I’m Matteo Gätzner, currently pursuing an M.Sc. in Statistics at ETH Zürich, where I focus on confidence estimation methods for compressed sensing. Previously, I earned a B.Sc. in Computer Science from TU Berlin and have worked on probabilistic inference, MCMC methods, and AI-driven forecasting. I’ve also held roles at Roche (lab automation & ML) and Fraunhofer HHI (AI research).

I maintain an open-source Rust library called mini-mcmc, which implements MCMC algorithms (HMC, Gibbs sampling, Metropolis–Hastings, NUTS) and is designed for easy integration into probabilistic modeling pipelines: github.com/MatteoGaetzner/mini-mcmc.

For a detailed overview of my background and skills, please see my full resume: Resume.

I’m always open to discussing interesting projects or potential collaborations—feel free to get in touch via email (matteo.gatzner@gmail.com) or connect on LinkedIn and GitHub.