PhD, University of Cambridge (2017)
MSc, Johns Hopkins University (2011)
BSc, McGill University (2008)
Nonasymptotic Statistics, High Dimensional & Functional Data, Concentration Inequalities, Stochastic processes, Nonparametric Statistics, Mathematical Statistics
Stat 378/502: Applied Regression Analysis
Stat 568: Design and Analysis of Experiments
Stationary series, spectral analysis, models in time series: autoregressive, moving average, ARMA and ARIMA. Smoothing series, computational techniques and computer packages for time series. Prerequisites: STAT 372 and 378. Note: This course may only be offered in alternate years.
Winter Term 2021The general linear model. Fully randomized designs, one-way layout, multiple comparisons. Block designs, Latin squares. Factorial designs confounding, fractions. Nested designs, randomization restrictions. Response surface methodology. Analysis of covariance. Prerequisite: STAT 368 and a 400-level STAT course.
Winter Term 2021