Capstone project forecasting critical telemetry signals such as Lambda (λ) and RPM using LSTM, ARIMAX, and ETSformer models — inspired by real-world incidents such as Hamilton's 2024 Grand Prix retirement.
Delivered a forecast-first ECU pipeline with sub-5 ms inference on embedded controllers, enabling real-time prevention of lean spikes and over-rev failures before they escalate to mechanical damage.