Natural Born Bayesian.
I am Professor of Statistics at Stockholm University. I enjoy doing research and teaching about Bayesian statistical methods. My work often focuses on prediction and decision making, and I like to think about computational aspects of the methods that I develop.
Click to learn a little more about my professional life, and see below for links to publications and courses that I teach.
I develop computationally efficient Bayesian methods for inference, prediction and decision making with flexible probabilistic models. I try to keep an updated list of my research papers and links to preprints or journal versions.
I teach master or PhD level courses in Bayesian Statistics and Machine Learning. I keep all my course material public on github, including source files for code and slides. You will find it all linked from each course here.
I supervise PhD students and mentor post docs. Meet past and current students, and my academic ancestors in the Mathematics Genealogy project.
Some things that have kept me busy lately.