Nadja Klein is an assistant professor of Applied Statistics at the School of Business and Economics at Humboldt-Universität zu Berlin. She 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.
- Statistical and Machine Learning
- Bayesian computational methods
- Advanced geoadditive regression modelling, model and variable selection