My research lies at the intersection of causal inference and machine learning, particularly as applied to large, messy datasets. I have applied my methods to problems such as finding surrogate endpoints in clinical trials, identifying relevant explanatory variables in the presence of correlation and measurement error, predicting the risk of heart attacks using electronic health record data, and understanding human behavior patterns using smartphone sensor data.
My collaborative work spans multiple disciplines, including infectious disease (HIV/Ebola), cardiovascular health, nutrition and obesity, and pediatrics. I serve as lead statistician on a number of clinical trials, consult on small projects with a wide variety of investigators, and participate in interdisciplinary research teams pursuing longer-term research projects.
I am co-founder and Chief Technology Officer of Daynamica, a University of Minnesota startup company that offers smartphone-based data collection, storage, and analysis to researchers and organizations who want to better understand human activity and travel behavior.
Areas of Interest
Electronic health data
Wearable sensor data
PUBH 7200: Data Visualization in R (Summer 2019-2021, Public Health Institute)
PUBH 7401: Fundamentals of Biostatistical Inference
Syllabus (Fall 2019)
PUBH 7461: Exploring and Visualizing Data in R
Syllabus (Fall 2017)
PUBH 7462: Advanced Programming and Data Analysis in R
Syllabus (Spring 2023)
PUBH 6450: Biostatistics I
PUBH 7430: Statistical Methods for Correlated Data
PUBH 8412: Advanced Statistical Inference
In 2016, I was awarded the Leonard M. Schuman Award for Excellence in Teaching by the University of Minnesota School of Public Health.
I serve or have served – as unblinded statistician – on the Data and Safety Monitoring Boards (DSMBs) for three randomized trials coordinated at the University of Minnesota: LIFE-HIV, TACTICAL-HIV, and PREVAIL I. The latter study was the first Phase 3 trial of an anti-Ebola vaccine, and launched in Liberia in January 2015.
I am an Associate Editor for the International Journal of Biostatistics and the Journal of the American Statistical Association (JASA); for the latter, I am an Associate Editor for Reproducbility (AER).
I obtained my Ph.D. in 2009 from the Department of Biostatistics at the University of Washington. My dissertation work was supervised by Prof. Peter Gilbert at the Vaccine and Infectious Disease Institute at the Fred Hutchinson Cancer Research Center. I graduated from McGill University with a B.Sc. Joint Honours in Mathematics and Computer Science in 2004.
I am proudly Canadian, and stubbornly continue to pronounce Z the correct way. With three young kids (including twins!), I have no spare time, but if I did I would enjoy playing squash and golf, and experimenting in the kitchen.