I am a PhD student in Biostatistics. I graduated from Harvard University in 2015 with a BA in Organismic and Evolutionary Biology, and a Spanish language citation. After completing my undergraduate degree, I worked as a research associate at the Institute for Genomic Medicine at Columbia University Medical Center. My research focused primarily on non-invasive prenatal testing and rare variant association testing.

For my dissertation research, I work with Noah Simon and Marco Carone on nonparametric statistics and machine learning, primarily applied to survival analysis. I developed the global survival stacking framework for estimating personalized survival curves under censoring and truncation using off-the-shelf machine learning tools. The implementation is available at github.com/cwolock/survML. I am also studying efficient nonparametric estimation of variable importance in survival analysis. Variable importance describes the contribution of a variable in predicting an outcome, relative to other available predictors. Our method extends previous variable importance results to the time-to-event setting, where informative censoring is a concern. In addition to my primary methodological research, I have had the opportunity to collaborate in a number of other areas, including personalized medicine, conservation biology, and microbial ecology.  

Outside of school, I enjoy backpacking, skiing, music, and spending time with my dog.