About Me
I recently completed an M.Sc. in Mathematics and Statistics at McGill University and Mila – Quebec AI Institute, where I was supervised by Prof. Eric Kolaczyk.
My work focuses on graph representation learning for molecular property prediction in low-data regimes, combining deep graph models with tree-based methods to improve performance in graph-level prediction tasks. I am broadly interested in machine learning on graphs, including pretraining strategies for graph transformers, foundational graph models, and their applications.
I hold a B.Sc. in Physics and Applied Mathematics from Bowling Green State University, where I was a member of the NCAA Division I Men’s Soccer Team and a Research Assistant in the Zamkov Lab, studying quantum dots.
Before graduate school, I worked as a Data Scientist in South Essex Fabricating’s R&D Division.
In Summer 2025, I worked as a Quantitative Strategist Associate at Morgan Stanley on the U.S. Treasuries desk, and will be returning full-time in June 2026.
