Build, train, and benchmark ML models (e.g. LSTM, XGBoost) for battery State-of-Health (SOH), Remaining Useful Life (RUL), and degradation prediction. Analyze large-scale battery performance data to extract actionable insights. Develop anomaly and event detection algorithms for safety-critical battery threats.