Senior QA Engineer at Harvard Law School.
Helping software teams evaluate and mitigate risk — through disciplined testing, automation, and AI-assisted QA.
QA Engineer with over 15 years in technology, currently serving as Senior QA Engineer at Harvard Law School. I help software teams build confidence in their releases through disciplined testing practices, automation, and a growing focus on AI-assisted QA techniques.
Provided comprehensive IT support for small nonprofits in the DC metro area — including cloud migrations, domain management, network infrastructure, and office relocations.
Trained volunteers and local counterparts on workplace technology use, created income-generating internet cafés for local women's groups, and co-managed a USAID-funded HIV/AIDS awareness program.
Exploring how AI can make quality engineering faster, smarter, and more secure.
An AI-powered workflow that converts video recordings of software interactions into structured, executable test scripts — reducing the manual effort of test authoring.
Generates synthetic test data using voice dictation fed into a locally-hosted LLM — keeping sensitive data requirements entirely off external APIs.
In my spare time I work on AI-assisted development, building tools for my own personal use.
Local, privacy-first retirement projection app with Monte Carlo simulation, historical backtesting, and bracket-level tax modeling — all computed by a pure-Rust engine on your own machine.
A proof-of-concept that answers natural-language questions over a collection of PDF documents, grounding each answer in the source material.