Geir-Arne Fuglstad

About

Professor of Statistics at the Department of Mathematical Sciences, and study programme leader for Applied Physics and Mathematics (MTFYMA).

Research

Interests

My main interests lie in spatio-temporal statistics, computational statistics, and stochastic partial differential equations (SPDEs). One key topic is the use of SPDEs for modelling and fast computations for spatio-temporal processes. I am interested in applications in a wide range of scientific fields from epidemiology and demography to physical sciences.

Projects

DIScover. This is a research collaboration between analysis of partial differential equations, numerical analysis, spatio-temperal statistics, and the fields of fluid mechanics, neuroscience and neurolinguistics. The project started in 2025.

Center for Health Equity Analytics (CHAIN). This is a Toppforsk@IE research group whose goal is to investigate the determinants of health inequity, generate deeper insights into its underlying causes, examine spatial variations in health equity across multiple scales, and advocate for targeted policy reforms that promote fairer and more equitable health outcomes.

IMod (Partial differential equations, statistics and data: An interdisciplinary approach to data-based modelling) This is an inter-disciplinary project building collaboration between statistics, partial differential equations, numerics, neuroscience, and fluid mechanics. The project started in autumn 2022.

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. The project started in autumn 2020.

SUMMER (Spatio-Temporal Under-Five Mortality Methods for Estimation). This is an R package where the target is to develop 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).

Preprints

Simen Knutsen Furset, Geir-Arne Fuglstad, and Espen R. Jakobsen. (2026). ARMA approximation of a Non-separable Spatio-Temporal Model with Fractional Smoothnesses in Space and Time. (arXiv preprint)
Alana McGovern, Geir-Arne Fuglstad, and Jon Wakefield. (2026). Sampling distributions for complex design variance estimators in a Fay-Herriot model. (arXiv preprint)
Elling Svee, and Geir-Arne Fuglstad. (2025). Non-stationary Spatial Modeling Using Fractional SPDEs. (arXiv preprint)
Øyvind Stormark Auestad, Geir-Arne Fuglstad, and Annika Lang. (2025). Surface finite element approximation of parabolic SPDEs with Whittle--Matérn noise. (arXiv preprint)
Øyvind Stormark Auestad, Geir-Arne Fuglstad, Espen Robstad Jakobsen, and Annika Lang. (2025). Finite element approximation of parabolic SPDEs with Whittle--Matérn noise. (arXiv preprint)
John Paige, Geir-Arne Fuglstad, and Andrea Riebler. (2024). A joint model for DHS and MICS surveys: Spatial modeling with anonymized locations. (arXiv preprint)
Umut Altay, John Paige, Andrea Riebler, and Geir-Arne Fuglstad. (2022). Accounting for Spatial Anonymization in DHS Household Surveys. (arXiv preprint)

PhD students

I am currently the co-supervisor of three PhD students:

Daniel Kjellevold (2023--): Working in the interface of spatial statistics and fluid mechanics
Simen Furset (2023--): Working in the interface between statistics and numerical analysis
Karina Lilleborge (2022--): Working on traffic analysis and spatio-temporal models on graphs.

Additional details

See here for more details.

DIScover

Research collaboration between analysis of partial differential equations, numerical analysis, spatio-temperal statistics, and the fields of fluid mechanics, neuroscience and neurolinguistics.

IMod: Partial differential equations, statistics and data: An interdisciplinary approach to data-based modelling

Inter-disciplinary project building collaboration between statistics, partial differential equations, numerics, neuroscience, and fluid mechanics.

MASCOT: Maritime Autonomous Sampling and Control

Inter-disciplinary project that aims to develop and design observational strategies in spatio-temporal domains, enabling autonomous platforms to increase our knowledge of dynamic environments like the upper water-column.

Publications

2026

Hu, Xiangping; Ballal, Vedant Pushpahas; Martinelli, Gabriele; Fuglstad, Geir-Arne; Nocente, Alessandro; Iacono, Roberto. (2026) Impacts of drought on electricity production, fossil carbon emissions, and air pollution in Europe. Energy Nexus
Academic article
Paulson, Katherine; Fuglstad, Geir-Arne; Li, Zehang Richard; Wakefield, Jonathan. (2026) Temporal models for estimation and short-term forecasting of neonatal mortality rates in sub-Saharan Africa. Annals of Applied Statistics
Academic article
Wakefield, Jon; Gao, Peter; Fuglstad, Geir-Arne; Li, Zehang Richard. (2026) The Two Cultures of Prevalence Mapping: Small Area Estimation and Model-Based Geostatistics. Statistical Science
Academic article

2025

Lilleborge, Karina; Martino, Sara; Fuglstad, Geir-Arne; Lindgren, Finn Kristian; Ingebrigtsen, Rikke. (2025) Joint Modelling of Line and Point Data on Metric Graphs. Spatial Statistics
Academic article
Li, Zehang Richard; Martin, Bryan D; Dong, Tracy Qi; Fuglstad, Geir-Arne; Godwin, Jessica; Paige, John Leonard. (2025) Space-Time Smoothing of Survey Outcomes using the R Package SUMMER. The R Journal
Academic article
Altay, Umut; Paige, John Leonard; Riebler, Andrea Ingeborg; Fuglstad, Geir-Arne. (2025) GeoAdjust: Adjusting for Positional Uncertainty in Geostatistial Analysis of DHS Data. The R Journal
Academic article

2024

Altay, Umut; Paige, John; Riebler, Andrea Ingeborg; Fuglstad, Geir-Arne. (2024) Impact of jittering on raster- and distance-based geostatistical analyses of DHS data. Statistical Modelling
Academic article
Hem, Ingeborg; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg. (2024) makemyprior: Intuitive Construction of Joint Priors for Variance Parameters in R. Journal of Statistical Software
Academic article
Berild, Martin Outzen; Fuglstad, Geir-Arne. (2024) Non-stationary spatio-temporal modeling using the stochastic advection–diffusion equation. Spatial Statistics
Academic article

2023

Zhang, Jiachen; Bonas, Matthew; Bolster, Diogo; Fuglstad, Geir-Arne; Castruccio, Stefano. (2023) High-resolution global precipitation downscaling with latent Gaussian models and non-stationary stochastic partial differential equation structure. Journal of the Royal Statistical Society, Series C (Applied Statistics)
Academic article
Berild, Martin Outzen; Fuglstad, Geir-Arne. (2023) Spatially varying anisotropy for Gaussian random fields in three-dimensional space. Spatial Statistics
Academic article
Berild, Martin Outzen; Ge, Yaolin; Eidsvik, Jo; Fuglstad, Geir-Arne; Ellingsen, Ingrid Helene. (2023) Efficient 3D real-time adaptive AUV sampling of a river plume front. Frontiers in Marine Science
Academic article

2022

Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2022) Bayesian multiresolution modeling of georeferenced data: An extension of ‘LatticeKrig’. Computational Statistics & Data Analysis
Academic article
Hu, Wenjing; Fuglstad, Geir-Arne; Castruccio, Stefano. (2022) A stochastic locally diffusive model with neural network-based deformations for global sea surface temperature. Stat
Academic article
Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2022) Spatial aggregation with respect to a population distribution: Impact on inference. Spatial Statistics
Academic article

2021

Wu, Yunhan; Li, Zehang Richard; Mayala, Benjamin K.; Wang, Houjie; Gao, Peter; Paige, John. (2021) Spatial Modeling for Subnational Administrative Level 2 Small-Area Estimation. ICF ICF
Report
Hem, Ingeborg Gullikstad; Selle, Maria; Gorjanc, Gregor; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg. (2021) Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge. Genetics
Academic article

2020

Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2020) Design- and Model-Based Approaches to Small-Area Estimation in a Low- and Middle-Income Country Context: Comparisons and Recommendations. Journal of Survey Statistics and Methodology
Academic article
Fuglstad, Geir-Arne; Castruccio, Stefano. (2020) Compression of Climate Simulations with a Nonstationary Global Spatio-Temporal SPDE Model. Annals of Applied Statistics
Academic article
Fuglstad, Geir-Arne; Hem, Ingeborg Gullikstad; Knight, Alexander; Rue, Håvard; Riebler, Andrea Ingeborg. (2020) Intuitive Joint Priors for Variance Parameters. Bayesian Analysis
Academic article
Huang, Bo; Hu, Xiangping; Fuglstad, Geir-Arne; Zhou, Xu; Zhao, Wenwu; Cherubini, Francesco. (2020) Predominant regional biophysical cooling from recent land cover changes in Europe. Nature Communications
Academic article

2018

Bakka, Haakon; Rue, Håvard; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Bolin, David; Illian, Janine B.. (2018) Spatial modelling with R-INLA: A review. Wiley Interdisciplinary Reviews: Computational Statistics
Academic literature review
Fuglstad, Geir-Arne; Julien, Beguin. (2018) Environmental mapping using Bayesian spatial modelling (INLA/SPDE): A reply to Huang et al. (2017). Science of the Total Environment
Reader opinion piece
Fuglstad, Geir-Arne; Simpson, Daniel; Lindgren, Finn; Rue, Håvard. (2018) Constructing Priors that Penalize the Complexity of Gaussian Random Fields. Journal of the American Statistical Association
Academic article
Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Godwin, Jessica; Wilson, Katie; Clark, Samuel J.. (2018) Estimating under-five mortality in space and time in a developing world context. Statistical Methods in Medical Research
Academic article

2017

Beguin, Julien; Fuglstad, Geir-Arne; Mansuy, Nicolas; Pare, David. (2017) Predicting soil properties in the Canadian boreal forest with limited data: Comparison of spatial and non-spatial statistical approaches. Geoderma
Academic article

2016

Kinyoki, Damaris K.; Kandala, Ngianga-Bakwin; Manda, Samuel O.; Krainski, Elias Teixeira; Fuglstad, Geir-Arne; Moloney, Grainne M.. (2016) Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010. BMJ Open
Academic literature review
Norman, Anita J.; Stronen, Astrid V.; Fuglstad, Geir-Arne; Ruiz-Gonzalez, Aritz; Kindberg, Jonas; Street, Nathaniel R.. (2016) Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations. Landscape Ecology
Academic article

2015

Fuglstad, Geir-Arne; Simpson, Daniel Peter; Lindgren, Finn Kristian; Rue, Håvard. (2015) Does non-stationary spatial data always require non-stationary random fields?. Spatial Statistics
Academic article
Fuglstad, Geir-Arne; Simpson, Daniel Peter; Lindgren, Finn Kristian; Rue, Håvard. (2015) Exploring a new class of non-stationary spatial Gaussian random fields with varying local anisotropy. Statistica sinica
Academic article

Journal publications

Hu, Xiangping; Ballal, Vedant Pushpahas; Martinelli, Gabriele; Fuglstad, Geir-Arne; Nocente, Alessandro; Iacono, Roberto. (2026) Impacts of drought on electricity production, fossil carbon emissions, and air pollution in Europe. Energy Nexus
Academic article
Paulson, Katherine; Fuglstad, Geir-Arne; Li, Zehang Richard; Wakefield, Jonathan. (2026) Temporal models for estimation and short-term forecasting of neonatal mortality rates in sub-Saharan Africa. Annals of Applied Statistics
Academic article
Wakefield, Jon; Gao, Peter; Fuglstad, Geir-Arne; Li, Zehang Richard. (2026) The Two Cultures of Prevalence Mapping: Small Area Estimation and Model-Based Geostatistics. Statistical Science
Academic article
Lilleborge, Karina; Martino, Sara; Fuglstad, Geir-Arne; Lindgren, Finn Kristian; Ingebrigtsen, Rikke. (2025) Joint Modelling of Line and Point Data on Metric Graphs. Spatial Statistics
Academic article
Li, Zehang Richard; Martin, Bryan D; Dong, Tracy Qi; Fuglstad, Geir-Arne; Godwin, Jessica; Paige, John Leonard. (2025) Space-Time Smoothing of Survey Outcomes using the R Package SUMMER. The R Journal
Academic article
Altay, Umut; Paige, John Leonard; Riebler, Andrea Ingeborg; Fuglstad, Geir-Arne. (2025) GeoAdjust: Adjusting for Positional Uncertainty in Geostatistial Analysis of DHS Data. The R Journal
Academic article
Altay, Umut; Paige, John; Riebler, Andrea Ingeborg; Fuglstad, Geir-Arne. (2024) Impact of jittering on raster- and distance-based geostatistical analyses of DHS data. Statistical Modelling
Academic article
Hem, Ingeborg; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg. (2024) makemyprior: Intuitive Construction of Joint Priors for Variance Parameters in R. Journal of Statistical Software
Academic article
Berild, Martin Outzen; Fuglstad, Geir-Arne. (2024) Non-stationary spatio-temporal modeling using the stochastic advection–diffusion equation. Spatial Statistics
Academic article
Zhang, Jiachen; Bonas, Matthew; Bolster, Diogo; Fuglstad, Geir-Arne; Castruccio, Stefano. (2023) High-resolution global precipitation downscaling with latent Gaussian models and non-stationary stochastic partial differential equation structure. Journal of the Royal Statistical Society, Series C (Applied Statistics)
Academic article
Berild, Martin Outzen; Fuglstad, Geir-Arne. (2023) Spatially varying anisotropy for Gaussian random fields in three-dimensional space. Spatial Statistics
Academic article
Berild, Martin Outzen; Ge, Yaolin; Eidsvik, Jo; Fuglstad, Geir-Arne; Ellingsen, Ingrid Helene. (2023) Efficient 3D real-time adaptive AUV sampling of a river plume front. Frontiers in Marine Science
Academic article
Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2022) Bayesian multiresolution modeling of georeferenced data: An extension of ‘LatticeKrig’. Computational Statistics & Data Analysis
Academic article
Hu, Wenjing; Fuglstad, Geir-Arne; Castruccio, Stefano. (2022) A stochastic locally diffusive model with neural network-based deformations for global sea surface temperature. Stat
Academic article
Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2022) Spatial aggregation with respect to a population distribution: Impact on inference. Spatial Statistics
Academic article
Hem, Ingeborg Gullikstad; Selle, Maria; Gorjanc, Gregor; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg. (2021) Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge. Genetics
Academic article
Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2020) Design- and Model-Based Approaches to Small-Area Estimation in a Low- and Middle-Income Country Context: Comparisons and Recommendations. Journal of Survey Statistics and Methodology
Academic article
Fuglstad, Geir-Arne; Castruccio, Stefano. (2020) Compression of Climate Simulations with a Nonstationary Global Spatio-Temporal SPDE Model. Annals of Applied Statistics
Academic article
Fuglstad, Geir-Arne; Hem, Ingeborg Gullikstad; Knight, Alexander; Rue, Håvard; Riebler, Andrea Ingeborg. (2020) Intuitive Joint Priors for Variance Parameters. Bayesian Analysis
Academic article
Huang, Bo; Hu, Xiangping; Fuglstad, Geir-Arne; Zhou, Xu; Zhao, Wenwu; Cherubini, Francesco. (2020) Predominant regional biophysical cooling from recent land cover changes in Europe. Nature Communications
Academic article
Bakka, Haakon; Rue, Håvard; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Bolin, David; Illian, Janine B.. (2018) Spatial modelling with R-INLA: A review. Wiley Interdisciplinary Reviews: Computational Statistics
Academic literature review
Fuglstad, Geir-Arne; Julien, Beguin. (2018) Environmental mapping using Bayesian spatial modelling (INLA/SPDE): A reply to Huang et al. (2017). Science of the Total Environment
Reader opinion piece
Fuglstad, Geir-Arne; Simpson, Daniel; Lindgren, Finn; Rue, Håvard. (2018) Constructing Priors that Penalize the Complexity of Gaussian Random Fields. Journal of the American Statistical Association
Academic article
Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Godwin, Jessica; Wilson, Katie; Clark, Samuel J.. (2018) Estimating under-five mortality in space and time in a developing world context. Statistical Methods in Medical Research
Academic article
Beguin, Julien; Fuglstad, Geir-Arne; Mansuy, Nicolas; Pare, David. (2017) Predicting soil properties in the Canadian boreal forest with limited data: Comparison of spatial and non-spatial statistical approaches. Geoderma
Academic article
Kinyoki, Damaris K.; Kandala, Ngianga-Bakwin; Manda, Samuel O.; Krainski, Elias Teixeira; Fuglstad, Geir-Arne; Moloney, Grainne M.. (2016) Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010. BMJ Open
Academic literature review
Norman, Anita J.; Stronen, Astrid V.; Fuglstad, Geir-Arne; Ruiz-Gonzalez, Aritz; Kindberg, Jonas; Street, Nathaniel R.. (2016) Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations. Landscape Ecology
Academic article
Fuglstad, Geir-Arne; Simpson, Daniel Peter; Lindgren, Finn Kristian; Rue, Håvard. (2015) Does non-stationary spatial data always require non-stationary random fields?. Spatial Statistics
Academic article
Fuglstad, Geir-Arne; Simpson, Daniel Peter; Lindgren, Finn Kristian; Rue, Håvard. (2015) Exploring a new class of non-stationary spatial Gaussian random fields with varying local anisotropy. Statistica sinica
Academic article

Report

Wu, Yunhan; Li, Zehang Richard; Mayala, Benjamin K.; Wang, Houjie; Gao, Peter; Paige, John. (2021) Spatial Modeling for Subnational Administrative Level 2 Small-Area Estimation. ICF ICF
Report

Teaching

Courses

Supervision

I supervise bachelor, project and master theses in statistics.

Outreach