Hannes Riebl

Education

Hannes Riebl completed his M.Sc. in Applied Statistics at the University of Göttingen, before starting his Ph.D. at the Chair of Statistics in 2017, where he now works on SP 10-1 of the RTG. His research focuses on extensions of the structured additive distributional regression model class and applications in ecology and forestry. He is also developing a Python software framework for research on these models, building on cutting-edge machine learning technology for efficient Bayesian inference.

PhD Research Project

Structured Additive Distributional Regression Models in Ecology and Forestry: Applications, Software, and Inference

Publications


Conferences

  • Hannes Riebl, Nadja Klein and Thomas Kneib, Gaussian Process Responses in Distributional Regression, Poster, European Courses in Advanced Statistics on Statistical Analysis for Space-Time Data, Lisbon, 15–17 July 2019
  • Hannes Riebl, Nadja Klein and Thomas Kneib, Gaussian Process Responses in Distributional Regression, Poster, International Workshop on Statistical Modelling, Guimarães (Portugal), 7–12 July 2019
  • Hannes Riebl, Nadja Klein and Thomas Kneib, Random Function Responses in Distributional Regression, Talk, DAGStat (Deutsche Arbeitsgemeinschaft Statistik) Conference, Munich, 18–22 March 2019

Teaching

  • Practical Statistical Training, Summer 2021
  • Advanced Statistical Programming with R, Summer 2020 and 2021
  • Advanced Mathematics: Optimization (Exercise Class), Winter 2018 and 2019
  • Statistical Modelling and Advanced Regression Analyses (Exercise Class), Winter 2018
  • Mathematics coaching for economics and business students, Summer 2018
  • Econometrics II (Tutorial), Summer 2017