Michael Hagmann

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

Education

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

Awards

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

Selected Publications (full list)

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

link | bib

@book{riezler2022,
  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/}
}