For years 2014-2018 I have been granted 3,360,000 SEK (euro 380,000) from the Swedish research council for the interdisciplinary project "Statistical Inference and Stochastic Modelling of Protein Folding" (here is an accessible description) for which I am the
principal investigator, in collaboration with Kresten Lindorff-Larsen (Dept. Biology, Copenhagen University) and Julie Lyng Forman (Dept. Biostatistics, Copenhagen University).
In a preliminary work with Julie Forman we have considered the problem of estimating folding rates for some protein having a coordinate switching between the folded and unfolded state. We have proposed a new dynamical model (expressed as sum of two diffusions) and a quite fast computational strategy based on Approximate Bayesian Computation (ABC) that seems to work well and could be used in place of exact Bayesian inference, when large datasets do not allow for the latter. See also my research page for further details.
In 2015 I have been principal investigator for the creation of a study group in Bayesian methods at Lund University (SEK 100,000).
The study group has organized a number of well attended acivities during year 2016 for the promotion and understanding of Bayesian modelling.
More information here.
In 2013 the Faculty of Science at Lund University awarded me 100,000 SEK (euro 12,000) for the project “A software for fitting general state–space multidimensional models”. I coded abc-sde which is a MATLAB package performing Approximate Bayesian Computation to estimate parameters in stochastic models having dynamics defined by stochastic differential equations (SDEs). Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. See also my software page.