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 involved 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. The methods and software were used to produce official subnational under-five mortality estimates for 1990-2019 in close coordination with the United Nations Inter-agency Group for Mortality Estimation (UN IGME).

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 methods are available in the R-package makemyprior.

See here for more details.

Scientific, academic and artistic work

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

2021

2020

2019

2018

2017

2016

2015