I’m a postdoctoral fellow in the biostatistics department at the Johns Hopkins Bloomberg School of Public Health where I am super fortunate to work with a ton of great people in Jeff Leek’s group.

Since starting with Jeff in July 2016, I’ve been working with the data in recount to build phenotype predictors capable of accurately predicting tissue, sex, and age. I have begun to use the predictions to improve analyses and better understand expression in humans.

Before joining Jeff, I received my Ph.D. in human genetics from the Institute of Genetic Medicine at the Johns Hopkins University School of Medicine. In Dan Arking’s lab I focused on improving our understanding of autism. To do this, I used post-mortem cortical brain samples from autism cases and controls to study alterations in gene expression and methylation.

Regarding my interests, I love analyzing human data carefully and teaching others how to do so. I, of course, like pristine data sets. However, data are generally messy. Fortunately, I also really enjoy digging into and untangling the mess that often results from the generation of large amounts of data. So, if there’s a data set and an interesting question, I’m probably interested.

When I’m not analyzing data, cursing myself for a bug in my code, or writing about these endeavors, I harbor reasonable obsessions for beach volleyball, FiveThirtyEight, baking, podcasts, and riding my bike all around Baltimore.