Install python3 using Homebrew.
I am a PhD candidate in Applied Mathematics at the University of British Columbia being advised by Özgür Yilmaz and Yaniv Plan. My research is in the area of compressed sensing, convex optimization and machine learning — comprising aspects of high-dimensional probability, applications of random matrix theory, convex analysis and geometric functional analysis.
During October 2016 – February 2017 I completed an internship with Awake Labs, where I worked as a data scientist developing online algorithms for performing learning tasks on structured high-dimensional physiological data.
I completed my MSc Mathematics in August 2014 at the University of Toronto. My supervisor was Dr. Adrian Nachman, under whom I researched fast computational methods in image processing with applications in medical imaging. Before that, I completed my BSc in Mathematics & Statistics at McMaster University in Hamilton, ON.
PhD Candidate, Applied Mathematics
University of British Columbia
MSc in Applied Mathematics, 2014
University of Toronto
BSc in Mathematics & Statistics, 2013
A brief summary and some incomplete reflections from the 2018 BC Data Science workshop.
A kind of repository for some links to blogs and resources that I’ve found useful over the years.
A tutorial on how to create, customize and host a website using Hugo and GitHub Pages.
A matrix completion mini-project that I designed for the 2017 BC Data Science Workshop
My take on the Smart Shores project from the bcdata workshop
Gradient descent concepts from Mark Schmidt’s 540 course at UBC (with code ported to Python).
In Fall 2020, I was the lecture and lab instructor for the UBC MDS program’s DSCI 551: Descriptive Statistics and Probability for Data Science.
In 2017, 2018 and 2019, I was a teaching assistant for the UBC MDS program. UBC MDS courses for which I’ve been a TA include:
Past TA duties include: ODEs, Vector Calculus, Calculus I and Mathematics for Biology.