About

Double major: B.S. Quantitative Economics (Mathematics) · B.A. Mathematics

Minor: Computer Science

University of Kentucky Center for Poverty Research (UKCPR)

• Build tract-level and national panel datasets of U.S. educational attainment from 1990 to 2024 in R and Stata, harmonizing 1,306 Kentucky census tracts to 2020 boundaries and reconciling three data schemas across 25 years of ACS, NHGIS, and postsecondary award data, then apply econometric models and train machine learning models on 3M+ observations to forecast 5-year degree trends and analyze attainment gaps.

Economics & Business Department · Berea College

• Helped students during economics lab sessions in economic modeling, applied statistics, micro, macro, and econometrics by providing hands-on support in STATA and R for applied regression analysis, including multivariable models, cross-sectional and panel data, and individualized guidance on data cleaning, visualization, and the interpretation of empirical results.

Data Science for the Public Good Program · Virginia Tech

• Developed an interactive R Shiny dashboard to estimate and visualize monthly cost-of-living measures across all Virginia counties by family size and structure, using statistical models to estimate the cost of living. Also analyzed wage data to identify regional income–cost gaps and affordability challenges for stakeholders and policy-making use.

Writing Resources · Berea College

• Assisted 1000+ students with paper writing, writing assignments, and mentoring for various writing tasks. And also provided personalized feedback to improve their writing skills and academic performance through consultation.

Built a 40,000+ observation county-year panel from ACS, County Health Rankings, and IHME data to study how income relates to health and well-being across U.S. regions. Found that a 10% higher income is associated with larger gains in health and well-being outcomes in Appalachian counties than in wealthier regions, suggesting that the marginal return to income is higher where baseline resources are lower. Results point to targeted transfers and place-based policy as more efficient than uniform national programs.

Built a cross-country regression model of U.S. remittance outflows to 97 countries using World Bank, IMF, UN, and Pew data to study what drives the volume and cost of cross-border wealth transfers. Found that transaction costs are associated with roughly 14% lower flows and that migrant stock is the strongest predictor of remittance volume, consistent with the view that both frictions and network size shape international financial transfers. Results carry direct implications for cross-border payment design and remittance corridor policy.

Interactive RShiny dashboard that estimates (and visualizes) county-level cost of living across all Virginia counties by family structure and demographics.

ML Explorer

Browser-based interactive guide to machine learning, tune hyperparameters, watch decision boundaries shift in real time, and build intuition across supervised, unsupervised, and probabilistic methods.

Global GDP Dashboard

An interactive dashboard that visualizes global GDP data to allow users to see countries ranked against 57 real-world economies, and compare nominal vs. real GDP and per capita living standards through interactive charts.

• Founded and lead a student organization at Berea College that promotes applied learning in economics and data science through workshops, projects, and peer collaboration focused on real-world problems.

• Nonprofit providing free pre-college mentorship and educational programs for Afghan students, especially girls banned from formal education. Supported 4,000+ students since 2024.

• Co-managed a ~$390K equity portfolio on behalf of Berea College, contributing to a 10% return that outperformed the S&P 500 by analyzing financial statements, valuation multiples, and revenue trends, presenting buy and sell recommendations to the portfolio committee, and flagging rebalancing needs during volatile periods to reduce downside exposure.

• Selected from a competitive pool of undergraduates across the U.S. for Stanford Engineering's SERIS program to get a hands-on experience of graduate studies and research experiences at Stanford.

• Leadership and professional development program for first-generation college students with HBS-style coursework in project management, data analytics, and leadership.