Associated Member
Nadja Klein holds the Chair of Uncertainty Quantification and Statistical Learning at the Research Center Trustworthy Data Science and Security (UA Ruhr) and the Department of Statistics (Technische Universität Dortmund). Prior to this, she was an assistant professor of Applied Statistics at the School of Business and Economics at Humboldt-Universität zu Berlin.
Nadja has a diploma in Mathematics and Physics from the University of Hamburg (2012) and a PhD in Mathematics and Statistics from the Georg-August-University of Goettingen (2105, summa cum laude) for which she won two prices. From 2016 to 2018, Nadja Klein was a Feodor-Lynen fellow of the Alexander von Humboldt founda-tion hosted by the University of Melbourne. Recently, Nadja Klein was granted with a Emmy-Noether research group for excellent young researchers by the German research foundation (DFG).
The overarching goal of her research is to develop statistical methods for high-dimensional and complex problems or “big data”. She tries to combine the strengths of both Bayesian statistics and machine learning to develop statisti-cally informed models that address issues of nowadays real data problems.
Research Interests
- Statistical and Machine Learning
- Bayesian computational methods
- Advanced geoadditive regression modelling, model and variable selection
