Undergraduate research under Dr. Deidra Coleman at Wofford College.
This research addresses the technical challenges of implementing large-scale spatial multiple testing for disease surveillance. The statistical frameworks presented by Wenguang, S. et al. in the paper "False discovery control in large-scale spatial multiple testing" were analyzed to assess their efficacy in controlling false discoveries. By improving the documentation and reproducibility of the original study, we hope to make these complex spatial methods more transparent and accessible.

Poster Presentation

Southern Conference Undergraduate Research Forum
Black Alumni Summit

Senior Research Symposium
An AI-powered web application using deep learning to analyze retinal images and predict potential eye diseases. Upload a retinal scan image, and the model will classify it into one of four categories: CNV (Choroidal Neovascularization), DME (Diabetic Macular Edema), DRUSEN, or NORMAL.

At CES 2025, Delta CEO Ed Bastian claimed that technology will propel the next century of flight. But is this merely branding, or a financial imperative?
This project uses Random Forest modeling and Semantic Search (RAG) to mathematically test that hypothesis.


