LLM workflows, tool routing, prompt-injection checks, privacy modes, telemetry, and human review surfaces.
/ Me
First-generation UNC grad building AI and data products.
I work at the intersection of machine learning, applied AI, and data engineering. I do not treat those as separate lanes. The projects I build usually need all three: data has to be ingested and shaped, a model or AI workflow has to be evaluated, and the result has to land in a product surface someone can actually use.
My background started in biology and retail operations, then moved into data science and software engineering. That combination shaped how I build: I like messy operational domains where data quality, model behavior, workflow design, and user trust all matter.
University of North Carolina at Chapel HillB.S. Biology - Data Science minor
Forecasting, feature engineering, model evaluation, SHAP explainability, drift/performance monitoring, and release gates.
ETL, ingestion, SQL models, warehouse-to-serving patterns, background jobs, validation, and reconciliation.
FastAPI and Next.js applications, dashboards, Chrome extensions, auth-aware workflows, and operational interfaces.