About me

I recently completed my Master in Automation Engineering at RWTH Aachen University, Germany focusing on the application of modern control approaches such as Model-Predictive Control and Norm-Optimal Iterative Learning Control at the Institute for Automatic Control. My research focuses on model-based control, controller tuning and applying machine learning techniques to incorporate process knowledge into controllers.

My Master thesis focused on the Automatic Parameterization of a Norm-optimal Iterative Learning Cavity Pressure Control in Plastic Injection Molding. Currently I am staying in Joinville, Brasil for a research stay at Laboratório de Sistemas Embarcados hosted by Prof. Dr. Gian Berkenbrock. My research here focuses on the usage of Physics-Informed Neural Networks for the usage as process models in model-based controllers.

Previously I completed my bachelor’s in Mechanical Engineering at RWTH Aachen University.

I taught the supplementary courses “Introduction to MATLAB” and “Simulation using MATLAB and Simulink” for the IT Center RWTH Aachen. Each semester 150 students participated in these courses. During the Covid pandemic I was in charge of developing a novel digital course design for both courses.

I completed an internship at BMW as a DevOps engineer within the Vehicle Dynamics Division. I mainly worked on the MBSE Toolchain, the tool used at BMW to generate C-Code for ECUs from Simulink models. In this capacity I gained experience working with Matlab, JAVA, Python and Bazel. In addition I got exposed to developing and maintaining large CI/CD systems. During this period, I also developed the medical imaging toolbox ImageRefiner for the research group of Prof. Dr. Ostendorf at Uniklinik RWTH Aachen University.

At the Institute for Plastics Processing I worked on the automatic deployment of a large process optimization platform using Docker containers.