The Bayesian Computational Statistics and Modeling group uses Bayesian methods to solve real-life challenges on a computationally efficient framework. We develop fundamental theory, methodology, computational frameworks as well as the end-user implementation in the R-INLA package under the leadership and guidance of Prof. Haavard Rue (also see here).

All our research is very exciting since we develop statistical products for use by scientists and practitioners, as complimentary to all methodology.

Some expository articles on important applications of our work can be found in KAUST Discovery and on founding work in a Royal Statistical Society feature.