G. Kateman

4.1k total citations
128 papers, 3.2k citations indexed

About

G. Kateman is a scholar working on Analytical Chemistry, Artificial Intelligence and Spectroscopy. According to data from OpenAlex, G. Kateman has authored 128 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Analytical Chemistry, 30 papers in Artificial Intelligence and 27 papers in Spectroscopy. Recurrent topics in G. Kateman's work include Spectroscopy and Chemometric Analyses (49 papers), Analytical Chemistry and Chromatography (26 papers) and Fault Detection and Control Systems (18 papers). G. Kateman is often cited by papers focused on Spectroscopy and Chemometric Analyses (49 papers), Analytical Chemistry and Chromatography (26 papers) and Fault Detection and Control Systems (18 papers). G. Kateman collaborates with scholars based in Netherlands, United Kingdom and Germany. G. Kateman's co-authors include C.B. Lucasius, B.G.M. Vandeginste, L.M.C. Buydens, J.R.M. Smits, Nicolaas M. Faber, W.J. Melssen, H.C. Smit, B. Vandeginste, L.M.C. Buydens and D. Wienke and has published in prestigious journals such as Analytical Chemistry, Journal of Chromatography A and Analytica Chimica Acta.

In The Last Decade

G. Kateman

124 papers receiving 2.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
G. Kateman Netherlands 29 1.6k 1.0k 659 468 463 128 3.2k
Jure Zupan Slovenia 36 1.4k 0.8× 1.0k 1.0× 844 1.3× 592 1.3× 470 1.0× 140 5.2k
Курт Вармуза Austria 26 1.1k 0.7× 671 0.6× 1.1k 1.7× 251 0.5× 198 0.4× 112 4.0k
Sijmen de Jong Netherlands 21 2.2k 1.3× 345 0.3× 713 1.1× 290 0.6× 524 1.1× 31 4.3k
John H. Kalivas United States 33 2.4k 1.4× 490 0.5× 710 1.1× 208 0.4× 782 1.7× 119 3.3k
M. Daszykowski Poland 29 1.3k 0.8× 613 0.6× 507 0.8× 353 0.8× 172 0.4× 79 3.1k
T. L. Isenhour United States 28 998 0.6× 1.0k 1.0× 616 0.9× 305 0.7× 134 0.3× 118 2.5k
Roman M. Balabin Switzerland 36 1.9k 1.1× 890 0.9× 1.2k 1.9× 147 0.3× 376 0.8× 62 4.3k
Paul J. Gemperline United States 29 2.0k 1.2× 755 0.7× 771 1.2× 105 0.2× 573 1.2× 74 2.9k
D.L. Massart Belgium 25 1.6k 1.0× 389 0.4× 575 0.9× 133 0.3× 353 0.8× 48 2.4k
Fredrik Lindgren Sweden 20 1.3k 0.8× 315 0.3× 449 0.7× 95 0.2× 360 0.8× 42 2.9k

Countries citing papers authored by G. Kateman

Since Specialization
Citations

This map shows the geographic impact of G. Kateman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by G. Kateman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Kateman more than expected).

Fields of papers citing papers by G. Kateman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. Kateman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by G. Kateman. The network helps show where G. Kateman may publish in the future.

Co-authorship network of co-authors of G. Kateman

This figure shows the co-authorship network connecting the top 25 collaborators of G. Kateman. A scholar is included among the top collaborators of G. Kateman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with G. Kateman. G. Kateman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Faber, Nicolaas M., L.M.C. Buydens, & G. Kateman. (1994). Aspects of pseudorank estimation methods based on the eigenvalues of principal component analysis of random matrices. Chemometrics and Intelligent Laboratory Systems. 25(2). 203–226. 33 indexed citations
2.
Melssen, W.J., J.R.M. Smits, L.M.C. Buydens, & G. Kateman. (1994). Using artificial neural networks for solving chemical problems. Chemometrics and Intelligent Laboratory Systems. 23(2). 267–291. 71 indexed citations
3.
Faber, Nicolaas M., L.M.C. Buydens, & G. Kateman. (1994). Generalized rank annihilation method. I: Derivation of eigenvalue problems. Journal of Chemometrics. 8(2). 147–154. 39 indexed citations
4.
Parczewski, A., C.B. Lucasius, & G. Kateman. (1994). Evolutionary determination of physico-chemical parameters and concentrations of analytes from titration data. Analytical and Bioanalytical Chemistry. 348(10). 626–632. 7 indexed citations
5.
Faber, Nicolaas M., L.M.C. Buydens, & G. Kateman. (1994). Aspects of pseudorank estimation methods based on an estimate of the size of the measurement error. Analytica Chimica Acta. 296(1). 1–20. 25 indexed citations
6.
Postma, Geert, et al.. (1994). A data base approach on analytical chemical methods applying fuzzy logic in the search strategy and flow charts for the representation of the retrieved analytical procedures. Chemometrics and Intelligent Laboratory Systems. 25(2). 285–295. 5 indexed citations
7.
Weijer, A.P. de, C.B. Lucasius, L.M.C. Buydens, G. Kateman, & H. M. Heuvel. (1993). Using genetic algorithms for an artificial neural network model inversion. Chemometrics and Intelligent Laboratory Systems. 20(1). 45–55. 14 indexed citations
8.
Faber, Nicolaas M., L.M.C. Buydens, & G. Kateman. (1993). Standard errors in the eigenvalues of a cross‐product matrix: Theory and applications. Journal of Chemometrics. 7(6). 495–526. 27 indexed citations
9.
Lucasius, C.B. & G. Kateman. (1992). Towards Solving Subset Selection Problems with the Aid of the Genetic Algorithm.. 241–250. 15 indexed citations
10.
Blommers, Marcel J. J., C.B. Lucasius, G. Kateman, & Robert Kaptein. (1992). Conformational analysis of a dinucleotide photodimer with the aid of the genetic algorithm. Biopolymers. 32(1). 45–52. 50 indexed citations
11.
Wienke, D., C.B. Lucasius, & G. Kateman. (1992). Multicriteria target vector optimization of analytical procedures using a genetic algorithm. Analytica Chimica Acta. 265(2). 211–225. 54 indexed citations
12.
Wehrens, Ron, L.M.C. Buydens, & G. Kateman. (1991). Validation and refinement of expert systems: interpretation of NMR spectra as an application in analytical chemistry. Chemometrics and Intelligent Laboratory Systems. 12(1). 57–67. 7 indexed citations
13.
Leeuwen, J. van, L.M.C. Buydens, B.G.M. Vandeginste, G. Kateman, & M. Mulholland. (1990). Expert system for precision testing in validation of liquid chromatographic methods. Analytica Chimica Acta. 235. 27–40. 10 indexed citations
14.
Lucasius, C.B. & G. Kateman. (1989). Application of genetic algorithms in chemometrics. international conference on Genetic algorithms. 170–176. 22 indexed citations
15.
Vandeginste, B., et al.. (1989). LABGEN, expert system for knowledge-based modelling of analytical laboratories. Analytica Chimica Acta. 222(1). 1–17. 5 indexed citations
16.
Jansen, A.P., et al.. (1987). Solomon, a classification program based on a statistical multivariate disjoint model. Analytica Chimica Acta. 193. 269–276. 3 indexed citations
17.
Kateman, G., et al.. (1986). Multi-inductive component analysis ? A powerful tool in pattern recognition. Microchimica Acta. 89(1-6). 153–161.
18.
Kateman, G., et al.. (1986). Automation of the optical alignment of a diode-laser spectrometer by means of simplex optimization. Analytica Chimica Acta. 184. 87–97. 5 indexed citations
19.
Kateman, G.. (1983). Meeting reports: International conference on chemometrics in analytical chemistry. TrAC Trends in Analytical Chemistry. 2(3). XI–XII. 2 indexed citations
20.
Kateman, G., et al.. (1979). Education in Analytical Chemistry. Fresenius Zeitschrift für Analytische Chemie. 297(4). 249–253. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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