Position: Head of research unit

Office hours: by appointment

Contact: Wiedner Hauptstraße 8-10, 4th floor, yellow area, A - 1040 Wien

• Model selection in econometrics and statistics
• Inference after model selection
• Lasso methods, shrinkage estimators
• Geometric aspects in penalized estimation

• Ph.D. (Applied Mathematics) University of Colorado at Boulder, 2003
• Mag.rer.nat. (M.Sc., Mathematics), University of Vienna, 1999

• Associate Professor, Institute of Statistics and Mathematical Methods in Economics, TU Wien, 2015 -
• Assistant Professor, Institute of Mathematical Methods in Economics, TU Wien, 2011 - 2015
• Junior Professor, Institute for Mathematical Stochastics, University of Göttingen, 2009 - 2011
• Assistant Professor (non-tenure track), Department of Statistics, University of Vienna, 2006 - 2009
• Postdoc, National Center for Atmospheric Research (NCAR), Boulder, Colorado, 2003 - 2005

• Editor-in-Chief for Statistical Papers.

• Econometrics for Business Informatics (VU)
• Microeconometrics (VO)
• Microeconometrics (UE)
• Seminar in Econometrics with seminar paper (SE)
• Project with Bachelor Thesis (Econometrics) (PR)

Preprints

• P. Kramlinger, T. Krivobokova and U. Schneider, Uniformly Valid Inference Based on the Lasso in Linear Mixed Models; arXiv:2204.03887.
• P. Graczyk, U. Schneider, T. Skalski and P. Tardivel, Pattern Recovery by Penalized and Thresholded Estimation and its Geometry; hal:03262087.

Journal articles

• U. Schneider and P. Tardivel, The Geometry of Uniqueness, Sparsity and Clustering in Penalized Estimation; Journal of Machine Learning Research 23 (2022), 1 - 36.
• N. Amann and U. Schneider, Uniform Asymptotics and Confidence Regions Based on the Adaptive Lasso with Partially Consistent Turning; forthcoming in Econometric Theory.
• K. Ewald and U. Schneider, On the Distribution, Model Selection Properties and Uniqueness of the Lasso Estimator in Low and High Dimensions; Electronic Journal of Statistics 14 (2020)  944 - 969.
• K. Ewald and U. Schneider, Uniformly Valid Confidence Sets Based on the Lasso; Electronic Journal of Statistics 12 (2018) 1358 - 1387.

Full publication list (pdf), opens a file in a new window