Umberto Picchini

Associate Professor, Mathematical Sciences

I am interested in statistical inference for stochastic modelling, and especially Bayesian computational methods. For example, I am interested in MCMC, sequential Monte Carlo (particle filters) and especially “likelihood-free” methods, such as approximate Bayesian computation (ABC). I have special interest in stochastic modelling (e.g. stochastic differential equations) and applications in biomedicine.

​A more detailed personal webpage is at https://umbertopicchini.github.io/

Sometimes I blog at https://umbertopicchini.wordpress.com/

You can follow me on Twitter at https://twitter.com/uPicchini

​I am PI for the VR funded project “Statistical inference and stochastic modelling of protein folding” (2013-5167). See a description at http://www.maths.lu.se/index.php?id=85411

​• Ongoing cooperation with Prof. Kresten Lindorff-Larsen (University of Copenhagen), Assoc. Prof. Julie Lyng Forman (University of Copenhagen) and PhD student Samuel Wiqvist (Lund University) on the VR funded project “Statistical inference and stochastic modelling of protein folding” (2013-5167). See a description at http://www.maths.lu.se/index.php?id=85411

• Ongoing cooperation with Assoc. Prof. Ingemar André (Lund University) on “Bayesian inference of self-assembly pathways of viruses”, an eSSENCE funded project.

​• In 2016 have created Bayes Nordics, a list to distribute news on events related to Bayesian analysis in the European nordic countries. You can join and contribute at https://sites.google.com/site/bayesnordics/

Published: Mon 14 May 2018. Modified: Tue 15 May 2018