RTG 2300: Enrichment of European beech forests with conifers

Jens Lichter

Education

10.2018-12.2020:
  • M.Sc. in Applied Statistics at the University of Göttingen
  • Specialization Economics
  • M.Sc. thesis: ”Studying Variational Inference Methods for Bayesian Regression Models with different Effect Types”.

10.2013-05.2018:
  • B.A. in Economics at the Universtity of Göttingen including an exchange year at the University of Nottingham.
  • Specialization Trade and Quantitative Methods
  • B.A. thesis: ”Influence of Off-Shore Windenergy on German Electricity Prices”.
  • Guest Scientist in the Next Generation Mobility research group at the Max-Planck-Institute for Dynamics and Self-Organization with research focus on wind energy (04.2017- 04.2018)

PhD Research Project

Title of doctoral Project: “Hierarchical Bayesian Regression Models with Applications in Ecology and Forestry”.
We develope flexible Hierarchical Bayesian regression models and fast inferential methods to analyze highly complex systems in the field of ecology and forestry. For fast estimation of the model parameters we explore Variational Inference as alternative to Markov Chain Monte Carlo (MCMC) methods, where inference can take high computational times for complex models or large data sets. Additionally, we develope models to analyze tree stem increment and water status using Gaussian Processes as continuous response.

Publications

Thielmann, A., Seifert, Q., and Lichter, J. (2020). Sign language recognition using regularized convolutional neural networks. In B. Säfken, A. Silbersdorff, and C. Weisser (Eds.), Learning
Deep - Perspectives on Deep Learning Algorithms and Artificial Intelligence (pp 53–70), Universitätsverlag Göttingen
Lichter, J., Hosius, E., Wacker, B., and Schlüter, J. (2020). Der Einfluss von Offshore-Windenergie auf die EEX-Strompreise. Zeitschrift für Energiewirtschaft, (44):85–99.

Teaching

  • Tutor in Econometrics II in the summer term 2020 (Master Module offered by the Chair of Econometrics at the University of Göttingen)

  • Tutor in Statistics for Biology Students with focus on statistic software Python (summer term 2019) and tutor supervisor in the subsequent year (Bachelor Module offered by the Department of Data-driven Analysis of Biological Networks at the University of Göttingen)

  • Tutor in a one week Latex course in 2018 (Optional Bachelor or Master course offered by the Chair of Statistics at the University of Göttingen)

  • Tutor in a two weeks introductory course in statistics with focus on statistic software R (10.2019, International Max Planck Research School for Molecular Biology in Göttingen)