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Humboldt-Universität zu Berlin | School of Business and Economics | News | Archive | 2019 | Nadja Klein receives funding from DFG’s Emmy Noether Programme

Nadja Klein receives funding from DFG’s Emmy Noether Programme

Third Emmy Noether Group in economics since the launch of the funding programme


Our School member Nadja Klein, Junior Professor of Applied Statistics, receives funding from DFG’s prestigious Emmy Noether Programme to establish her own junior research group. Together with her funded team of a postdoc and a doctoral student, Nadja Klein will develop a general framework of statistical methods and inferential techniques for a wide range of big-data applications, such as in economics (e.g. marketing), or natural and life sciences (e.g. weather forecast, chronic diseases).

The funded project will develop statistical tools for flexible high-dimensional regression models, as well as necessary scalable estimation methods. Proposing an explicit link between Bayesian probabilistic approaches and algorithms in machine learning, the research programme aims to develop more efficient statistical learning algorithms to estimate models for huge data sets. To obtain more accurate regression models for the entire distribution (instead of only the mean) simultaneously, new distributional models based on copulas and transformation models in combination with variable and shrinkage methods will be constructed for univariate as well as multivariate responses.

DFG’s Emmy Noether Programme gives exceptionally qualified early-career researchers (postdocs and junior professors with temporary contracts who are at an early stage in their research careers) the chance to qualify for a full professorship at a university by leading an independent junior research group for a period of six years (with an interim evaluation after three years). Nadja Klein’s group will be the third funded Emmy Noether Group in economics since the launch of the funding programme. Thus, DFG’s decision is a great success for Nadja Klein and our School.