Automated manual health tracking into a structured workflow with ML-driven pattern detection and insight generation.

• ›Designed ingestion pipelines to convert raw user inputs into validated, analysis-ready datasets.
• ›Implemented trend and anomaly detection to surface meaningful health insights.
• ›Built backend services to support reporting and future optimization.

FastAPI and PostgreSQL backend supporting trip ingestion, analytics, and reporting for future optimization use cases.

• ›Developed REST APIs for automated trip data ingestion and processing.
• ›Designed scalable relational schemas for maintainable backend workflows.
• ›Generated structured datasets to support analytics and forecasting.

Multithreaded Python server handling concurrent clients with robust lifecycle tracking and validation.

• ›Built a multithreaded server to manage concurrent connections.
• ›Implemented structured logging and validation for fault-tolerant operation.