Gemma Moran is advised by David Blei. She is interested in developing statistical methods for analyzing high-dimensional data, particularly in the sciences. She is currently working on a project to identify when more complex models for data are required, or whether more simple models are sufficient. Her current collaborative projects are analyzing CRISPR data to identify gene interaction effects, and predicting the formation of perovskites inexpensive materials with promising photovoltaic properties for solar cells. Gemma received her Ph.D. in statistics from the University of Pennsylvania under the direction of Edward George. During her graduate school, she studied Bayesian statistics, particularly feature selection and dimensionality reduction, and used it to find patterns in genomics data.