Michiel Debruyne
- Statistics and Probability top 2%
- Artificial Intelligence top 10%
- Statistics, Probability and Uncertainty top 2%
- Control and Systems Engineering top 10%
- Analytical Chemistry top 5%
- Co-authors
- Mia HubertPeter J. RousseeuwTim VerdonckSanne EngelenJohan A. K. SuykensSven SerneelsAndreas ChristmannKarlien Vanden Branden
- Topics
- Advanced Statistical Methods and Models (14 papers)Statistical Methods and Inference (8 papers)Advanced Statistical Process Monitoring (6 papers)
- Journals
- Computational Statistics & Data AnalysisJournal of ChemometricsJournal of Multivariate Analysis
- Partner nations
- BelgiumUnited StatesMexico
In The Last Decade
Michiel Debruyne
16 papers receiving 615 citations
Peers
Comparison fields: 5 of 129
- Statistics and Probability 212
- Artificial Intelligence 163
- Statistics, Probability and Uncertainty 119
- Control and Systems Engineering 93
- Analytical Chemistry 74
Countries citing papers authored by Michiel Debruyne
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 130 | |
| 3 | 6 | |
| 4 | 15 | |
| 5 | 37 | |
| 6 | 7 | |
| 7 | 13 | |
| 8 | 25 | |
| 9 | 173 | |
| 10 | 21 | |
| 11 | Model Selection in Kernel Based Regression using the Influence Function | 52 |
| 12 | 14 | |
| 13 | Robustness of censored depth quantiles, PCA and kernel based regression with new tools for model selection | 3 |
| 14 | 5 | |
| 15 | 121 | |
| 16 | The influence function of Stahel-Donoho type methods for robust PCA | 2 |
About Michiel Debruyne
Michiel Debruyne is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Analytical Chemistry, having authored 16 papers that have together received 634 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (14 papers), Statistical Methods and Inference (8 papers) and Advanced Statistical Process Monitoring (6 papers). The work is most often cited by research in Statistics and Probability (212 citations), Statistics, Probability and Uncertainty (119 citations) and Analytical Chemistry (74 citations). Michiel Debruyne has collaborated with scholars based in Belgium, United States and Mexico. Frequent 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. Their work appears in journals such as Computational Statistics & Data Analysis, Journal of Chemometrics and Journal of Multivariate Analysis.
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.