Bayesian methods

I am very interested in researching computational methods for Bayesian inference. For example approximate Bayesian computation (ABC), Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (aka particle filters) for Bayesian inference. More in general I am interested in likelihood-free inference for models having intractable likelihoods.

These interests are reflected in my publications and my blog posts.

Bayes Nordics

To ease the spread of information on events related to Bayesian methods, Bayesian data analysis and the practice of Bayesian analysis, I have created Bayes Nordics. This is a distribution-list that focusses on Bayesian-related events, activities and job-posts in the European Nordic countries (just because I happen to work in a Nordic country). Please join in! It’s free!

Study group in Bayesian methods at Lund University

In 2015-16 I have coordinated a group “to advance the understanding and use of Bayesian methodology for the quantification and communication of uncertainty at Lund University.” We organized many activities and workshops, all available at this page.