My research focuses on making machine-learning systems reliably deployable under real-world variability and distribution shift. I develop methods that quantify and certify model behavior by combining deep learning with statistical divergence estimation. Together with my students and industry partners, I translate these principles into tools for domain adaptation, robustness certification, and shift-aware benchmarking. Our vision is to establish ML robustness as a measurable and auditable property within engineering workflows. 

In 2024, I joined the institute led by Sepp Hochreiter, where I lead the Robust AI group. Previously, I was a Postdoctoral Researcher at RICAM, Austrian Academy of Sciences (2022–2024), Research Team Lead at SCCH GmbH (2020–2022), and Industrial Researcher at SCCH GmbH (2012–2016). I earned my BSc from TU Graz and both my MSc and PhD from JKU (2020).