Biosketch
Max obtained his Bachelor of Mechanical Engineering in 2020 at Baden-Wuerttemberg Cooperative State University Stuttgart with Bosch. His interest in learning from data where models from first principles fail drove him to enroll in the Robotics, Cognition, Intelligence Master at TUM, where he graduated in 2023.
During his studies, he came to love systems and control as a framework for building models in the face of complex interactions. Since 2023, he has been pursuing his PhD with Prof. Hirche. He is particularly interested in learning practical dynamical systems representations in terms of utilizing the inherent structure in dynamical systems data, provable learning theoretic guarantees and uncertainty quantification.
relAI Research
Learning with Dynamical Systems for Control
My research focuses on learning-based dynamical system representations that enable the automated design with performance guarantees for a downstream task; for example, predicting and controlling a robotic system. To this end, I am especially interested in geometric and operator-theoretic methods. Through fruitful collaboration, I have applied these mathematical ideas to time series forecasting, sequence modeling, and optimal control.
Publications
https://scholar.google.com/citations?hl=en&user=iZppzEYAAAAJ