I am a research scientist with over six years of industrial experience in software development and more than four years specializing in factory and robotic assembly automation. I obtained a master’s degree in mechatronics from the University of Stuttgart and a bachelor’s degree in mechanical engineering from the University of Applied Sciences Albstadt‑Sigmaringen and am currently pursuing a PhD at the Fraunhofer Institute for Manufacturing Engineering and Automation IPA. My work focuses on leveraging mathematical optimization techniques and machine learning to solve complex problems in industrial automation. I am interested in applying new research and advanced problem-solving methods to tackle real-world challenges, particularly in robotics and automation systems.

My expertise spans the following areas:

• Assembly Line Optimization: Developing mixed-integer programming models to optimize robotics and hybrid assembly lines and address challenges in Assembly Line Balancing through new models and methods.
• Robotic Assembly and AI Integration: Implementing symbolic AI techniques to enhance robotic assembly tasks, such as peg-in-hole operations, with real-world execution and performance evaluation.
• Reinforcement Learning for Robotic Manipulation: Training robotics systems to perform complex assembly tasks within physics-based simulations using Reinforcement Learning algorithms.
• Machine Learning for Safety-Critical Applications: Investigate machine learning detection models' reliability, conformity and safety in applications where accuracy is critical.
• Assistive Robotics in Dynamic Environments: Designing, simulating, and optimizing the drive-controller for assistive robotic systems capable of adapting to highly variable and dynamic settings.
• Automation of Automation: Responsible for the “automation of automation” in the context of factory reconfiguration, and matrix production to create flexible production systems for the future.

Download my resumé.