Biology student at UNC-Chapel Hill on the pre-dental track, building computational biology projects in Python.
I study Biology at the University of North Carolina at Chapel Hill, with minors in Chemistry and Neuroscience, and I'm headed toward dentistry. Alongside clinical work as a dental assistant, I build Python projects that apply data science to health questions: how an outbreak spreads, which genes change in oral cancer, and how a tumor classifier can explain its own predictions.
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Education Clinical Teaching |
Leadership Community Languages Off the clock |
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Computational epidemiology platform: deterministic, stochastic, network and spatial outbreak models, fitted to real surveillance data and checked against analytical results. Interactive dashboard with live parameters.
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Explainable tumor classification on the Wisconsin breast cancer dataset: nested cross-validation across five models, a recall-first decision threshold, and SHAP explanations for every prediction in a Streamlit app.
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Reanalysis of public RNA-seq data (GEO GSE20116) comparing oral squamous cell carcinoma with matched normal tissue: paired negative-binomial differential expression, Hallmark pathway enrichment, publication figures and an interactive explorer.
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All projects are educational and use public data. None are medical devices or forecasting tools.