Spring 2027: Lecturer for "Regression Analysis"
Fall 2026: Lecturer for "Portfolio Theory and Risk Management"
Spring 2026: Lecturer for "Regression Analysis"
01/2026 – present: Supervision and examiner of Master theses
Fall 2024: Lecturer for "Theory of Statistical Inference" and "Statistical Learning"
Spring 2024: Lecturer for "PhD course in Mathematical Statistics"
Fall 2023: Lecturer for "Bayesian Methods" and "Statistical Learning"
2023 – 2025: Supervision and examiner of Bachelor and Master theses
Fall 2022: "Linear Algebra and Geometry I" course assistant and teaching of exercise classes
Spring 2022: "Statistical methods for Biologists", exercise classes
Fall 2021: Lecturer for "Multivariate Extreme Value Theory"
Spring 2021: Lecturer for "Introduction to Extreme Value Theory and its Applications"
Fall 2020: Analysis 3 course assistant and teaching of exercise classes
Spring 2020: Analysis 2 course assistant and teaching of exercise classes
Sept. 2018: Mini-course on "Random Matrix Theory with Heavy Tails" at the "Stochastics Workshop" organized by Ruhr University Bochum
2017 – 2018:
Tutor for "Linear Algebra", "Analysis", "Introduction to Probability Theory", and "Advanced Probability Theory" (4x)
Partial teaching of "Stochastic Calculus" (Main course responsible: Mark Podolskij)
Member in examination committees
2014 – 2017:
Teaching assistant for "Quantitative Risk Management" (3x)
Preparation and grading of written assignments
Member in examination committees
Spring 2013: Tutor for "Risk Management in Finance and Insurance"
2024: Felix Seo. "Phase transitions for linear spectral statistics of high-dimensional sample correlation matrices"
2024: Martin Andersson. "Comparing Cox regression and flexible parametric survival models on healthcare data"
2026: Ingunn Lilja Bergsdottir. "The Classic Cox or the Counterfactual Potential Outcome? A Simulation Study of Treatment Effects in Survival Analysis"
2026: Max Brehmer. "Multidimensional change point detection using likelihood ratio statistics"
2026: Skjöldur Orri Eyjólfsson. "Simulating Inflation Risk in Icelandic Inflation-Indexed Mortgages"
2026: Eskil Billsten. "Reconstructing Spatial Structure in Noisy Spatial Graphs"
2026: Ceasar Linus Malki. "Statistical Analysis and Modelling of Fuel Consumption in Sweden"
2026: Noah Eriksson Tewolde Berhane. "Data-Driven Modeling of Machine Failure Risk in Passenger Cars"
2022–2023: Maja Egger. "A characterization of extreme value copulas via tail dependence coefficients"
2023: Alexander Käll. "Navigability of configuration model graphs"
2023: Esma Özdolap. "Which factor or factors influence high school students most to choose to study further"
2023: Emma Romero-Hamrin. "Logistic regression of alcohol consumption based on life factors"
2024: Sam Linderoth. "Bayesian portfolio optimization: out-of-sample performance of the market portfolio"
2024: Liliya Trila. "A comparative study of binary classification performance with logistic regression, support vector machines and artificial neural networks"
2024: Xin Tang. "Comparative analysis of Bayesian logistic regression using Gibbs and Metropolis-Hastings sampling with diverse prior distributions"
2024: Markus Söderqvist. "Predictive Performance of AdaBoost and Random Forest in Binary Classification Tasks"
2024: August Jonasson. "Edgeworth Expansions for Studying Rate of Convergence towards Normality - with Applications to Variance-Stabilizing Transformations"
2024: Betty Frankl. "Tail Estimation: A Comparative Simulation Study of Extreme Value Theory and Importance Sampling"
2025: Fikrat Ibragimov. "A Comparative Performance Analysis of Random Forest and XGBoost in Regression for Various Noise Levels and Data Patterns"
2025: Morris Lundberg Allerholm. "Full stop: a statistical analysis on the effect of stop words on the appreciation of classical literature"
2025: Sherin Shabo. "Forecasting and Backtesting Value-at-Risk"
2025: Gustav Thorzén. "Comparison of Bayesian and ML predictive distributions"
2025: Pontus Masip. "Wavelet and Fourier Methods for Nonparametric Regression"
2025: Alexander Kostavelis. "Machine Learning for Football Betting"
2025: Gabriel Lindqvist. "A Comparative Study of Predictive Power in Football Match Outcomes"
2025: Ellinor Lindkvist. "Learning Concentric Circular Boundaries: A Simulation Study Comparing Neural Networks and Random Forests"
2025: Hedwig Nordlinder. "Geometrically Aware Markov Chain Monte Carlo"
2026: Arvand Jourabian. "Supervised Outlier Detection via Binary Classification: A Simulation Based Analysis"