About Me

Background. I earned my PhD in Biostatistics under the supervision of Tianxi Cai at Harvard University and a BA in Applied Mathematics at UC Berkeley. I did my postdoctoral work with Lu Tian in the Department of Biomedical Data Science at Stanford University. I then spent a few years at Alphabet's Verily Life Sciences as a data scientist on the Project Baseline Mood Study. In addition to my primary appointment in Statistical Sciences at the University of Toronto, I am a faculty affiliate of the Vector Institute for Artificial Intelligence. I also serve as an associate editor for Biometrics and the Journal of the American Statistical Association (ACS).   

Philosophy.  My experience in academia and industry working with high volume, high noise data has forever made me a data skeptic. I believe in respecting the data at hand and being realistic about the questions it can be used to answer. I aim to develop methods that are based on foundational statistical principles and tailored to the intricacies of real-world problems.

Mentoring. One of my primary motivations for returning to academia from industry is the opportunity to work with rising data scientists. I come from a background where achieving an undergraduate education seemed out of reach. I am extremely grateful for the support I received from numerous mentors throughout my career and strive to offer the same mentorship to students in research and beyond. Each summer I look forward to organizing and teaching Data Science in Action: Machine Learning for Self Driving Cars, a summer program where high school students learn machine learning, statistics, and programming through building a toy self-driving car.