As a member of the powertrain subteam, I redesigned our gearbox and driveline geometry in SolidWorks, then validated those changes through rigorous back-to-back acceleration tests. To accelerate decision-making, I developed a Python-based DAQ pipeline that automatically logged, cleaned, and visualized sensor data—cutting analysis time in half and enabling same-day tuning adjustments. Our optimizations delivered a 15% increase in peak torque and shaved 0.2 s off our 0–60 mph sprint time. At competition, we clinched 1st in Design, 2nd in Autocross, and 4th in Skidpad, showcasing the power of rapid iteration and data-driven engineering.

I helped launch our SAE Aero team from the ground up—starting with little more than a classroom model and a passion for flight. Over the year, we designed and built a lightweight aluminum-and-balsa aircraft with a 15-ft wingspan and 55-lb limit, iterating on wing shape, material choices, and control surfaces until it was competition-ready. At Van Nuys, we flew our first prototype against established teams—finishing 22nd out of 27—but more importantly, we proved our concept, forged valuable industry connections, and laid the foundation for even stronger results next season.

I built a Flask-based Python tool to turn raw air-bearing test logs into clean, ready-to-analyze datasets and auto-generated summary plots. By scripting with pandas to parse multiple runs, align time series, and calculate key metrics (bearing load, running force, speed, temperatures), I slashed data-prep time by 75% and delivered consistent chart outputs for rapid operational insights.

I love turning compact boards into on-the-go powerhouses. Whether it’s packing a Raspberry Pi Zero into a handheld weather station or building a solar-charged data logger with wireless sensors, I thrive on squeezing full desktop-style capabilities into pocket-sized devices. From custom PCBs and heat-sink design to battery management and firmware in C/C++, I combine hardware and software skills to make technology truly portable.