I’m a PhD student in the Machine Learning Group, co-supervised by Prof. Jimmy Ba and Prof. Sanja Fidler. During my undergraduate degree, I studied Engineering Science, majoring in Electrical and Computer Engineering at the University of Toronto. My undergraduate thesis advisor was Prof. Deepa Kundur. I interned at Qualcomm Canada in the Video Processing group as part of my Professional Experience Year for 16 months. Prior to starting my graduate degree, I spent a year working at Intel Programmale Solutions Group (PSG) in the OpenCL Usability team. More details in my CV.
I’m also a speedcuber.
I’m broadly interested in optimization algorithms for neural networks, and the intersection of reinforcement learning, computer vision, and natural language processing. I’m still in the exploration phase!
I was a Teaching Assistant for the following courses:
- ECE421 Introduction to Machine Learning, Winter 2019. Taught weekly 2-hour tutorials.
- MIE324 Introduction to Machine Intelligence, Fall 2018. Developed 3 new assignments over the summer.
- CSC321 Introduction to Neural Networks, Winter 2018
- CSC411 Introduction to Machine Learning, Fall 2017
- Closing the generalization gap in stochastic optimization through Fisher gradient noise. Vector Institute, Toronto, Canada. February, 2018