prof.dr. M.N.M. van Lieshout (Marie-Colette)

Full Professor
EEMCS-AM-MOR
Zilverling 4029
m.n.m.vanlieshout@utwente.nl
+31534895647
Business card

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

  • Earth and Planetary Sciences

    • Model
    • Summary

  • Mathematics

    • Point Process
    • intensity function λ
    • Kernel Estimator
    • Spatial Point Process

  • Computer Science

    • Functions
    • Models

Organisations

Ancillary activities

  • CWISenior researcher

Publications

2024
Discussion of ‘Marked Spatial Point Processes: Current State and Extensions to Point Processes on Linear Networks’ by Matthias Eckardt and Mehdi Moradi, 395-398. van Lieshout, M.-C.https://doi.org/10.1007/s13253-024-00609-xM.N.M. van Lieshout and C. Lu's contribution to the Discussion of 'the Discussion Meeting on Probabilistic and statistical aspects of machine learning', 306-307. van Lieshout, M.-C. & Lu, C.https://doi.org/10.1093/jrsssb/qkad150Non‑parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions, 313–331. van Lieshout, M.-C.https://doi.org/10.1007/s10463-023-00890-6On the moments of Cox rate-and-state models, 1-13. ArXiv.org. Baki, Z. & van Lieshout, M. N. M.https://doi.org/10.48550/arXiv.2403.13413XGBoostPP: Tree-based Estimation of Point Process Intensity Functions. ArXiv.org. Lu, C., Guan, Y., van Lieshout, M.-C. & Xu, G.https://doi.org/10.48550/arXiv.2401.17966A non-homogeneous semi-Markov model for interval censoring, 1-21. ArXiv.org. van Lieshout, M.-C. & Markwitz, R. L.
2023
Data-driven chimney fire risk prediction using machine learning and point process tools, 3088-3111. Lu, C., van Lieshout, M.-C., de Graaf, M. & Visscher, P.https://doi.org/10.1214/23-AOAS1752Optimal decision rules for marked point process models, 1-14. ArXiv.org. van Lieshout, M.-C.https://doi.org/10.48550/arXiv.2309.03752State estimation for aoristic models, 1068-1089. van Lieshout, M.-C. & Markwitz, R. L.https://doi.org/10.1111/sjos.12619Exploring Seismic Hazard in the Groningen Gas Field Using Adaptive Kernel Smoothing (E-pub ahead of print/First online). van Lieshout, M.-C. & Baki, Z.https://doi.org/10.1007/s11004-023-10081-x

Research profiles

Address

University of Twente

Zilverling (building no. 11), room 4029
Hallenweg 19
7522 NH Enschede
Netherlands

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