MS student by day. Building things that matter by night. I like problems with real stakes and systems that hold up under pressure.
MS Information Technology @ Northwestern University ('26) · BS Information Systems @ Carnegie Mellon ('23)
Scalable Music Analytics Platform Full-stack app integrating the Spotify Web API to analyze tracks, generate recommendations, and surface playlist and artist stats in real time. React frontend, Python backend, AWS architecture.
ML Movie Recommendation Engine Polynomial regression, L1/L2 regularization, and a Perceptron classifier built from scratch in Python/NumPy — no ML libraries. Trained on 45,000+ TMDB entries.
Languages: C#, Python, JavaScript, Java, SQL, Swift, R
Frameworks: React, Flask, Node.js, REST APIs, Ruby on Rails
ML/AI: NumPy, Pandas, scikit-learn, TensorFlow, PySpark, LLMs
Cloud & DevOps: AWS (Lambda, S3, API Gateway), Azure DevOps, Docker, Git, CI/CD
Tools: Cypress, Playwright, MongoDB, Figma, PowerBI, Tableau
- CEI / Zelis Healthcare — Integrated LLMs into enterprise QA workflows, engineered 6 major C# features
- UPMC — Built full-stack QA monitoring system in C# and SQL
- DSW — Built Python/scikit-learn predictive models across 10+ data reports
- CMU Teaching Assistant — Mentored 80+ students in full-stack development