Associate Professor, Faculty of Science - Mathematics & Statistical Sciences
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
Survey of contemporary languages/environments suitable for algorithms of Statistics and Data Science. Introduction to Monte Carlo methods, random number generation and numerical integration in statistical context and optimization for both smooth and constrained alternatives, tailored to specific applications in statistics and machine learning. Prerequisites: One of STAT 265 or MATH 281, or consent of the Department.
Measure and integration, Laws of Large Numbers, convergence of probability measures. Conditional expectation as time permits. Prerequisites: STAT 471 and STAT 512 or their equivalents.