Ingelin Steinsland
Ingelin Steinsland
Professor. Vice Dean of research
Department of Mathematical Sciences Faculty of Information Technology and Electrical EngineeringBackground and activities
Ingelin Steinsland (1974) is professor at the Department of Mathematical Sciences. She is a member of the the Statistics group. Professor Steinsland has a MSc in Industrial Mathematics and a PhD in Statistics from NTNU. She is the Vice Dean of research at the Faculty of Information Technology and Electrical Engineering.
Research
Aim of research: Ingelin Steinsland aims to introduce new statistical methods and knowledge to applied scientists, and develop statistical methods and knowledge based on problems from applied scientists. She has a special focus on models and methods for large datasets, dependecies and uncertainty . Steinsland has some key interests; forecasting for physical systems, especially hydrology, quantitative genetics and citizen science. Recently she has been involved in NTNU's initativ on Covid 19.
Work Experience
- 2017- Vice Dean of research, Faculty of Information Technology and Electrical Engineering, NTNU
- 2014- Professor of Statistics, Dept. of Mathematical Sciences, NTNU
- 2008-2014 Associate Professor, Dept. of Mathematical Sciences, NTNU
- 2008- Advisor, SINTEF Energy Research (part time)
- 2006-2007: Researcher SINTEF Energy Research
- 2004-2006 Post Doctor, Dept.of Mathematical Sciences, NTNU. Project: Markov chain Monte Carlo methods in quantitative genetics
- 2003-2004 Associate Professor (temporary), Dept. of Mathematical Sciences, NTNU
- 1998-1999 Software developer in a start-up (VoxelVision AS)
Visiting researcher
- 2009-2010 Visiting scholar at Department of Statistics, Stanford University, USA
- 2009-2010 Visiting professor at SAMSI/Duke University, North Carolina, USA
- 2001-2002 Visiting post graduate at Department of Statistics, Trinity College, Ireland
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
Journal publications
- (2022) A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird abundance in mid-Scandinavia. Journal of Agricultural Biological and Environmental Statistics.
- (2022) Quantile based modeling of diurnal temperature range with the five-parameter lambda distribution. Environmetrics.
- (2021) Journal of the Royal Statistical Society: Series C (Applied Statistics) Journal of the Royal Statistical Society: Series C (Applied Statistics) ORIGINAL ARTICLE Open Access A two-field geostatistical model combining point and areal observations—A case study of annual runoff predictions in the Voss area. The Journal of the Royal Statistical Society, Series C (Applied Statistics).
- (2021) A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird populations in mid-Scandinavia. arXiv.org.
- (2021) Repeatability in a multiphase pipe flow case study. International Journal of Multiphase Flow. vol. 147.
- (2021) Closure Law Model Uncertainty Quantification. International Journal for Uncertainty Quantification.
- (2020) Accounting for spatial varying sampling effort due to accessibility in Citizen Science data: A case study of moose in Norway. Spatial Statistics.
- (2020) Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework. Hydrology and Earth System Sciences. vol. 24.
- (2020) Hierarchical Modelling of Haplotype Effects on a Phylogeny. Frontiers in Genetics. vol. 11.
- (2020) Spatial modelling improves genetic evaluation in smallholder breeding programs. Genetics Selection Evolution. vol. 52 (1).
- (2020) Uncertainty propagation through a point model for steady-state two-phase pipe flow. Algorithms. vol. 13 (3).
- (2019) Twenty-three unsolved problems in hydrology (UPH) – a community perspective. Hydrological Sciences Journal. vol. 64 (10).
- (2019) Streamflow forecast sensitivity to air temperature forecast calibration for 139 Norwegian catchments. Hydrology and Earth System Sciences. vol. 23 (2).
- (2019) Flexible modelling of spatial variation in agricultural field trials with the R package INLA. Theoretical and Applied Genetics. vol. 132 (12).
- (2018) Benefits of spatiotemporal modeling for short-term wind power forecasting at both individual and aggregated levels. Environmetrics. vol. 29 (3).
- (2017) Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction. Weather and forecasting. vol. 32 (6).
- (2016) Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway. Journal of Hydrology. vol. 536.
- (2016) Is my study system good enough? A case study for identifying maternal effects. Ecology and Evolution. vol. 6 (11).
- (2016) Spatial modeling with system of stochastic partial differential equations. Wiley Interdisciplinary Reviews: Computational Statistics. vol. 8 (2).
- (2015) Weather SDM: estimating snow density with high precision using snow depth and local climate. Hydrology Research. vol. 46 (4).