Volker J Schmid is a professor of statistics with a focus on Bayesian statistics for image and spatial analysis. His research interest includes efficiency of Bayesian computational methods. Applications of these methods include medical imaging and microscopic imaging in biology, as well as traditional applications in spatial statistics like disease mapping.
He is leader of the Bayesian imaging and spatial statistics group at the Department of Statistics at LMU Munich. He is involved in several initiatives which link statistics and data science, including the Munich Center of Machine Learning.
PhD in Statistics, 2004
Diploma in Statistics, 2000
BAMP is a software package to analyze incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model.
Software for Analysing Data from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI), Cardiac Magnetic Resonance (CMR) imaging and functional Magnetic Resonance Imaging (fMRI).