Projects
ML / AI Projects
Fine-tuning a large language model with CNN-based feature extraction to classify chest X-rays for pneumonia detection using PyTorch, torchvision, NumPy, augmentation, and normalization.
Compared Logistic Regression, SGD SVM, and Random Forest models on a 368-patient heart failure dataset to assess mortality prediction, risk segmentation, underwriting relevance, and model governance for an actuarial audience.
Cleaned and transformed data in R, then applied machine learning, predictive modeling, and data mining techniques to analyze factors contributing to alcoholism in a Kaggle analytics competition.
Scraped and compiled franchise scripts, then applied text mining and sentiment analysis to compare emotional tone, narrative structure, word frequency, sentiment trends, and thematic parallels.
Data Analytics / Science Projects
Analyzed 8-band satellite imagery with R, raster, tidyverse, and ggplot2 to identify environmental conditions associated with mosquito-borne disease exposure risk.
Built an HTML research website, cleaned crime datasets, implemented Tableau dashboards, and used R web scraping packages like rvest and httr to analyze crime patterns and trends.
Cleaned and validated survey data with Python, pandas, and NumPy, then used NLTK, matplotlib, and sentiment analysis to study student responses and inform future Civic course development.