Volker J Schmid

Volker J Schmid is a Professor of Bayesian Imaging and Spatial Statistics at the Department of Statistics, Ludwig Maximilian University of Munich. He leads the Bayesian Imaging and Spatial Statistics group and contributes to interdisciplinary initiatives like the Munich Center of Machine Learning. His work bridges statistical theory with applications in medical imaging and biology.

• PhD in Statistics (2004), LMU Munich
• Diploma in Statistics (2000), LMU Munich
• Abitur, Joseph-von-Fraunhofer-Gymnasium Cham (1993)

His research focuses on Bayesian computational methods for high-dimensional data, particularly in medical imaging (MRI, DCE-MRI) and biological microscopy (e.g., 3D nuclear architecture analysis via super-resolution microscopy). Key applications include disease mapping, image segmentation, and spatio-temporal modeling. His software tools (e.g., nucim, bioimagetools, BAMP) enable quantitative analysis in nuclear imaging and age-period-cohort modeling.

His 15 most recent publications span Bayesian modeling for medical imaging, spatio-temporal epidemiology, and computational biology. Topics include co-localization metrics in fluorescence microscopy, nuclear architecture analysis, and dynamic Bayesian frameworks for MRI data. Collaborations extend to neuroimaging, oncology, and nuclear biology.