Using Data to Empower and Inform Organizations
I am an Economics and Computer Science double major at the University of Washington Bothell. I am interested in using programming, economics, and financial mathematics to craft data-informed decisions for businesses, hospitals, government agencies, and nonprofit organizations.
June 2025 - Current
The House of Wisdom
Leading the development of a full-stack web app to automate internal operations. Engineered data pipelines to track student attendance and built dynamic dashboards for real-time performance monitoring.
July 2025 - Current
Mathnasium
Provided individualized instruction to students from elementary to high school. Applied the Mathnasium Method to create engaging, structured learning plans tailored to each student's needs.
Designed a project analyzing the growing disparity between the U.S. minimum wage and the cost of living using a large BLS dataset. Utilized PostgreSQL to clean and format the data and developed a model illustrating how the minimum wage would appear if it had consistently tracked inflation. Incorporated average rent prices and compared them to CPI data to highlight how CPI fails to reflect the true cost of living for most Americans, culminating in data-driven storytelling.
Download Report (.pbix) →Developed a data-driven model to optimize a stock portfolio using 10 years of historical price data from Yahoo Finance. Conducted Monte Carlo simulations with 50,000 portfolio weight combinations to identify allocations maximizing the Sharpe ratio (1.02) while minimizing risk (annualized volatility reduced by 18%). Visualized the efficient frontier to show optimal risk-return tradeoffs and recommended a portfolio mix projected to yield an annualized return of 22.3%.
View on GitHub →Built a system to find the best spots for new EV charging stations. This project used Python (Pandas, Scikit-Learn, Prophet) for analysis and forecasting, alongside SQL (PostGIS) for geospatial data. Data was integrated from government APIs and mapping services to ensure a comprehensive analysis. The result is an interactive dashboard that shows high-demand areas to help plan infrastructure spending wisely.
View on GitHub →