Welcome!
I’m a final-year PhD student in Prof. Justin Solomon’s Geometric Data Processing Group at the MIT Computer Science and Artificial Intelligence Lab. I’m on the academic job market in fall 2025. I’m also interested in chatting about research roles in industry.
I work towards understanding the behavior of generative models, particularly diffusion models. I’m especially interested in two questions:
- Why do generative models generate new content instead of merely memorizing their training data?
- How does a generative model’s behavior depend on its training data?
You can read more about my research here.
I’m grateful to have been supported by:
- A 2025-2026 MIT-Google Future Research Cohort Fellowship,
- a 2024 Exponent Fellowship,
- a 2022 Siebel Scholarship, and
- an NSERC PGS-D Scholarship.
I’m also grateful to have had the opportunity to co-author successful proposals for an MIT-Google Program for Computing Innovation Grant, which is helping fund my work on data attribution for diffusion models, and for an Amazon Research Award, which has helped fund my work on closed-form diffusion models.
I spent Summer 2025 interning with Dr. Kristjan Greenewald and Dr. Leshem Choshen at the MIT-IBM Watson AI Lab. We worked on model merging methods for LLMs.
I spent Summer 2024 interning with Dr. Paul Zhang at Backflip AI, a 3D generative AI startup based in San Francisco. We developed a state-of-the-art method for orienting 3D shapes, which you can read all about in Symmetry-Robust 3D Orientation Estimation.
I 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.