I’ve been working as a curriculum lead on the Chromebook Data Science project most recently. For this, I’ve been developing free, online, educational content to teach the basics of data science to individuls with no background in computing.
After starting Jeff in July 2016, I first began working with the data in recount to build predictors capable of accurately predicting critical phenotype information from gene expression . 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.
A bit more on my interests
I love analyzing data carefully and teaching others how to do the same! 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, baking, and riding my bike all around Baltimore.
Fore more information, my full CV can be found here.