Studies in electrical engineering and information technology at the Karlsruhe Institute of Technology (KIT) with a focus on control systems (Bachelor in 2015). Practical experience in the research and development division of SEW-EURODRIVE GmbH & Co. KG, working on trajectory tracking controllers for driverless transportation systems. Master's thesis in 2018 on the design and stability analysis of a holistic model predictive vehicle dynamics controller for a wheel-individually actuated vehicle at the Institute of Control Systems (IRS).

From January 2019 to August 2025 research scientist at the FZI Research Center for Information Technology, developing and evaluating trajectory planning methods for highly automated cars and buses.

Since September 2025 head of the research group Networked Multi-Energy Systems at the IRS.

Safely Learning Trajectory Planning for Highly Automated Vehicles

Highly automated driving functions must ensure high availability even under changing environmental conditions. Variations in vehicle dynamics, for example due to changing road conditions, limit the controllability of the vehicle and require safe adaptation of the planning method.

As part of this research, a combined trajectory planning method is being developed that learns unknown coupled longitudinal and lateral acceleration limits without violating the collision-free property of the planned trajectory. In addition, dynamic orientation-dependent collision constraints are being investigated that enable an exact, differentiable description of the drivable corridor, replacing previous approximation solutions.

The goal is a planning method that guarantees the safe availability of highly automated vehicles even under unknown and varying vehicle dynamics conditions.