Projects

This study utilized PCA and K-means clustering to identify four distinct country clusters based on climate and energy consumption, revealing temperature as a key differentiator—particularly for cold, high-energy northern nations—while suggesting that finer clustering could shift focus toward socioeconomic factors like GDP.

This study developed machine learning models to predict employee attrition and monthly income, identifying job satisfaction and job level as key factors, respectively, while highlighting the potential of such techniques to inform corporate decision-making.

This study uses text mining techniques to reveal distinct thematic and lexical differences in the economic writings of Keynes, Smith, and Ricardo, highlighting their unique contributions to economic theory through word frequencies, N-grams, and correlations.

Web Scraper that extracts data from a reef webpage.

Master’s in Computational Social Science Thesis

Networl Analysis of the website traffic and connectivity between different government sites in Iowa.

Predicting Unemployment with Demographic and Labor Force Characteristics

Replica and alternative representation of the NY Times graph “Where education drives mobility”

Economics Bachelor’s Thesis