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Humboldt-Universität zu Berlin - Statistics

Applied Statistics

Research Interests

  • Bayesian Statistics
  • Computational Methods
  • Machine Learning
  • Distributional Regression
  • Smoothing Methods
  • Copula Modelling
  • Shrinkage Priors and Variable Selection


Prizes and Awards

  • since 2016 Member of the Humboldt network (Alexander von Humboldt Foundation)
  • 07/2016–06/2018 Feodor-Lynen-Fellowship for Postdoctoral Researchers of the Alexander von Humboldt Foundation (hosted at the University of Melbourne; host: Michael Stanley Smith)
  • 2016 NSF-ISBA Junior Travel Support Grant of the US National Science Foundation
  • 2015 Wolfgang-Wetzel-Price 2015 of the German Statistical Society for the paper ‘Bayesian Generalized AdditiveModels for Location, Scale and Shape for Zero-Inflated and Overdispersed Count Data’
  • 2014 Award of the Georg-August-Universitaet Gorttingen for outstanding dissertation ‘Bayesian Structured Additive Distributional Regression’
  • 2014 Award of the Universitaetsbund Goettingen for the dissertation ‘Bayesian Structured Additive Distributional Regression’
  • 10/2013–10/2014 Awarded Membership in the Dorothea Schloezer Mentoring Programme, Georg-August-Universitaet Göttingen


Topics for Theses

  • Deep distributional learning
  • Standard errors of Variational Inference
  • Uncertainty quantification for deep learning
  • Bayesian stacking approaches
  • Bayesian neural network structures
  • Deep Gaussian process modelling
  • Multiple Imputation for Panel Data
  • Using Stacking to Average Distributional Regression Models
  • Bivariate Distributional Regression for Wind Speed and Wind Direction
  • Modelling Income Inequality with Semiparametric Transformation Models
  • Bayesian Nonparametric Conditional Density Estimators
  • Distributional Joint Modelling
  • Probabilistic Weather Forecasts
  • Approximations of Normalizing Constants in Doubly-Intractable Likelihoods
  • Effect Fusion of Categorial Predictors
  • Effect Selection in Semiparametric Quantile Regression Models
  • Measuring the Explained Variance in Structured Additive Distributional Regression
  • Bayesian Hierarchical Modelling of Hedonic Housing Prices
  • Comparisons and Implementation of Non-Local Shrinkage Priors



  • since August 2019: Member of the Math+ Faculty and Berlin Mathematical School
    (BMS), TU Berlin, FU Berlin and HU Berlin
  • since May 2019: Member of the Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), HU Berlin
  • since Jan. 2019: Member of the Berlin Doctoral Program in Economics and Management Science (BDPEMS)
  • since Dec. 2018: Member of Biostatnet
  • since Apr. 2018: Associate member of the DFG Research Training Group 2300 Enrichment of European beech forests with conifers: impacts of functional traits on ecosystem functioning
  • since Nov. 2018: Member of Berlin Economics Research Associates (BERA)
  • since Apr. 2018: Member of The German Statistical Society (DStatG)
  • since Jan. 2018: American Statistical Association (ASA) Early Career Member
  • since Aug. 2017: Member of The German Association of University Professors and Lecturers (DHV)
  • since Jan. 2017: Member of the Bayesian Analysis and Modeling Research Group, University of Melbourne
  • since Mar. 2015: Member of the Centre for Statistics, Georg-August-Universität Göttingen
  • Oct. 2012 -Dec. 2014: Associate member of the DFG Research Training Group 1644 Scaling Problems in Statistics


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