Foto von Max Beier

Max Beier

Short Biography

Since 11/2023

Research Assistent

Chair of Information-oriented Control

Technical University of Munich


Master of Science - Robotics, Cognition, Intelligence

Technical University of Munich

Focus: Machine Learning for Dynamical Systems and Control


Bachelor of Engineering - Mechanical Engineering

Baden-Wuerttemberg Cooperative State University (DHBW) Stuttgart

Robert Bosch GmbH

Research Interests

  • Principled Machine Learning
  • Systems Theory 
  • Prediction-based Control

My research revolves around finding learning-based system representations using operator theory. The overarching goal is to build models from data that allow for convenient automated control design.


I am always looking forward to working with motivated students. If you are curious about my research and looking for a thesis, do not hesitate to contact me. If there is no topic on display, please specify which topics you are interested in. Please include your CV, a current transcript of records, and your preferred start date.

Publications (full list on Google Scholar)

  • P. Bevanda, M. Beier, A. Lederer, S. Sosnowski, E. Hüllermeier, S. Hirche: Koopman Kernel Regression. Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023) (NeurIPS Proceedings), 2023 more…
  • P. Bevanda; M. Beier; S. Kerz; A. Lederer; S. Sosnowski; S. Hirche: Diffeomorphically Learning Stable Koopman Operators. IEEE Control Systems Letters (L-CSS) 6, 2022, 3427 - 3432 more…