East Setauket, New York, United States
Intuitive Computing Lab: CTY Data Analysis Team
Summer 2026: Jane Street Immersion Program
UChicago Trading Contest (3rd in Case 1: Market Making) IMC Prosperity Trading Contest (Top 5%) Georgetown Trading Contest (3rd in Face-Up)
Conducted NSF-sponsored research on low-discrepancy point generation for quasi-Monte Carlo Methods using Graph Neural Networks. Implemented new algorithms for high-dimensional discrepancies and Brownian Bridge path generation into QMCPy library and applied results to Asian Options pricing. Presented results at the Biennial International Monte Carlo Methods (MCM) Conference.