• Developed a new baseball lineup optimization tool featuring a novel metric to quantify player run contribution based on lineup interaction effects

• Designed and implemented a high-performance algorithm to evaluate and rank 360,000+ lineup permutations, optimized using Numba JIT compilation, Pandas for data handling, and 4D NumPy tensors for efficient run value lookup and scoring.

• Presented research and results at MATRX 2025, JHU Design Day 2025 (won digital vanguard award), and the DC SABR Convention 2025

Engineer on the algorithm team for the Delineo Disease Modeling project. Goal is to understand disease spread at a granular level to inform policy decisions and improve outbreak intervention strategies. World Health Organization is funder and ultimate user