I'm a graduate student in the Machine Learning group
at the University of Toronto.
I work with Prof. David Duvenaud
on fundamental machine learning problems at the intersection of deep learning and Bayesian statistics.
Last term, I was part of the teaching staff for CSC411: Introduction to Machine Learning
This term, I'm part of the teaching staff for CSC412: Probabilistic Learning and Reasoning
I completed my BSc (2016) at the University of British Columbia in Computer Science and Statistics.
I spent last summer working in Prof. Mark Schmidt
's Machine Learning Lab where I worked mostly on unsupervised learning algorithms for a Matlab machine learning toolbox
I spent the summer before that as a software engineering intern at Arista Networks
, where I implemented link layer network protocols for high-performance routers.
I also graduated with a BA (2009) and MA (2011) from the University of British Columbia prior to starting my training as a research scientist.
My MA thesis
proposed a linguistic framework for analyzing the UN Intergovernmental Panel on Climate Change
's transformation of statistical climatology into standardized words and phrases for policy-oriented audiences.
This project sparked a strong interest in statistical inference and computer science that led me directly to machine learning.