Background and activities

Research

My main interests lie in spatio-temporal statistics and computational statistics. In particular, the use of stochastic partial differential equation (SPDE) models for fast computations with spatio-temporal processes. I am interested in applications in a wide range of scientific fields from epidemiology and demography to physical sciences.

From 2020 we are starting the project MASCOT (Maritime Autonomous Sampling and Control). This is an inter-disciplinary project that aims to develop and design observational strategies in spatio-temporal domains, enabling autonomous platforms to decide on a strategy of where and when to make measurements to increase our knowledge of dynamic environments like the upper water-column. 

I'm invoved in the development of the R-package SUMMER (Spatio-Temporal Under-Five Mortality Methods for Estimation), where the target is to take advantage of complex, but easy-to-use and computationally efficient methods for subnational mapping of under-five mortality in low- and medium-income countries. This work is lead by Jon Wakefield at the University of Washington, Seattle, USA.

I'm also interested in methodological development in Bayesian statistics, and I'm taking part in the project "Penalized Complexity-priors: A new tool to define default priors and robustify Bayesian models" (NFR), which is lead by Andrea Riebler at IMF, NTNU. This project aims to create a framework for specifying intuitive and robust joint priors for several variance parameters in a latent Gaussian model. The end goal is an R package that allows the developed framework to be easily used by all scientists fitting latent Gaussian models.

See here for more details.

Scientific, academic and artistic work

Displaying a selection of activities. See all publications in the database

2020

2019

2018

2017

2016

2015