About Me
Marie-Colette van Lieshout was educated at Free University and CWI Amsterdam. She started her career as lecturer at the University of Warwick before moving back to CWI as senior researcher. She also holds a chair in spatial stochastics at the University of Twente. She has published around 60 scientific papers and 5 books in stochastic geometry, spatial statistics and image analysis. Her research concerns the modelling and analysis of complicated geometrical structures such as point and object processes, random fields and tessellation models. Van Lieshout is an elected member of the ISI (International Statistical Institute). She is a board member of the council of the Bernoulli Society and the STAR research cluster, and was a member of the editorial boards of several journals, including Bernoulli and Methodology and Computing in Applied Probability, as well as of the KWG.
Expertise
Mathematics
# Earthquake
# Infill Asymptotics
# Intensity Function
# Kernel Estimator
# Point Process
# Spatio-Temporal Process
Business & Economics
# Kernel Estimator
# Point Process
Organisations
Ancillary Activities
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CWI
Senior researcher
Publications
Recent
van Lieshout, M.-C. (2024).
Discussion of ‘Marked Spatial Point Processes: Current State and Extensions to Point Processes on Linear Networks’ by Matthias Eckardt and Mehdi Moradi.
Journal of Agricultural, Biological, and Environmental Statistics. Advance online publication.
https://doi.org/10.1007/s13253-024-00609-x
Baki, Z.
, & van Lieshout, M. N. M. (2024).
On the moments of Cox rate-and-state models. (pp. 1-13). ArXiv.org.
https://doi.org/10.48550/arXiv.2403.13413
van Lieshout, M.-C.
, & Markwitz, R. L. (2024).
A non-homogeneous semi-Markov model for interval censoring. (pp. 1-21). ArXiv.org.
Lu, C., Guan, Y.
, van Lieshout, M.-C., & Xu, G. (2024).
XGBoostPP: Tree-based Estimation of Point Process Intensity Functions. ArXiv.org.
https://doi.org/10.48550/arXiv.2401.17966
van Lieshout, M.-C. (2024).
Non‑parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions.
Annals of the Institute of Statistical Mathematics,
76, 313–331.
https://doi.org/10.1007/s10463-023-00890-6
van Lieshout, M.-C.
, & Lu, C. (2024).
Contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning.
Journal of the Royal Statistical Society. Series B: Statistical Methodology. Advance online publication.
https://doi.org/10.1093/jrsssb/qkad150
Lu, C.
, van Lieshout, M.-C.
, de Graaf, M., & Visscher, P. (2023).
Data-driven chimney fire risk prediction using machine learning and point process tools.
Annals of applied statistics,
17(4), 3088-3111.
https://doi.org/10.1214/23-AOAS1752
van Lieshout, M.-C. (2023).
Optimal decision rules for marked point process models. (pp. 1-14). ArXiv.org.
https://doi.org/10.48550/arXiv.2309.03752
van Lieshout, M.-C., & Baki, Z. (2023).
Exploring Seismic Hazard in the Groningen Gas Field Using Adaptive Kernel Smoothing.
Mathematical geosciences. Advance online publication.
https://doi.org/10.1007/s11004-023-10081-x
van Lieshout, M.-C.
, & Markwitz, R. L. (2023).
State estimation for aoristic models.
Scandinavian journal of statistics,
50(3), 1068-1089.
https://doi.org/10.1111/sjos.12619
UT Research Information System
Courses Academic Year 2023/2024
Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
Courses Academic Year 2022/2023
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11), room 4029
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
4029
P.O. Box 217
7500 AE Enschede
The Netherlands