1967: 0 publications 1968: 7 publications 1969: 3 publications 1970: 40 publications 1971: 2 publications 1972: 3 publications 1973: 9 publications 1974: 9 publications 1975: 9 publications 1976: 17 publications 1977: 9 publications 1978: 6 publications 1979: 8 publications 1980: 10 publications 1981: 14 publications 1982: 18 publications 1983: 24 publications 1984: 15 publications 1985: 19 publications 1986: 16 publications 1987: 11 publications 1988: 15 publications 1989: 16 publications 1990: 10 publications 1991: 13 publications 1992: 24 publications 1993: 20 publications 1994: 26 publications 1995: 29 publications 1996: 40 publications 1997: 35 publications 1998: 58 publications 1999: 48 publications 2000: 51 publications 2001: 46 publications 2002: 38 publications 2003: 33 publications 2004: 39 publications 2005: 29 publications 2006: 10 publications 2007: 5 publications 2008: 0 publications 2009: 0 publications 2010: 6 publications 2011: 1 publication
1963 2011

843 publications in total across all disciplines

View publications per year as a table
Desire L. Massart: publications per year, 1963 to 2011
Year Publications
1963 1
1964 0
1965 1
1966 0
1967 0
1968 7
1969 3
1970 40
1971 2
1972 3
1973 9
1974 9
1975 9
1976 17
1977 9
1978 6
1979 8
1980 10
1981 14
1982 18
1983 24
1984 15
1985 19
1986 16
1987 11
1988 15
1989 16
1990 10
1991 13
1992 24
1993 20
1994 26
1995 29
1996 40
1997 35
1998 58
1999 48
2000 51
2001 46
2002 38
2003 33
2004 39
2005 29
2006 10
2007 5
2008 0
2009 0
2010 6
2011 1
Total 843
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Desire L. Massart publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Desire L. Massart sits on this spectrum.

No. of scientists
250 500 750 1,000 1,250
Bar chart with 63 bars. Horizontal axis: publications, 61–80 to 1,295+. Vertical axis: number of scientists, 0 to 1,350. Most scientists, 1,350, have 161–180 publications. The last bar groups every scientist with 1,295 publications or more. The highlighted bar, 701–720 publications, is where this scientist sits. 61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61–80 publications 1,295+

This scientist: 705 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,295 publications or more.

View publications distribution as a table
Number of Chemistry scientists by publication count, Research.com 2026 ranking edition. Based on 17,934 ranked scientists.
Publications Scientists This scientist
61–80 66
81–100 302
101–120 623
121–140 918
141–160 1,218
161–180 1,350
181–200 1,344
201–220 1,281
221–240 1,216
241–260 1,100
261–280 979
281–300 939
301–320 764
321–340 643
341–360 628
361–380 522
381–400 459
401–420 397
421–440 327
441–460 270
461–480 265
481–500 252
501–520 201
521–540 185
541–560 148
561–580 148
581–600 132
601–620 114
621–640 104
641–660 91
661–680 92
681–700 73
701–720 57 705
721–740 54
741–760 67
761–780 45
781–800 46
801–820 39
821–840 32
841–860 36
861–880 29
881–900 26
901–920 24
921–940 14
941–960 23
961–980 28
981–1,000 15
1,001–1,020 29
1,021–1,040 12
1,041–1,060 19
1,061–1,080 12
1,081–1,100 6
1,101–1,120 8
1,121–1,140 12
1,141–1,160 5
1,161–1,180 6
1,181–1,200 14
1,201–1,220 7
1,221–1,240 2
1,241–1,260 6
1,261–1,280 4
1,281–1,294 6
1,295+ 100
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Desire L. Massart D-index placement in Chemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Chemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Desire L. Massart sits on this spectrum.

No. of scientists
250 500 750 1,000
Bar chart with 61 bars. Horizontal axis: D-Index, 40–41 to 159+. Vertical axis: number of scientists, 0 to 1,051. Most scientists, 1,051, have 56–57 D-Index. The last bar groups every scientist with 159 D-Index or more. The highlighted bar, 96–97 D-Index, is where this scientist sits. 40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40–41 D-Index 159+

This scientist: 97 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

View D-Index distribution as a table
Number of Chemistry scientists by D-index, Research.com 2026 ranking edition. Based on 17,934 ranked scientists.
D-Index Scientists This scientist
40–41 289
42–43 612
44–45 808
46–47 776
48–49 835
50–51 861
52–53 872
54–55 933
56–57 1,051
58–59 930
60–61 882
62–63 834
64–65 731
66–67 775
68–69 683
70–71 646
72–73 561
74–75 501
76–77 437
78–79 388
80–81 354
82–83 292
84–85 275
86–87 254
88–89 235
90–91 185
92–93 192
94–95 155
96–97 163 97
98–99 125
100–101 105
102–103 105
104–105 112
106–107 88
108–109 68
110–111 69
112–113 65
114–115 79
116–117 61
118–119 44
120–121 37
122–123 40
124–125 33
126–127 26
128–129 34
130–131 35
132–133 25
134–135 27
136–137 17
138–139 16
140–141 20
142–143 20
144–145 15
146–147 9
148–149 9
150–151 16
152–153 11
154–155 9
156–157 3
158 3
159+ 98
Download as CSV

Overview

What is she best known for?

The fields of study she is best known for:

  • Statistics
  • Artificial intelligence
  • Machine learning

Artificial intelligence, Pattern recognition, Chromatography, Statistics and Analytical chemistry are her primary areas of study. Her research integrates issues of Machine learning, Multivariate statistics and Multivariate calibration in her study of Artificial intelligence. Anomaly detection is closely connected to Outlier in her research, which is encompassed under the umbrella topic of Multivariate statistics.

Her Chromatography research incorporates elements of Phase and Blind deconvolution. Desire Massart combines subjects such as Repeatability, Impurity and Near-infrared spectroscopy with her study of Analytical chemistry. Her Calibration research focuses on Chemometrics and how it connects with Algorithm.

Her most cited work include:

  • Handbook of Chemometrics and Qualimetrics: Part A (1752 citations)
  • The Mahalanobis distance (1262 citations)
  • Handbook of Chemometrics and Qualimetrics (741 citations)

What are the main themes of her work throughout her whole career to date?

Her primary areas of study are Chromatography, Artificial intelligence, Pattern recognition, Analytical chemistry and Statistics. Her Phase research extends to the thematically linked field of Chromatography. Her study in Artificial intelligence focuses on Pattern recognition, Principal component analysis, Feature selection, Linear discriminant analysis and Outlier.

Her Principal component analysis study frequently draws parallels with other fields, such as Chemometrics. Her Pattern recognition research includes elements of Cluster analysis, Set, Multivariate calibration and Data set. Calibration and Partial least squares regression are the subjects of her Statistics studies.

She most often published in these fields:

  • Chromatography (22.77%)
  • Artificial intelligence (20.16%)
  • Pattern recognition (18.32%)

What were the highlights of her more recent work (between 2002-2011)?

  • Chromatography (22.77%)
  • Statistics (12.83%)
  • Artificial intelligence (20.16%)

In recent papers she was focusing on the following fields of study:

Desire Massart mainly investigates Chromatography, Statistics, Artificial intelligence, Pattern recognition and Algorithm. Her Chromatography study integrates concerns from other disciplines, such as Phase and Analytical chemistry. Her Partial least squares regression, Regression, Principal component regression and Total least squares study in the realm of Statistics interacts with subjects such as Variance.

The concepts of her Pattern recognition study are interwoven with issues in Boosting and Overfitting. Her Algorithm research is multidisciplinary, relying on both Calibration, Orthographic projection and Selection. Her studies examine the connections between Chemometrics and genetics, as well as such issues in Principal component analysis, with regards to Multiple factor analysis and Set.

Between 2002 and 2011, her most popular works were:

  • Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals: Part I: Peak detection (116 citations)
  • Feasibility study for the use of near infrared spectroscopy in the qualitative and quantitative analysis of green tea, Camellia sinensis (L.) (114 citations)
  • Projection methods in chemistry (106 citations)

In her most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Machine learning

Her primary areas of investigation include Chromatography, Chemometrics, Analytical chemistry, High-performance liquid chromatography and Phase. Her research on Chromatography focuses in particular on Reversed-phase chromatography. Her Chemometrics research is multidisciplinary, incorporating perspectives in Set, Regression, Environmental data, Environmental chemistry and Principal component analysis.

Her work in the fields of High-performance liquid chromatography, such as Monolithic HPLC column, intersects with other areas such as Variable elimination. Her work deals with themes such as Column and Selection, which intersect with Phase. Desire Massart has researched Iterative method in several fields, including Statistics, Artificial intelligence and Pattern recognition.

Best Publications

  • Handbook of Chemometrics and Qualimetrics: Part A

    D. L. Massart;B. G. Vandeginste;L. M.C. Buydens;P. J. Lewi

  • Chemometrics: A Textbook

    Desiré L. Massart

  • Elimination of Uninformative Variables for Multivariate Calibration

    V Centner;D L Massart;O E de Noord;S de Jong

  • Handbook of Chemometrics and Qualimetrics

    Desire L. Massart;B. G. Vandeginste;L. M. Buydens;P. J. Lewi

  • The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis

    Desiré L. Massart;Leonard Kaufman

  • Guidance for robustness/ruggedness tests in method validation.

    Y Vander Heyden;A Nijhuis;J Smeyers-Verbeke;B.G.M Vandeginste

  • Near-infrared spectroscopy applications in pharmaceutical analysis

    J. Luypaert;D.L. Massart;Y. Vander Heyden

  • D-optimal designs

    P.F. de Aguiar;B. Bourguignon;M.S. Khots;D.L. Massart

  • Rough sets theory

    B. Walczak;D.L. Massart

  • Peak purity control in liquid chromatography with photodiode-array detection by a fixed size moving window evolving factor analysis

    H.R. Keller;D.L. Massart

  • Heuristic evolving latent projections: resolving two-way multicomponent data. 2. Detection and resolution of minor constituents

    Yi Zeng. Liang;Olav M. Kvalheim;Hans R. Keller;D. Luc. Massart

  • Validation of bioanalytical chromatographic methods.

    C Hartmann;J Smeyers-Verbeke;D.L Massart;R.D McDowall

  • Representative subset selection

    M. Daszykowski;Beata Walczak;Desire Massart

  • Orthogonal projection approach applied to peak purity assessment.

    F. Cuesta Sanchez;J. Toft;B. Van Den Bogaert;D. L. Massart

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

    M. Daszykowski;Beata Walczak;Desire Massart

  • Standardization of near-infrared spectrometric instruments

    E. Bouveresse;and C. Hartmann;D. L. Massart

  • Noise suppression and signal compression using the wavelet packet transform

    Beata Walczak;Desire Massart

  • Evolving factor analysis

    H.R. Keller;D.L. 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

  • Alternative k-nearest neighbour rules in supervised pattern recognition : Part 1. k-Nearest neighbour classification by using alternative voting rules

    D. Coomans;D.L. Massart

Frequent Co-Authors

Beata Walczak
Beata Walczak University of Silesia
Qing-Song Xu
Qing-Song Xu Central South University
Yvan Vander Heyden
Yvan Vander Heyden Vrije Universiteit Brussel
Yvette Michotte
Yvette Michotte Vrije Universiteit Brussel
Susan Gourvenec
Susan Gourvenec University of Southampton
Philip K. Hopke
Philip K. Hopke Clarkson University
Jacques Crommen
Jacques Crommen University of Liège
Lutgarde M. C. Buydens
Lutgarde M. C. Buydens Radboud University
Matthias Laska
Matthias Laska Linköping University
Kim H. Esbensen
Kim H. Esbensen Geological Survey of Denmark and Greenland

External Links

Google Scholar page

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Best Scientists Citing Desire L. Massart

Yi-Zeng Liang

Yi-Zeng Liang

Central South University

Publications: 159

Romà Tauler

Romà Tauler

Spanish National Research Council

Publications: 114

Yvan Vander Heyden

Yvan Vander Heyden

Vrije Universiteit Brussel

Publications: 96

Lutgarde M. C. Buydens

Lutgarde M. C. Buydens

Radboud University

Publications: 68

Serge Kokot

Serge Kokot

Queensland University of Technology

Publications: 51

Ru-Qin Yu

Ru-Qin Yu

Hunan University

Publications: 49

Beata Walczak

Beata Walczak

University of Silesia

Publications: 49

Qing-Song Xu

Qing-Song Xu

Central South University

Publications: 48

Yong He

Yong He

Zhejiang University

Publications: 41

Yukihiro Ozaki

Yukihiro Ozaki

Kwansei Gakuin University

Publications: 39

Da-Wen Sun

Da-Wen Sun

University College Dublin

Publications: 39

Mário César Ugulino de Araújo

Mário César Ugulino de Araújo

Federal University of Paraíba

Publications: 35

Héctor C. Goicoechea

Héctor C. Goicoechea

National University of the Littoral

Publications: 34

Quansheng Chen

Quansheng Chen

Jiangsu University

Publications: 34

Roberto Kawakami Harrop Galvão

Roberto Kawakami Harrop Galvão

Instituto Tecnológico de Aeronáutica

Publications: 34

Age K. Smilde

Age K. Smilde

University of Amsterdam

Publications: 34

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