Research
Measurement → Automation → Evidence

Research

Reproducible, interpretable, open source.

I build AI-driven neuroimaging methods for stereotactic and clinical use, where millimetric accuracy constrains model design, uncertainty is explicit, and automated workflows remain auditable and reproducible across scanners, sites, and populations.

Lane 1: Measurement & QC

Make errors visible, comparable, and actionable.

Lane 2: Targeting & Anatomy

Interpretability and uncertainty over “pretty maps.”

Lane 3: Reproducible Tooling

Pipelines that survive other people’s hands.