I'm a PhD student in the Systems, Synthetic, and Quantitative Biology PhD program at Harvard on an NSF Graduate Research Fellowship. I studied computer science and math at the University of Connecticut during my undergrad years. I like working on a wide range of problems but my interests are mainly in Bayesian statistics and biology.
Computational gene expression prediction can combine the statistical power and biological insights of transcriptome-wide association studies with the genetic signals discovered by genome-wide association studies. However, current methods are not accurate for many genes. Our models relax the independence of genetic markers to more accurately predict a large subset of genes.
Thunderstorms are complex phenomena that cause substantial power outages in a short period. Predicting these outages is challenging using eventwise models, which summarize the weather dynamics over the entire course of the storm. We developed a framework designed for models to learn the dynamics of thunderstorm-caused outages directly from hourly weather forecasts.