Michael Hagmann, MSc.

I am a graduate research assistant at the StatNLP group, supervised by Prof. Dr. Stefan Riezler. My current research focus are the application and adapation of empirical methods for machine learning. I am also interested in differentialy private machine learning techniques and their application to medical data.

Research Interests

  • Differential Privacy
  • Empirical Methods in ML
  • Time Series Modelling
  • Convex and Non-Convex Optimization
  • Bayesian Statistics
  • Medical Data Analysis

Curriculum Vitae


2016 Master in Statistics (with distinctions), University of Vienna
2016 Bachelor in Psychology, University of Vienna
2013 Bachelor in Statistics, University of Vienna

Employment History

09/19 Graduate Research Associate
StatNLP group, Department for Computational Linguistics, Heidelberg University
10/18 - 08/19 Research Associate
Heinrich-Lanz-Zentrum, Medical Faculty Mannheim, Heidelberg University
04/16 - 09/18 Research Associate
Department for Medical Statistics, Medical Faculty Mannheim, Heidelberg University
06/12 - 03/16 Consultant Statistician
Section for Medical Statistics, CeMSIIS, Medical University of Vienna


  • 2017 Award for the best Master thesis in applied statistics by the Austrian Statistical Society (ÖSG) pdf

Selected Publications (full list)

  1. Stefan Riezler and Michael Hagmann
    Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science
    Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers, 2022
      author = {Riezler, Stefan and Hagmann, Michael},
      title = {Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science},
      publisher = {Morgan \& Claypool Publishers},
      series = {Synthesis Lectures on Human Language Technologies},
      editor = {Hirst, Graeme},
      year = {2022},
      isbn = {9781636392714},
      doi = {10.2200/S01137ED1V01Y202110HLT055},
      url = {https://www.cl.uni-heidelberg.de/statnlpgroup/empirical_methods/}