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 revolves around finding efficacious learning-based dynamical system representations. Dynamical systems are used to model phenomena in the time domain. They are used extensively in any physical science and, in particular, in robotics. I am especially interested in geometric and operator theoric modeling techniques for their explainability and numerical efficiency. The overarching goal of my research is building models from data that allow for *fast* and *reliable* control design for complex systems.