Tim van de Brug
My research focuses on high-dimensional statistics and data analysis. I have a special interest in medical imaging data and radiomics. I develop advanced statistical methodology and machine learning tools to extract relevant information from MRI/PET scans and predict disease progression and treatment response. For example, I am currently investigating how to select the optimal therapy for diffuse large B-cell lymphoma patients based on whole body PET-CT scans. My background is in theoretical mathematics; I have done research on probability theory and mathematical physics. In particular, I studied spatial properties of random networks and statistical mechanics models.
T. Klausch, P.M. van de Ven, T. van de Brug, M.A. van de Wiel, and J. Berkhof, Estimating Bayesian optimal treatment regimes for dichotomous outcomes using observational data, Submitted (2018). link
T. van de Brug, F. Camia, and M. Lis, Spin systems from loop soups, Electronic Journal of Probability 23 (2018), no. 81, 1-17. link
T. van de Brug, F. Camia, and M. Lis, Random walk loop soups and conformal loop ensembles, Probability Theory and Related Fields 166 (2016), no. 1, 553-584. link
T. van de Brug, Percolation, loop soups and stochastic domination, PhD Thesis Vrije Universiteit Amsterdam (2015). link