At Braint Systems, I worked on backend services using FastAPI and PostgreSQL. I refactored legacy code in the Forecast Budgeting project, adding features, fixing bugs, and improving performance.
I also implemented REST APIs and database operations with SQLModel and SQLAlchemy, managed schema changes with Alembic, and containerized applications with Docker and Docker Compose.
For my Samsung Innovation Campus Artificial Intelligence graduation project, I developed HemaAI, an explainable system for analyzing Complete Blood Count results. It evaluates 14 blood indicators using age- and sex-specific reference ranges and combines rule-based reasoning with machine learning to identify abnormal patterns and rank medical hypotheses.
I implemented HemaAI's backend services with Python, FastAPI, and PostgreSQL, integrating data processing and machine learning components. Earlier, I presented Truck Up, an Android application project where drivers can post available trips and employers can post cargo transportation requests.

