I am a graduate student in Machine Learning at the University of Toronto and the Vector Institute. I am currently pursuing follow-up research to my work on Neural Ordinary Differential Equations, and am generally interested in approximate inference for latent variable models. I have recently completed an M.Sc. supervised by Drs. David Duvenaud and Roger Grosse, and am continuing as a Ph.D. student under David Duvenaud. In Winters 2018 and 2019 I was the instructor for CSC412/2506: Probabilistic Learning and Reasoning.
Winter 2020 I will be co-instructing, with David Duvenaud, the course STA414: Statistical Methods in Machine Learning II.
PhD in Computer Science
University of Toronto, 2019 - Present
MSc in Computer Science
University of Toronto, 2017 - 2019
MSc in Mathematics
University of Toronto, 2015 - 2016
BSc in Integrated Science and Mathematics
McMaster Unviersity, 2011 - 2015
I am currently teaching the following course at University of Toronto:
In the past I have taught the following courses at University of Toronto:
In the past I have been a teaching assistant for the following courses: