M.S. Data Science & Analytics, Georgetown (Dec 2026). B.S. Data Science and Business, Chapman (2025). Most recently a data analyst on the Enterprise Alignment team at Mission Support and Test Services, supporting NNSA missions at the Nevada National Security Site. U.S. citizen, clearance-eligible.
Selected work
Curriculum learning for dental disease detection
DENTEX 2023 panoramic X-rays. YOLOv8m segmentation. Three-stage curriculum (quadrant, tooth, disease) tested against a matched single-stage baseline.
mAP@0.5 of 0.394 for the curriculum versus 0.417 for the baseline. The schedule didn’t help. Class imbalance was the binding constraint.
Predictive modeling of U.S. oral health outcomes
NHANES 2017–2018, n = 5,265. Logistic regression, random forest, and XGBoost under 5-fold cross-validation.
ROC-AUC of 0.849. A two-stage regression on socioeconomic predictors alone reduced DMFT MAE by 33%.
Residential electricity demand forecasting
NYC residential load. DSGrid demand profiles joined to ERA5 weather via Open-Meteo.
Supervised baselines (ridge, gradient boosting). Residual structure explored with PCA, t-SNE, K-means, DBSCAN, and hierarchical clustering.
Geospatial crime pattern analysis
Pandas, GeoPandas, and scikit-learn pipeline.
Normalization, K-means clustering, and choropleth visualization of urban incident density against residential and commercial zoning.