Geir-Arne Fuglstad
Professor of Statistics
Department of Mathematical Sciences
Norwegian University of Science and Technology
Contact Information
Address: |
Department of Mathematical Sciences
NTNU
NO-7491 Trondheim
Norway
|
Office: |
1036, Sentralbygg 2 |
Phone: |
+47 73 59 16 99 |
Email: |
geir-arne.fuglstad@ntnu.no |
Research Activities
Interests
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Spatial and spatio-temporal modelling
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Stochastic modeling with stochastic partial differential equations (SPDEs)
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Finite element methods and finite volume methods applied to SPDEs
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Non-stationary spatial and spatio-temporal modelling
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Computational statistics
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INLA (Integrated Nested Laplace Approximations)
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Spatio-temporal estimation of demographic and health indicators
Software
GitHub: gafuglstad
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SUMMER: Spatio-temporal estimation of demographic and health indicators using household surveys.
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makemyprior : Intuitive construction of intepretable joint priors for variance parameters.
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GeoAdjust : Geostatistical inference for DHS data (under intential random displacement).
Grants
Major Collaborations
Awards and Honors
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The Royal Norwegian Society of Sciences and Letters' scientific award to young researchers. Awarded by the Royal Norwegian Society of Sciences and Letters in the category Natural Sciences in 2022.
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Sverdrup Award to Young Researcher. Awarded by Norwegian Statistical Association in 2017.
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Norwegian Computing Center's Master's Prize in Mathematics and ICT. Awarded by Norwegian Computing Center in 2011.
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Stubban Prize (Stubbanprisen). Awarded by Department of Mathematical Sciences, NTNU, in 2011.
Preprints
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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)
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John Paige, Geir-Arne Fuglstad, and Andrea Riebler. (2024). A joint model for DHS and MICS surveys: Spatial modeling with anonymized locations. (arXiv preprint)
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Umut Altay, John Paige, Andrea Riebler, and Geir-Arne Fuglstad. (2022). Accounting for Spatial Anonymization in DHS Household Surveys. (arXiv preprint)
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Geir-Arne Fuglstad, Zehang Richard Li, and Jon Wakefield. (2021). The Two Cultures for Prevalence Mapping: Small Area Estimation and Spatial Statistics. (arXiv preprint)
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Zehang Richard Li, Bryan D Martin, Tracy Qi Dong, Geir-Arne Fuglstad, John Paige, Andrea Riebler, Samuel Clark, and Jon Wakefield. (2020). Space-Time Smoothing of Demographic and Health Indicators using the R Package SUMMER. (arXiv preprint)
Reports
2021
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Yunhan Wu, Zehang Richard Li, Benjamin K. Mayala, Houjie Wang, Peter Gao, Johnny Paige, Geir-Arne Fuglstad, Caitlin Moe, Jessica Godwin, Rose E. Donohue, Bradley Janocha, Trevor N. Croft, and Jon Wakefield (2021). Spatial Modeling for Subnational Administrative Level 2 Small-Area Estimation. DHS Spatial Analysis Reports No. 21. Rockville, Maryland, USA: ICF.
Peer-reviewed journal publications
2025
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Umut Altay, John Paige, Andrea Riebler, and Geir-Arne Fuglstad. (2025). Impact of Jittering on Raster- and Distance-based Geostatistical Analyses of DHS Data. Statistical Modelling, 25(1):55–74. (arXiv preprint)
2024
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Martin Outzen Berlid, and Geir-Arne Fuglstad. (2024). Non-stationary Spatio-Temporal Modeling Using the Stochastic Advection-Diffusion Equation. Spatial Statistics, 64. (arXiv preprint)
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Ingeborg Gullikstad Hem, Geir-Arne Fuglstad, and Andrea Riebler. (2024). makemyprior: Intuitive Construction of Joint Priors for Variance Parameters in R. Journal of Statistical Software, 110(3):1–39. (arXiv preprint)
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Umut Altay, John Paige, Andrea Riebler, and Geir-Arne Fuglstad. (2024). GeoAdjust: Adjusting for Positional Uncertainty in Geostatistial Analysis of DHS Data. The R journal. In press. (arXiv preprint)
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Martin Outzen Berlid, Yaolin Ge, Jo Eidsvik, Geir-Arne Fuglstad, Ingrid Ellingsen. (2024). Efficient 3D real-time adaptive AUV sampling of a river plume front. Frontiers in Marine Science, 10. (Journal version)
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Jiachen Zhang, Matthew Bonas, Diogo Bolster, Geir-Arne Fuglstad, and Stefano Castruccio. (2024). High Resolution Global Precipitation Downscaling with Latent Gaussian Models and Nonstationary SPDE Structure. Journal of the Royal Statistical Society: Series C, 73(1):65–81. (arXiv preprint)
2023
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Martin Outzen Berild, and Geir-Arne Fuglstad. (2023). Spatially Varying Anisotropy for Gaussian Random Fields in Three-Dimensional Space. Spatial Statistics, 55. (arXiv preprint)
2022
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John Paige, Geir-Arne Fuglstad, Andrea Riebler, and Jon Wakefield. (2022). Spatial Aggregation with Respect to a Population Distribution: Impact on Inference. Spatial Statistics, 51. (arXiv preprint)
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John Paige, Geir-Arne Fuglstad, Andrea Riebler, and Jon Wakefield. (2022). Bayesian Multiresolution Modeling of Georeferenced Data: An Extension of `LatticeKrig'. Computational Statistics and Data Analysis, 173. (arXiv preprint)
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Wenjing Hu, Geir-Arne Fuglstad, and Stefano Castruccio. (2022). A Stochastic Locally Diffusive Model with Neural Network-Based Deformations for Global Sea Surface Temperature. Stat, 11(1):e431:1–9. (published version)
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John Paige, Geir-Arne Fuglstad, Andrea Riebler, and Jon Wakefield. (2022). 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, 10(1):50–80. (arXiv preprint)
2021
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Ingeborg Gullikstad Hem, Maria Lie Selle, Gregor Gorjanc, Geir-Arne Fuglstad, and Andrea Riebler. (2021). Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge. Genetics, 217(3). (bioRxiv preprint)
2020
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Geir-Arne Fuglstad, and Stefano Castruccio. (2020). Compression of Climate Simulations with a Nonstationary Global Spatio-Temporal SPDE Model. Annals of Applied Statistics, 14(2):542–559. (DOI)
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Bo Huang, Xiangping Hu, Geir-Arne Fuglstad, Xu Zhou, Wenwu Zhao, and Francesco Cherubini. (2020). Predominant regional biophysical cooling from recent land cover changes in Europe. Nature Communications, 11, 1066. (DOI)
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Geir-Arne Fuglstad, Ingeborg Gullikstad Hem, Alexander Knight, Håvard Rue, and Andrea Riebler. (2020). Intuitive joint priors for variance parameters. Bayesian Analysis, 15(4):1109–1137. (arXiv preprint)
2019
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Jon Wakefield, Geir-Arne Fuglstad, Andrea Riebler, Jessica Godwin, Katie Wilson, Samuel J. Clark. (2019) Estimating Under Five Mortality in Space and Time in a Developing World Context. Statistical Methods in Medical Research, 28(9):2614–2634. (arXiv preprint)
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Geir-Arne Fuglstad, Daniel Simpson, Finn Lindgren, and Håvard Rue. (2019) Constructing Priors that Penalize the Complexity of Gaussian Random Fields. Journal of the American Statistical Association, 114(525):445–452. (arXiv preprint)
2018
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Haakon Bakka, Håvard Rue, Geir-Arne Fuglstad, Andrea Riebler, David Bolin, Elias Krainski, Daniel Simpson, and Finn Lindgren (2018). Spatial modelling with R-INLA: A review. WIREs Computational Statistics, 10(6):e1443. (arXiv preprint)
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Geir-Arne Fuglstad, and Julien Beguin (2018). Environmential mapping using Bayesian spatial modelling (INLA/SPDE): a reply to Huang et al. (2017), Science of the Total Environment. 624:596–598.
2017
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Julien Beguin, Geir-Arne Fuglstad, Nicolas Mansuy, and David Paré. (2017) Predicting soil properties in the Canadian boreal forest with limited data: comparison of spatial and non-spatial statistical approaches. Geoderma, 306:195–205.
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Anita J. Norman, Astrid V. Stronen, Geir-Arne Fuglstad, Aritz Ruiz-Gonzales, Jonas Kindberg, Nathaniel R. Street, and Göran Spong. (2017) Landscape relatedness: Detecting contemporary fine-scale spatial structure in wild populations. Landscape Ecology, 32(1):181–194.
2016
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Damaris K. Kinyoki, Ngianga-Bakwin Kandala, Samuel O. Manda, Elias T. Krainski, Geir-Arne Fuglstad, and Grainne M. Moloney. (2016) Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010. BMJ Open 2016, 6:3
2015
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Geir-Arne Fuglstad, Daniel Simpson, Finn Lindgren, and Håvard Rue. (2015) Does non-stationary data always require non-stationary random fields?. Spatial Statistics, 14C:505–531. doi:10.1016/j.spasta.2015.10.001 (arXiv preprint)
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Geir-Arne Fuglstad, Finn Lindgren, Daniel Simpson, and Håvard Rue. (2015) Exploring a New Class of Non-stationary Spatial Gaussian Random Fields with Varying Local Anisotropy. Statistica Sinica, 25:115–133. doi:10.5705/ss.2013.106w (arXiv preprint)
Other
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Umut Altay, John Paige, Andrea Riebler, and Geir-Arne Fuglstad. (2022). Spatial Modelling with Covariates for Survey Data with Positional Uncertainty. In Nicola Torelli, Ruggero Bellio, and Vito Muggeo (Eds.), Proceedings of the 36th International Workshop on Statistical Modelling (pp. 64–68). EUT Edizioni Università di Trieste.
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John Paige, Geir-Arne Fuglstad, Andrea Riebler, and Jon Wakefield. (2022). Aggregating from Point to Areal Prevalences: A Complete Population Model. In Nicola Torelli, Ruggero Bellio, and Vito Muggeo (Eds.), Proceedings of the 36th International Workshop on Statistical Modelling (pp. 274–279). EUT Edizioni Università di Trieste.
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Geir-Arne Fuglstad, Andrea Riebler, Jon Wakefield, Johnny Paige, Katie Wilson, and Tracey Dong. (2018) Contribution to discussion on discussion paper "From start to finish: a framework for the production of small area official statistics". Journal of Royal Statistical Society, Series A, 181(4):927–979.
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Geir-Arne Fuglstad (2011). Contribution to discussion on discussion paper "An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach" in Journal of Royal Statistical Society, Series B, 73(4):423–498.
Theses
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Geir-Arne Fuglstad (2015). Modeling Spatial Non-stationarity. Ph.D. thesis, NTNU (Online version)
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Geir-Arne Fuglstad (2011). Spatial Modelling and Inference with SPDE-based GMRFs. Master's thesis, NTNU (Online version)
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Geir-Arne Fuglstad (2010). Approximating Solutions of Stochastic Differential Equations with Gaussian Markov Random Fields. Master's specialization project, NTNU (Online version)
Supervision
PhD students
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Supervisor:
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Øyvind Auestad (2022–)
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Martin Outzen Berild (2024): "Modeling complex dependence structures in space and time using SPDEs"
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Umut Altay (2023): "Geostatistical Analysis of DHS Data: Accounting for Random Displacement of Survey Locations"
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Ingeborg Hem (2021): "Robustifying Bayesian Hierarchical Models Using Intuitive Prior Elicitation"
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Member of Doctoral Supervisory Committee:
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John Paige (2020, University of Washington): "Statistical Methods for Geospatial Modeling with Stratified Cluster Survey Data"
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Co-supervisor:
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Daniel Kjellevold (2023–)
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Simen Furset (2023–)
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Karina Lilleborge (2022–)
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Yaolin Ge (2024): "Adaptive Sampling of River Plume Fronts: Integrating Statistical Modeling and Autonomous Path Planning for Enhanced Oceanographic Exploration"
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Thea Roksvåg (2020): "Bayesian geostatistical two field models for combining data sources and exploiting short records: Applied to annual runoff interpolation in Norway"
Master students
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Supervisor:
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Jakob Heide (2024–):
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Elling Svee (2024–):
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Ine Daiwei Zhao (2024–):
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Johannes Tveit Gjerdåker (2024): "A comparison of Bayesian Kriging and DeepKriging"
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Jim Totland (2023): "Geostatistical Modeling under Positional Uncertainty"
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Petter Giørtz (2023): "Fast Spatial Multi-level Models for Small Area Estimation"
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Kristoffer Flaglien (2023): "Penalizing R2 Through Priors in Linear Regression and Poisson Regression"
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Karina Lilleborge (2022): "Multivariate Spatial Modeling using SPDEs with Application to Ocean Sampling"
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Vegard Kolaas (2022): "Penalised complexity priors in hierarchical models"
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Thakshina Tharmapalan (2021): "Accounting for the survey design in logistic regression: A case study of associations in neonatal mortality in Kenya"
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Christian Barkald (2021): "Model-Based Multiresolution Small Area Estimation"
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Julie Røste (2020): "The Importance of Mesh Resolution When Using the SPDE Approach"
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Mathias Isaksen (2020): "Comparing Global and Local Specification of Spatially Varying Anisotropy"
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Julie Wilberg (2020): "Predicting the Risk of Customers Redeeming Loans"
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Hedda Vik (2019): "Forecasting Child Mortality while Accounting for Complex Survey Designs"
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Marte Saghagen (2019): "A Comparison of Model-Based and Design-Based Methods for Spatial Modelling Using Complex Survey Data"
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Co-supervisor:
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Ingeborg Hem (2017): "A Statistical Approach to Spatial Mapping of Temperature Change"
Bachelor students
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Supervisor:
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Magnus Engstrøm (2024): "Comparing Gaussian Process Regression to Random Ensemble Deep Spatial Learning"
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Martin Emil Pettersen (2022): "Computationally Efficient Spatial Statistics with Stochastic Differential Equations"
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Jonas Nordstrøm (2022): "Non-parametric Regression in Machine Learning: A Comparison of the Probabilistic and Algorithmic Approach"
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Simen Furset (2021): "Stationary Gaussian Stochastic Processes"
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Andreas Matre (2020): "Linear Regression for Survey Data"
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Louise Bauer-Nilsen (2020): "Analysing Nested Data with Multilevel Models"
Conferences
Invited
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GEOMED 2024, Hasselt, Belgium. September 9–11, 2024.
Talk on "Addressing Positional Anonymisation in Geostatistial Analyses of DHS Data"
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Current Frontiers in Gaussian Processes, Digital and University of Bern, Switzerland. August 24–26, 2022.
Talk on "Non-stationary Global Spatio-Temporal Modelling Using SPDEs"
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GEOMED 2019, Glasgow, UK. August 27–29, 2019.
Talk on "Disease mapping using complex survey data"
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Det 19. norske statistikermøtet, Fredrikstad, Norway. June 13–15, 2017.
- Sverdrup lecture on "Spatial Non-stationarity with Varying Anisotropy"
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Smögen Workshop 2016, Smögen, Sweden. August 15–18, 2016.
- Talk on "Constructing sensible priors for spatial fields"
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Nordstat 2016, Copenhagen, Denmark. June 27–30, 2016.
- Talk on "A New Prior that Penalises the Complexity of Stationary and Non-stationary Spatial Fields"
Contributed/Attended
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Workshop on PDEs, Spatio-Temporal Statistics, and Data-Driven Methods in Neuroscience and Fluid Mechanics, Trondheim, Norway, March 12–14, 2024.
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Trondheim Symposium in Statistics 2023, Trondheim, Norway. October 27, 2023.
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NORDSTAT 2023, Gothenburg, Sweden. June 19–22, 2023.
Talk on "Spatially Varying Anisotropy In Three Dimensons With Applications To Adaptive Oceanographic Sampling"
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Trondheim Symposium in Statistics 2022, Bårdshaug, Norway. October 28–29, 2022.
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Trondheim Symposium in Statistics 2021, Blekstad, Norway. November 5–6, 2021.
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ISBA 2021 World Meeting, online. June 28–July 2, 2021.
Talk on "Spatio-Temporal Estimation of Demographic and Health Indicators From Household Surveys"
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NORDSTAT 2021, Tromsø, Norway, and online. June 21–24, 2021.
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12th Trondheim Symposium in Statistics, Scandic Lerkendal, Trondheim, Norway. September 25, 2020.
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Autumn meeting on latent Gaussian models 2016, Trondheim, Norway. November 10–11, 2016.
- Talk on "Efficient posterior sensitivity calculations with INLA"
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ISBA 2016 World Meeting, Sardinia, Italy. June 13–17, 2016.
- Poster on "Penalised Complexity Priors for Gaussian Random Fields"
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Autumn meeting on Latent Gaussian Models 2015, Norwegian University of Science and Technology, Trondheim, Norway. September 17–18, 2015.
- Member of the organizing committee
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10th Conference on Bayesian Nonparametrics, North Carolina State University, Raleigh, North Carolina, the US. June 22–26, 2015.
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Mathematical and Statistical Analysis of Spatial Data, Workshop at Department of Mathematical Sciences, Aalborg University, Aalborg, Denmark. June 1–3, 2015.
- Poster on "Penalised Complexity Priors for Gaussian Random Fields"
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Sub-Saharan Conference on Spatial Statistics, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa. November 19–20, 2014.
- Talk on "Sensible Priors on the Hyperparameters for Gaussian Random Fields in the Matérn Family"
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Seventh Trondheim Symposium in Statistics, Selbu, Norway. October 17–18, 2014.
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Sixth Trondheim Symposium in Statistics, Selbu, Norway. October 18–19, 2013.
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The Third Workshop on Bayesian Inference for Latent Gaussian Models with Applications, Reykjavik, Iceland. September 12–14, 2013.
- Talk on "Non-stationary Spatial Modelling with Application to Spatial Prediction of Precipitation"
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Fifth Trondheim Symposium in Statistics, Selbu, Norway. October 19–20, 2012.
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24th Nordic Conference in Mathematical Statistics, Umeå, Sweden. June 10–14, 2012.
- Talk on "Spatial modelling and Inference with SPDE-based Gaussian Markov Random Fields"
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The Second Workshop on Bayesian Inference for Latent Gaussian Models with Applications, Trondheim, Norway. May 30 to June 1, 2012.
- Poster on "Spatial modelling and Inference with SPDE-based Gaussian Markov Random Fields"
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Fourth Trondheim Symposium in Statistics, Selbu, Norway. October 14–15, 2011.
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The 16th Norwegian Statistical Conference, Røros, Norway. June 14–17, 2011.
- Short talk about master's thesis
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Workshop in Bayesian Inference for Latent Gaussian Models, Zurich, Switzerland. February 2–5, 2011.
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Third Trondheim Symposium in Statistics, Selbu, Norway. October 15–16, 2010.
Popular Science Talks
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Researchers' Night 2021, Trondheim, Norway. September 24, 2021. Event for high school students with goal to promote university studies and careers in research.
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Talk on "Regional barnedødelighet i Afrika – ingen skal utelates!"
Other Invited Talks
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Colloquium, Institute of Mathematical Statistics and Actuarial Science, University of Bern, Switzerland. November 3, 2023.
- Non-stationary Spatio-Temporal Modelling with Applications to Autonomous Sampling
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Norwegian Computing Center, Oslo, Norway. June 4, 2018.
- Modelling Non-stationarity in the Spatial
Dependence Structure
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King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. May 1, 2017.
- Sensitivity Analysis for Posteriors in INLA
Summer Schools
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Pan-American Advanced Study Institute on Spatio-Temporal Statistics, Búzios, RJ, Brazil. June 16–26, 2014
- Nonstationary workshop, June 18–21
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Ten Lectures on Statistical Climatology, Seattle, USA. Course by Douglas Nychka at University of Washington. August 6–8, 2012
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ABS - 2011 Applied Bayesian Statistics School on Hierarchical Modeling for Environmental Processes, Bolzano, Italy. Course by Alan Gelfand. June 20–24, 2011.
Professional activities
Administrative work
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Member of the study programme council for Applied Physics and Mathematics (Fysikk og matematikk). 2023–.
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Committee for the study specialization "Industrial Mathematics", NTNU. (Studieretningsutvalget for Industriell Matematikk).
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Leader (2022–).
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Member (2021–2022).
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Study councelling for Industrial Mathematics (2022–).
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Approval of statistics courses for exchange stays (Industrial Mathematics programme, NTNU). 2021–.
Meetings
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Organizing committee for Workshop on PDEs, Spatio-Temporal Statistics, and Data-Driven Methods in Neuroscience and Fluid Mechanics, Trondheim, Norway. March 12–14, 2024.
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Co-organizer for 12th Trondheim Symposium in Statistics 2020, Scandic Lerkendal, Trondheim, Norway. September 25, 2020.
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Organizing committee for Autumn meeting on Latent Gaussian Models 2015, Norwegian University of Science and Technology, Trondheim, Norway. September 17–18, 2015.
Other
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PhD evaluation committees
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King Abdullah University of Science and Technology (2024)
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Norwegian University of Science and Technology (2023)
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Mines Paris - PSL (2023)
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University of Washington (2020)
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Hasselt University (2020)
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Norwegian University of Science and Technology (2020)
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Lund University (2019)
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Treasurer, Norwegian Statistical Association, Trondheim Division. 2011–.
Teaching activities
Courses
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TMA4250 - Spatial Statistics, Spring 2024
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TMA4250 - Spatial Statistics, Spring 2023
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TMA4240 - Statistics, Fall 2022 (course development)
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TMA4265 - Stochastic Modelling, Fall 2022 (partially teaching and partially mentoring)
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TMA4250 - Spatial Statistics, Spring 2022
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MA8001 - Mathematical Sciences Seminar for PhD-students, Fall 2021: Seminar-based course on survey statistics and small area estimation
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TMA4265 - Stochastic Modelling, Fall 2021
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TMA4245 - Statistics, Spring 2021
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TMA4265 - Stochastic Modelling, Fall 2020
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TMA4245 - Statistics, Spring 2020
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TMA4265 - Stochastic Modelling, Fall 2019
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TMA4240 - Statistics, Fall 2016
Short Courses
- A Practical Introduction to Bayesian inference using R-INLA at Lund University, Sweden. April 14–15, 2016
- Co-instructed with Jingyi Guo
- INLA Pre-conference Workshop at Sub-Saharan Conference on Spatial Statistics. School of Public Health, University of the Witwatersrand, Jonhannesburg, South Africa. November 17–18, 2014
- Co-instructed with Elias Teixeira Krainski
- INLA Workshop at CANSSI Workshop – Advancements to State-Space Models for Fisheries Science at Fields Institute, Toronto, Canada. May 30, 2014
- Informal short course on R-INLA at LEG at UFPR, Curitiba, Paraná, Brazil. November 25–29, 2013
- Co-instructed with Håvard Rue
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R-INLA Workshop at KEMRI Wellcome Trust, Kilifi, Kenya. October 3–5, 2013.
- Co-instructed with Janine Illian
Background
Academic
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2022–: Professor of Statistics at the Department of Mathematical Sciences, NTNU.
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2019–2022: Associate Professor of Statistics at the Department of Mathematical Sciences, NTNU.
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2015–2018: Post.doc. at the Department of Mathematical Sciences, NTNU.
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2011–2015: Ph.D. at the Department of Mathematical Sciences, NTNU.
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2006–2011: Master of Science in Applied Physics and Mathematics at NTNU.
Research Stays
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2017–2018: Visiting Scientist at the Department of Statistics, University of Washington, Seattle, Washington, USA. 7 months.
International competitions
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2010: Northwestern Europe Regional Contest (NWERC) in Bremen, Germany.
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2009: Northwestern Europe Regional Contest (NWERC) in Nürnberg, Germany.
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2008: Northwestern Europe Regional Contest (NWERC) in Utrecht, the Netherlands.
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2007: International Mathematics Competition
for University Students in Blagoevgrad, Bulgaria.
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2006: The International Physics Olympiad in Singapore, Singapore.
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2006: The final of the Norwegian Physics Olympiad.
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2006: The final of the Norwegian Chemistry Olympiad.