Michiel Debruyne

995 total citations
16 papers, 634 citations indexed

About

Michiel Debruyne is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Analytical Chemistry. According to data from OpenAlex, Michiel Debruyne has authored 16 papers receiving a total of 634 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Statistics and Probability, 7 papers in Statistics, Probability and Uncertainty and 4 papers in Analytical Chemistry. Recurrent topics in Michiel Debruyne's work include Advanced Statistical Methods and Models (14 papers), Statistical Methods and Inference (8 papers) and Advanced Statistical Process Monitoring (6 papers). Michiel Debruyne is often cited by papers focused on Advanced Statistical Methods and Models (14 papers), Statistical Methods and Inference (8 papers) and Advanced Statistical Process Monitoring (6 papers). Michiel Debruyne collaborates with scholars based in Belgium, United States and Mexico. Michiel Debruyne's co-authors include Mia Hubert, Peter J. Rousseeuw, Tim Verdonck, Sanne Engelen, Johan A. K. Suykens, Sven Serneels, Andreas Christmann, Karlien Vanden Branden, Christophe Mues and Tony Van Gestel and has published in prestigious journals such as Computational Statistics & Data Analysis, Journal of Chemometrics and Journal of Multivariate Analysis.

In The Last Decade

Michiel Debruyne

16 papers receiving 615 citations

Peers

Michiel Debruyne
Michiel Debruyne
Citations per year, relative to Michiel Debruyne Michiel Debruyne (= 1×) peers Laurie Davies

Countries citing papers authored by Michiel Debruyne

Since Specialization
Citations

This map shows the geographic impact of Michiel Debruyne'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 Michiel Debruyne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michiel Debruyne more than expected).

Fields of papers citing papers by Michiel Debruyne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michiel Debruyne. 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 Michiel Debruyne. The network helps show where Michiel Debruyne may publish in the future.

Co-authorship network of co-authors of Michiel Debruyne

This figure shows the co-authorship network connecting the top 25 collaborators of Michiel Debruyne. A scholar is included among the top collaborators of Michiel Debruyne 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 Michiel Debruyne. Michiel Debruyne is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Debruyne, Michiel, et al.. (2018). Outlyingness: Which variables contribute most?. Statistics and Computing. 29(4). 707–723. 10 indexed citations
2.
Hubert, Mia, Michiel Debruyne, & Peter J. Rousseeuw. (2017). Minimum covariance determinant and extensions. Wiley Interdisciplinary Reviews Computational Statistics. 10(3). 130 indexed citations
3.
Debruyne, Michiel, et al.. (2014). A proposed framework for backtesting loss given default models. The Journal of Risk Model Validation. 8(1). 69–90. 6 indexed citations
4.
Verdonck, Tim & Michiel Debruyne. (2010). The influence of individual claims on the chain-ladder estimates: Analysis and diagnostic tool. Insurance Mathematics and Economics. 48(1). 85–98. 15 indexed citations
5.
Debruyne, Michiel & Tim Verdonck. (2010). Robust kernel principal component analysis and classification. Advances in Data Analysis and Classification. 4(2-3). 151–167. 37 indexed citations
6.
Debruyne, Michiel, Sven Serneels, & Tim Verdonck. (2009). Robustified least squares support vector classification. Journal of Chemometrics. 23(9). 479–486. 7 indexed citations
7.
Hubert, Mia & Michiel Debruyne. (2009). Breakdown value. Wiley Interdisciplinary Reviews Computational Statistics. 1(3). 296–302. 13 indexed citations
8.
Debruyne, Michiel, et al.. (2009). Detecting influential observations in Kernel PCA. Computational Statistics & Data Analysis. 54(12). 3007–3019. 25 indexed citations
9.
Hubert, Mia & Michiel Debruyne. (2009). Minimum covariance determinant. Wiley Interdisciplinary Reviews Computational Statistics. 2(1). 36–43. 173 indexed citations
10.
Debruyne, Michiel, Andreas Christmann, Mia Hubert, & Johan A. K. Suykens. (2009). Robustness of reweighted Least Squares Kernel Based Regression. Journal of Multivariate Analysis. 101(2). 447–463. 21 indexed citations
11.
Debruyne, Michiel, Mia Hubert, & Johan A. K. Suykens. (2008). Model Selection in Kernel Based Regression using the Influence Function. 9(78). 2377–2400. 52 indexed citations
12.
Debruyne, Michiel & Mia Hubert. (2008). The influence function of the Stahel–Donoho covariance estimator of smallest outlyingness. Statistics & Probability Letters. 79(3). 275–282. 14 indexed citations
13.
Debruyne, Michiel. (2007). Robustness of censored depth quantiles, PCA and kernel based regression with new tools for model selection. 3 indexed citations
14.
Debruyne, Michiel, Mia Hubert, Stephen Portnoy, & Karlien Vanden Branden. (2007). Censored depth quantiles. Computational Statistics & Data Analysis. 52(3). 1604–1614. 5 indexed citations
15.
Rousseeuw, Peter J., Michiel Debruyne, Sanne Engelen, & Mia Hubert. (2006). Robustness and Outlier Detection in Chemometrics. Critical Reviews in Analytical Chemistry. 36(3-4). 221–242. 121 indexed citations
16.
Debruyne, Michiel & Mia Hubert. (2005). The influence function of Stahel-Donoho type methods for robust PCA. 2 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026