Educational digital twin platform for power systems, integrating simulation, data pipelines, and forecasting to support decision-making and system understanding.

A predictive framework integrating forecasting, power modeling, and checkpointing to enable energy-aware decision support across smart grids and intermittent systems.

Developed a forecasting platform combining LSTM and LightGBM models to predict energy consumption across multiple horizons, enabling comparative analysis between historical and predicted demand.

Designed multi-horizon forecasting models to predict battery voltage and support checkpointing decisions in solar-powered intermittent systems.