Integreat PhD Fellow
University of Oslo, Department of Mathematics
Academic interests
Current interests are mainly Bayesian statistics, with a focus on variational inference, simulation-based inference and prior specification for Bayesian neural networks. Previously, he has worked on variance decompositions in Bayesian GLMMs using INLA for assessing biological traits.
Background
August holds five year masters degree (siv.ing) in Applied Physics and Mathematics at the Norwegian University of Science and Technology (NTNU), with a particular focus on statistics and mathematical modeling. His masters thesis was written under the supervision of Stefanie Muff.
PhD project
“Sparse models for machine learning from a Bayesian viewpoint”
He will explore ways to improve prior specification and/or shrinkage methods to form Bayesian models that are encouraged to be sparse. Pruning algorithms and statistical properties of these Bayesian models will be of particular interest.