I’m a fourth-year PhD student in Prof. Justin Solomon’s Geometric Data Processing Group at the MIT Computer Science and Artificial Intelligence Lab. My research seeks to understand the role of neural networks in generative modeling and build generative models without neural networks. I’m grateful to be supported by a 2022 Siebel Scholarship and an NSERC Postgraduate Doctoral Scholarship (PGS-D).

I’ve spent Summer 2021 and 2022 interning with Prof. Michael Bronstein and the Learning Methods team at Twitter Cortex!

I completed my undergrad degree in mathematics and economics at McGill University in Montreal. At McGill, I had the privilege of working with:

  • Profs. Rustum Choksi and Tim Hoheisel, with whom I helped develop a state-of-the-art algorithm for QR code deblurring.
  • Prof. Adrian Vetta, with whom I worked on efficient approximation schemes for fair chore division and scheduling problems.
  • Prof. Prakash Panangaden, with whom I worked on efficiently computable approximations to optimal transport distances.

Check out my research page to learn more about my active projects.

Check out my publications page to learn more about past projects that I’ve worked on.