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Developed an XGBoost model with marine sensor data to predict engine failures and integrated anomaly detection using Isolation Forest and SHAP for explainability. Deployed a Streamlit dashboard with Docker on AWS EC2, achieving less than 10% error in hourly fuel prediction and enabling 12% average fuel savings.

Utilized Random Forest on operational metrics for ship fuel efficiency estimation and developed a digital twin model that prevented 4 unplanned engine shutdowns in simulation testing. Deployed a REST API using FastAPI for real-time inference, achieving 92% classification accuracy on real-world ship telemetry data.

Achieved a 0.91 ROC AUC with XGBoost on telecom usage data for customer churn prediction, identifying key churn factors such as contract type and payment method. Visualized top churn factors using SHAP and Streamlit, achieving 89% AUC and 85% accuracy on test data.

Founded and managed a mobile apps development company, overseeing various aspects of the business from conceptualization to deployment. Led teams in developing mobile applications for diverse clients.

Worked as a Salesforce CRM Developer, contributing to the development and implementation of CRM solutions. Gained experience in Salesforce platform functionalities and client relationship management.

Completed a Master of Technology degree focusing on marine technology. Gained specialized knowledge in the application of technology within marine environments.

Obtained a Bachelor of Technology degree with a focus on Information Technology. Developed foundational skills in IT principles and applications.