About

I am Stephan, a recent Computer Science Master's graduate from Technische Universität München (TUM). In addition to my main studies, I also studied Technology Management at the Center for Digital Technology and Management (CDTM), an interdisciplinary honours study program.

I am currently specializing in a sub-area of Artificial Intelligence called Machine Learning, where I am especially interested in statistical robustness, uncertainty quantification (through Bayesian methods), learning from non-i.i.d. data, as well as safety implications, reliability, and interpretability of ML systems. Recently, I was a Visiting Research Scholar at Carnegie Mellon University (CMU) working on my Master's thesis together with Prof. Zachary Lipton. As part of this work, we were evaulating and developing methods for detecting and quantifying shifts in the data distribution between source and target environments.

Right now, I am an Intern Applied Scientist at AWS AI Labs working on systematically assessing the impact of input/output representations for deep-learning-based time-series forecasting and on identifying such representations which robustly provide good performance.

Aside from technology, science, software development, and entrepreneurship, I am also interested in UI/UX design, architecture, and aviation.