Data Science undergrad at Simon Fraser University with a deep passion for Formula 1 telemetry, simulation, and performance modelling. I build motorsport analytics projects that mirror real-world race-engineering workflows — with the goal of joining an F1 team through an industrial student placement.
A Monte Carlo simulation that ranks two-stop tyre strategies by combining real FastF1 telemetry (tyre degradation, fuel burn, pit-stop loss) with stochastic race events (Safety Car, VSC, red flag) derived from historical track status. Runs 10,000 simulated races per strategy to estimate expected race time and its full distribution — the way a real strategy group reasons about pit calls.
🏆 F1 Top 3 Predictor A machine-learning pipeline that predicts podium finishers from tyre degradation, sector-wise qualifying data, and race pace using FastF1 telemetry.
🧪 Spanish GP 2024: Telemetry & Sector Analysis Benchmarked Norris vs. Verstappen, Leclerc, and Hamilton through Sector 2 to break down Lando's pole lap using 4 Hz telemetry.
Passionate about data-driven racing. Always looking to connect with motorsport engineers, data scientists, and analytics teams building the future of F1.
Passionate about data-driven racing. Always looking to connect with motorsport engineers, data scientists, and analytics teams building the future of F1.