From Scores to Decisions
A short note on turning anomaly scores into calibrated evidence and keeping the decision layer inspectable.
- conformal inference
- anomaly detection
- online FDR
Research staff / Machine learning / Uncertainty
Oliver Hennhöfer
I focus on ML systems that make uncertainty explicit, especially through conformal inference.
Research Focus
My work sits at the intersection of inferential statistics and applied machine learning.
- Uncertainty Quantification. Conformal inference methods for trustworthy decision-making.
- Anomaly Detection. Unsupervised methods for identifying rare patterns in ill-posed settings.
Projects
nonconform
Python pacakge for Conformal Anomaly Detection & Change-Point Detection.
online-fdr
Python pacakge for false discovery rate control in sequential hypotheses testing.
aberrant
Python package for online anomaly detection in streaming data and related tooling.
Publications
2026