Bio

I joined the University of South Carolina Department of Statistics as an Assistant Professor in 2020 after completing a two-year postdoc at the University of Pennsylvania. I earned my PhD in Statistics from University of Florida in 2018, my Masters in Applied Mathematics from the University of Massachusetts Amherst, and my Bachelor’s from Cornell University.

My research focuses on Bayesian statistics, high-dimensional modeling, and scalable machine learning algorithms for large and complex datasets. Some of the tools I use include nonconvex optimization, deep learning and deep generative models, and distributed inference on multicore computer architectures. My research is primarily motivated by addressing “big data” challenges in contemporary biomedical and public health problems, including genome-wide association studies, computational drug repositioning, and analysis of electronic health records. My research has been funded by the National Science Foundation (NSF).