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Full name: Marie-Colette van Lieshout
Formal name: Dr. M.N.M. van Lieshout
Function: Scientific Staff Member

Email: Marie-Colette.van.Lieshout@cwi.nl
Telephone: +31(0)20 592 4008
Room: M332
Homepage:  http://homepages.cwi.nl/~colette
Research groups: Stochastics


Research

Van Lieshout's research is in stochastic geometry and its applications, the branch of mathematics that concerns itself with modelling and analysing complicated geometrical structures. Important examples include point processes and random mosaics.

To indicate the range of application areas, Van Lieshout and her co-workers showed that random mosaics are useful prior models for Bayesian image segmentation, sequential point processes can be used to recognise and track moving objects, and space-time marked point processes are important tools in producing earthquake hazard maps.

Career

2013 Scientific staff member PNA2 - Probability and Stochastic Networks
2013 -  Scientific staff member ST - Stochastics
2007 - 2012 Scientific staff member PNA2 - Probability and Stochastic Networks
1997 - 2006 Scientific staff member PNA4 - Signals and Images
1994 - 1997 Lecturer University of Warwick
1990 - 1994 seconded BS4 - Image analysis and spatial stochastics
1990 - 1994 PhD student Free University Amsterdam
1989 - 1990 Junior staff member BS6 - Beeldanalyse

Recent Publications

K. Turkyilmaz, M.N.M. van Lieshout, A. Stein. Comparing the Hawkes and trigger process models for aftershock sequences following the 2005 Kashmir earthquake. Mathematical Geosciences 45, 149–164, 2013.
K. Turkyilmaz, M.N.M. van Lieshout, A. Stein. Comparing the Hawkes and trigger process models for aftershock sequences following the 2005 Kashmir earthquake. Mathematical Geosciences, 2013.
M.N.M. van Lieshout. An introduction to planar random tessellation models. Spatial Statistics 1, 40–49, 2012.
M.N.M. van Lieshout, A. Stein. Earthquake modelling at the country level using aggregated spatio-temporal point processes. Computational Geosciences 44, 309–326, 2012.
M.N.M. van Lieshout. On estimation of the intensity function of a point process. Methodology and Computing in Applied Probability 14, 567–578, 2012.

All publications (link to repository)

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