Teaching at Duke:
- I have been the instructor for two semesters (Spring 2021, Summer 2020), of the course Introduction to Biostatistics (STA 102), in the Department of Statistical Science at Duke University.
- I have also been a guest lecturer in the course Probabilistic Machine Learning (STA 561D), lecturing on generative models in machine learning.
Other Teaching Experiences:
As an undergraduate at Duke University and a graduate student at UNC-CH, I have served as a teaching assistant and/or grader for both undergraduate and graduate level courses, including Bayesian Statistics (UNC-CH BIOS 779), and Causal Inference in Biomedical Research (UNC-CH BIOS 776), among others, and guest lectured on Spatial Statistics from a Bayesian Perspective for BIOS 779.
I was the faculty lead for the Duke Universities Rhodes Information Initiative Data+ Summer Project entitled “Predicting Blindness in Duke’s Glaucoma Patient Population”. A full description of the project can be found here!
This project involved predicting the incidence of blindness in glaucoma patients at the Duke Eye Center (DEC) — specifically, the likelihood of a patient presenting legally blind (i.e. with very advanced disease) at their first visit. We assembled a novel data set of electronic health records from thousands of DEC glaucoma patients and data from the Durham Neighborhood Compass project, a repository of geo-spatially resolved socioeconomic statistics on Durham county that includes features like average distance to a healthcare facility. As a result of our project, we identified risk factors associated with delayed care for glaucoma in the Durham and wider NC communities.