A reproducible ML pipeline for predicting NBA player performance.
Built an end-to-end data pipeline, leakage-safe feature engineering, chronological model evaluation, serialized artifacts, and automated tests around real NBA player-game data.
Software Engineering · Testing / QA · AI / ML
I build reliable software and data-driven systems, with an emphasis on testing, reproducibility, and measurable results.
Built an end-to-end data pipeline, leakage-safe feature engineering, chronological model evaluation, serialized artifacts, and automated tests around real NBA player-game data.
My strongest work is in Python and software/data tooling, with growing frontend experience through this portfolio and other projects.
College of Engineering & Computer Science
Dean’s List (Fall 2025) · President’s Honor Roll (Spring 2026)
I’m an Information Technology student at UCF interested in software engineering, testing, and applied machine learning. I enjoy projects where correctness can be measured — whether that means building a data pipeline, designing tests, or turning raw information into something useful.
Outside of software, I’m usually following basketball, enjoying competitive strategy games, or fixating on the newest engineering developments in performance cars. I’m especially drawn to projects that connect software with the areas I’m most passionate about.
I’m currently pursuing software engineering, software testing/QA, and related internship opportunities.