About Me
I am a graduate student at McGill University and Mila – Quebec AI Institute, pursuing an M.Sc. in Mathematics and Statistics under the supervision of Prof. Eric Kolaczyk.
My research focuses on interpretable graph representation learning for molecular property prediction in low-data regimes, combining deep graph models with tree-based methods to improve generalization and reduce variance in graph-level prediction tasks. I also study pretraining strategies for graph neural networks and graph transformers, and am broadly interested in generative modeling for molecular design and drug discovery.
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 the Summer of 2025, I joined Morgan Stanley as a Quantitative Strategist Summer Associate on the U.S. Treasuries desk.
