Berk Ata Alpay

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.




Combinatorial and statistical prediction of gene expression from haplotype sequence

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.



Dynamic modeling of power outages caused by thunderstorms

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.