As part of my PhD in theoretical condensed matter physics at the University of Kaiserslautern I studied various physical problems - such as thermal, quantum and dimensional phase transitions - that I investigated with a Quantum Monte Carlo algorithm. In doing so, it was indispensable to be aware of the subtleties of the "High Performance Cluster" (HPC) I had access to, in order to be able to use the available resources efficiently. This also meant constantly improving and optimizing the implementation of the algorithm. As a result, I was able to perform numerous numerical simulations at both the work group's own HPC as well as the one of the University. In order to make use of the huge amount of resulting data, I wrote additional scripts for further investigation which then gave me the opportunity to compare my findings with analytical models. Besides my scientific work I acted as course assistant and also took on the role of system administrator of the working group. Embracing my role as researcher in the "CRC/TR 49", I was elected as student representative.

After finishing my PhD, I moved on to the Fraunhofer research institute and currently act as scientific assistant in the department of high performance computing. In further detail, I am in a group that is specialized in the field of machine learning and its usability in HPC systems. There I am currently creating a software stack for multi-user GPU clusters.
Machine Learning Day
AI/Machine Learning/Deep Learning
Clouds and Distributed Computing
HPC workflows
Scientific Software Development
System Software & Runtime Systems