An industrial digital twin solution for Combined Cycle Power Plants (CCPP). This project leverages XGBoost machine learning models and mathematical optimization (SLSQP) to predict net electrical output and prescribe the optimal exhaust vacuum setpoint, maximizing thermal efficiency based on real-time environmental conditions.

Enterprise Data Warehouse project for Chocolate Manufacturing using SQL Server, ETL, and Data Analytics.

Data & Analytics Expert specializing in optimizing industrial operations through end-to-end data science solutions. Focus on supply chain, maintenance, and production optimization using Python (Pandas/Scikit-learn), SQL, and machine learning to drive efficiency and cost savings.