Research Research OverviewThe Bayesian Computational Statistics and Modeling group (BayesComp) at King Abdullah University of Science and Technology (KAUST) involves research focusing on the modeling, design, optimization, and performance analysis of Bayesian modeling techniques. The group strives to develop generic solutions to real-life challenges for use by scientists from all fields. A particular feature of all approaches is the ability to scale to large datasets.The methodologies and computational advances developed by the group is implemented in the R-INLA package (see http://www.r-inla.org).Current focus areas are:Spatio-temporal modelsSPDE approach to solving spatio-temporal challengesR-INLA in a High performance computingSurvival analysisBayesian fundamentalsParallelization of existing approaches in R-INLAMultiple endpoint models
