I am a PhD Candidate in the Department of Statistics at the University of Washington advised by Daniela Witten. I completed my MSc in Statistics in the Department of Statistics at the University of British Columbia under the supervision of Alexandre Bouchard-Côté. My BSc is in Applied Mathematics from McMaster University.
My research interests are in developing new methods for applied problems using tools from high-dimensional statistics, machine learning, and optimization. I seek to generate new statistical innovation through interdisciplinary collaborations with scientists.
My recent work focuses on the estimation of structural changes, and the associated uncertainty of these estimates, in time series data. In particular, we recently introduced a new framework that allows us to quantify the uncertainty associated with an estimated changepoint through a p-value or a confidence interval. See my project website for additional details.
This work is motivated by a new experimental technique called calcium imaging that allows for simultaneous measurement of hundreds or thousands of neurons in behaving animals. For each neuron, this process results in a time series that can be used to estimate the firing times. My website for this project contains additional details and examples.
In the past, I have been involved in work on controlling the false discovery rate, modeling spatial data, Bayesian phylogenetics, and financial mathematics. See my research page for additional information.