Tim Verdonck

2.1k total citations
80 papers, 1.3k citations indexed

About

Tim Verdonck is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Tim Verdonck has authored 80 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 20 papers in Artificial Intelligence and 12 papers in Statistics, Probability and Uncertainty. Recurrent topics in Tim Verdonck's work include Advanced Statistical Methods and Models (24 papers), Statistical Methods and Inference (20 papers) and Advanced Statistical Process Monitoring (12 papers). Tim Verdonck is often cited by papers focused on Advanced Statistical Methods and Models (24 papers), Statistical Methods and Inference (20 papers) and Advanced Statistical Process Monitoring (12 papers). Tim Verdonck collaborates with scholars based in Belgium, Netherlands and United Kingdom. Tim Verdonck's co-authors include Bart Baesens, Mia Hubert, Sven Serneels, Peter J. Rousseeuw, Quinten David Soetens, Serge Demeyer, Ahmed Lamkanfi, Michiel Debruyne, Seppe vanden Broucke and María Óskarsdóttir and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Tim Verdonck

69 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tim Verdonck Belgium	16	295	255	219	161	128	80	1.3k
Bonnie K. Ray United States	22	187 0.6×	215 0.8×	144 0.7×	144 0.9×	47 0.4×	59	1.6k
Robert G. Cowell United Kingdom	11	1.2k 4.0×	219 0.9×	157 0.7×	258 1.6×	97 0.8×	25	2.0k
Refik Soyer United States	22	208 0.7×	480 1.9×	102 0.5×	217 1.3×	290 2.3×	97	1.6k
Renata M.C.R. de Souza Brazil	17	636 2.2×	220 0.9×	152 0.7×	100 0.6×	44 0.3×	81	1.1k
Brahim Ouhbi Morocco	16	299 1.0×	98 0.4×	149 0.7×	170 1.1×	64 0.5×	75	704
M. S. Nikulin France	14	180 0.6×	592 2.3×	53 0.2×	101 0.6×	274 2.1×	49	1.3k
Vicente García Mexico	23	1.4k 4.8×	53 0.2×	278 1.3×	179 1.1×	63 0.5×	62	2.2k
Jane M. Booker United States	12	191 0.6×	135 0.5×	51 0.2×	229 1.4×	209 1.6×	43	924
Jing–Rong Chang Taiwan	13	237 0.8×	180 0.7×	84 0.4×	629 3.9×	126 1.0×	32	962
Johan René van Dorp United States	24	144 0.5×	467 1.8×	59 0.3×	314 2.0×	726 5.7×	58	1.8k

Countries citing papers authored by Tim Verdonck

Since Specialization

Citations

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

Fields of papers citing papers by Tim Verdonck

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tim Verdonck

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

All Works

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20 of 20 papers shown

Baesens, Bart, et al.. (2025). Enhancing explainability in real-world scenarios: Towards a robust stability measure for local interpretability. Expert Systems with Applications. 274. 126922–126922. 1 indexed citations

Baesens, Bart, et al.. (2025). Code and Data for "Network Analytics for Anti-money Laundering—A Systematic Literature Review and Experimental Evaluation".

Wieneke, Sebastian, et al.. (2025). Improved gap-filling of eddy covariance CO 2 fluxes using remote sensing and environmental variables via XGBoost. Agricultural and Forest Meteorology. 378. 110987–110987.

Verbeke, Wouter, et al.. (2025). Advances in Continual Graph Learning for Anti‐Money Laundering Systems: A Comprehensive Review. Wiley Interdisciplinary Reviews Computational Statistics. 17(3).

Verdonck, Tim, et al.. (2024). Can causal machine learning reveal individual bid responses of bank customers? — A study on mortgage loan applications in Belgium. Decision Support Systems. 190. 114378–114378.

Vidal, Alix, Jan Willem van Groenigen, Tim Verdonck, et al.. (2024). How earthworms thrive and drive silicate rock weathering in an artificial organo-mineral system. Applied Geochemistry. 180. 106271–106271. 4 indexed citations

Dhaene, Jan, et al.. (2024). On the causality-preservation capabilities of generative modelling. Journal of Computational and Applied Mathematics. 457. 116312–116312. 1 indexed citations

Oirbeek, Robin Van, et al.. (2024). Non-Differentiable Loss Function Optimization and Interaction Effect Discovery in Insurance Pricing Using the Genetic Algorithm. Risks. 12(5). 79–79. 1 indexed citations

Lembrechts, Jonas J., et al.. (2024). Missing Value Imputation of Wireless Sensor Data for Environmental Monitoring. Sensors. 24(8). 2416–2416. 14 indexed citations

10.

Verbeke, Wouter, et al.. (2024). Network analytics for insurance fraud detection: a critical case study. European Actuarial Journal. 14(3). 965–990. 1 indexed citations

11.

Verdonck, Tim, et al.. (2023). Interpretable cost-sensitive regression through one-step boosting. Decision Support Systems. 175. 114024–114024.

12.

Verdonck, Tim, et al.. (2023). Smart initialisation and approximating loss function for robust regression. Information Sciences. 651. 119715–119715. 1 indexed citations

13.

Verdonck, Tim, et al.. (2023). Fraud analytics: A decade of research. Expert Systems with Applications. 232. 120605–120605. 9 indexed citations

14.

Serneels, Sven, et al.. (2023). Portfolio optimization using cellwise robust association measures and clustering methods with application to highly volatile markets. SHILAP Revista de lepidopterología. 9. 100097–100097. 6 indexed citations

15.

Serneels, Sven, et al.. (2023). Practicable optimization for portfolios that contain nonfungible tokens. Finance research letters. 55. 103969–103969. 2 indexed citations

16.

Boute, Robert, et al.. (2023). Optimizing the preventive maintenance frequency with causal machine learning. International Journal of Production Economics. 258. 108798–108798. 10 indexed citations

17.

Perrotta, Domenico, et al.. (2023). Co-clustering contaminated data: a robust model-based approach. Advances in Data Analysis and Classification. 18(1). 121–161. 2 indexed citations

18.

Verdonck, Tim, Sofia Pazmiño, Veerle Stouten, et al.. (2021). POS1434 WHICH PROGNOSTIC FACTORS MIGHT PREDICT THE NEED FOR TREATMENT ADAPTATION IN EARLY RHEUMATOID ARTHRITIS? A COMPARISON OF MACHINE LEARNING, SURVIVAL ANALYSIS AND REGRESSION METHODS. Annals of the Rheumatic Diseases. 80. 1001–1002. 1 indexed citations

19.

Baesens, Bart, et al.. (2020). Profit Driven Decision Trees for Churn Prediction. Lirias (KU Leuven). 84 indexed citations

20.

Boudt, Kris, et al.. (2020). Nearest comoment estimation with unobserved factors. Journal of Econometrics. 217(2). 381–397. 5 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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