I develop foundations for evaluating and certifying machine-learning systems, with publications in NeurIPS, ICML, ICLR, and JMLR.

My research focuses on machine learning under distribution shift, supporting reliable deployment decisions under uncertainty.

Since 2024, I head the Robust AI group at the LIT AI Lab, Johannes Kepler University Linz [link]

Research Areas

• Quantification of Distribution Shifts
  (density ratio estimation, out-of-distribution detection, divergence measures)

• Correction of Distribution Shifts
  (model selection, domain adaptation, re-calibration)

• Evaluation and Certification Readiness
  (benchmarks, synthetic test data, safety and regulatory alignment)

Short BIO

Since 2024, I lead applied research on robustness, evaluation, and certification readiness of machine-learning systems at the Institute for Machine Learning, Johannes Kepler University Linz; including supervision of PhD projects and coordination of industry-linked research. 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).