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
In 2016 I have created Bayes Nordics, a mail list that focusses on Bayesian-related events, activities and job-posts in the European Nordic countries. It is actively maintained and keeps spreading info. Please join in! It’s free!
Bayesian computing without exact likelihoods 2023
I co-organized the workshop Bayesian computing without exact likelihoods 12-14 March 2023 in Levi (Finland), a satellite event of the BayesComp 2023 conference also held in Levi.
One World ABC seminars (2020–current)
Since 2020 I am a co-organizer of the One World online seminars on Approximate Bayesian Computation. All videos are available at the ISBA’s YouTube channel.
Bayes@Lund 2017
In 2017 I organized the conference Bayes@Lund, with Ullrika Sahlin. It was well attended by a general public and scholars from many different departments.
göBayes reading group
I have created a reading group in Göteborg, to discuss noteworthy Bayesian papers.
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, summarised in this document.