ISHMAM Jahin completed Energy and Renewable: Machine Learning for the Power Grid

Built an end-to-end gas-turbine yield predictor using leakage-free sensor inputs, a time-based held-out split, and a baseline-vs-forest comparison. The candidate reported honest held-out performance (about 1.5 MWh MAE, 1.9 MWh RMSE, R² ≈ 0.98), checked residual behavior, and documented practical limits, including single-plant scope and drift monitoring.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Residual-Based Error Diagnosis
• Plain-Language Model Communication