I work to bridge the gap between statistical machine-learning research and software that's fast and reliable.
I'm a Uruguayan computer scientist and statistician, trained at Universidad de la República in Montevideo (Ingeniería en Computación, 2022; BSc in Statistics, 2026). I've published research in distributed deep generative models, and my work sits at the intersection of statistical learning, algorithm design, and high-performance computing.
Alongside research, I've spent 6+ years building production software for United States clients as a Staff Software Engineer at WyeWorks, where I focus on framework and interface design and help shape technical direction. What I do best is turn tangled problems into clean, composable abstractions. I bring that same rigor and craft to research software: statistical methods, implemented to be fast, tested, and reproducible.
Statistical package
A fast, memory-efficient implementation of Projection Pursuit Random Forests: a C++ core with R and CLI interfaces, and a modern successor to the R PPforest package. Oblique splits, multi-threaded training, and reproducible golden tests. On CRAN. My Statistics thesis, and the main research software I maintain.
Web application
A full-stack platform cataloguing English translations of Brazilian literature. Grown from a Java (JSF/JPA) technical-degree project into a React + Elixir/Phoenix platform, INPI-registered, and now an ongoing volunteer research collaboration with IFRS Canoas.
Languages: Spanish (native), Portuguese (bilingual), English (Cambridge FCE, C1).