Michael Kohler

Prof. Michael Kohler is a W3 Professor for Mathematical Statistics at the Technical University of Darmstadt since 2007, within the Department of Mathematics. His research focuses on nonparametric statistics, uncertainty quantification, machine learning, and applications in engineering and finance. He holds a PhD from the University of Stuttgart (1997) and a Habilitation from the same university (2000). His work includes contributions to regression estimation, Monte Carlo methods for pricing options, and statistical methods in computer linguistics.

Education: PhD in Mathematics (1997), Habilitation in Mathematics (2000), both from the University of Stuttgart. Earlier studies include a Diploma in Mathematics and Computer Science (1995) and scholarships from the German Academic Scholarship Foundation (1993-1995).

Research Interests: Nonparametric regression, uncertainty quantification using surrogate models, statistical machine learning, deep neural networks, and applications in finance and engineering. He has developed methods for quantifying uncertainty in technical systems and improving regression estimates under minimal assumptions.

Key Achievements: Awarded the Research Prize by the German Mathematical Society (1998) and the Best Teaching Prize from TU Darmstadt's Mathematics Department (2006). His work on deep learning and nonparametric regression has been published in top journals like IEEE Transactions on Information Theory and Annals of Statistics.

• Awards: Research Prize (1998), Best Teaching (2006)
• Grants: Not explicitly mentioned, but extensive research output suggests active grant involvement
• Labs/Teams: Leading research on uncertainty quantification, deep learning, and statistical methods at TU Darmstadt