I’m currently an Adjunct Professor in Statistics at UC Davis. In fall, I will join the University of San Francisco as an assistant professor, with joint appointments between Math and Statistics and the Masters in Data Science Program.

I received my PhD in Statistics under Prof. Hans-Georg Müller at UC Davis. Broadly, I am interested in the treatment of complex-structured data whose geometries thwart traditional, off-the-shelf statistical methods. In particular I am attracted to questions concerning functional data, especially when the functions are multivariate, contaminated by warping, or subject to constraints, as in the case of densities or monotonic curves. I am also a contributor and past maintainer of the R package fdapace.

A motivating example for much of my work arises in the study of human growth curves, in which several body measurements are tracked from infancy to adulthood. In my PhD, my methodological projects involved identifying systematic phase variation in growth spurts across both individuals and different modalities of growth (e.g. arms, legs, spine). My research approaches this problem by exploring models which can quantify intercomponent time dynamics for multivariate functional data, like time warping and time shifting frameworks.

Beyond developing methodology, I’m also a fan of working as a statistical consultant in my research. I like finding intuitive and creative ways of conveying results and breaking through the “language barrier” between statisticians and other scientists. My applied collaborations span a wide variety of domains: in the past I’ve collaborated with neuroscientists from the Bill & Melinda Gates Foundation, veterinarians from the San Diego Zoo, and the researchers behind Mt. Everest’s Himalayan Database, to name a few.

With much of my working time spent behind a computer screen, I find a lot of value in connecting to the natural world when I have the chance. In free moments you’ll probably find me on a trail, in a river, or road tripping around wherever I am at the current moment.