I’m a computational scientist by training, with a background spanning astrophysics, data analysis, and mathematical economics. I enjoy tackling messy, real-world problems—especially ones that involve modeling, statistics, and translating technical results into something useful for other people.

My recent academic work focused on computational and quantitative methods, including simulation and analysis pipelines developed through advanced coursework and research projects. Earlier in my career, I worked as a data analyst in an industry setting, where my training in mathematical economics shaped how I approached business and financial data, stakeholder questions, and decision-making under uncertainty.

This website is both a professional snapshot and a place to think out loud. In the blog, I plan to write occasionally about career transitions, quantitative ideas that show up in business and finance, and reactions to articles or podcast episodes that connect economics, data, and real-world outcomes. If you’re here as a potential collaborator or employer, it should give you a good sense of how I reason about problems and communicate technical work.

Check out my resume here and links to my email, LinkedIn, GitHub, and ORCID below.