CS Student · Future AI Engineer · Builder
I build practical software, study computer science, and contribute to open source.

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Languages and systems

Tools and deployment

Web, APIs and CI

_{C · C++ · Python · Databases · Search · AI and ML · Open source}

I focus on building reliable software while strengthening my foundations in computer science and working toward AI engineering.

• Systems and databases: C, database internals, B trees, storage, and data structures
• Search and algorithms: tokenization, inverted indexes, Boolean queries, and TF-IDF ranking
• Backend engineering: Python, REST APIs, authentication, data validation, and testing
• AI and machine learning: Developing my knowledge through practical work and continued study
• Open source: Fixing concrete issues, writing regression tests, and working with existing codebases

I contribute to existing codebases by learning the surrounding implementation, solving concrete issues, adding tests, and responding to maintainer feedback.

A small relational database engine inspired by SQLite in C11 with a SQL parser, persistent pages of 4096 bytes, leaf splits in a B tree, and an interactive shell. It supports INSERT and SELECT, including WHERE id equals a value, and validates stored metadata and B-tree structure. Its file format is specific to this project and is not compatible with SQLite database files. The project includes automated tests, a insertion benchmark with 1,000 rows, and CI checks with AddressSanitizer and UndefinedBehaviorSanitizer.

A Python search engine with text normalization, stop word filtering, an inverted index, AND and OR queries, quoted phrase search, TF IDF scoring, deterministic rankings, JSON persistence, and a command line interface. CI runs tests on Python 3.11, 3.12, and 3.13 and checks the code with Ruff.

An agricultural decision support app in active development, with a Flask API, validated simulation inputs, and early access signup backed by SQLite. Simulation results remain unavailable when required agricultural or economic inputs are missing, and version 2.0 is not deployed. The older prototype is available separately.

A FastAPI REST API for authenticated secret storage using PostgreSQL, asynchronous SQLAlchemy, Argon2 password hashing, JWT access tokens, and Fernet encryption. Secret queries are scoped to the authenticated owner. The project includes audit events, Alembic migrations, and integration tests backed by PostgreSQL in CI. It is a learning project, not production ready.

_{The contribution Snake is refreshed automatically from GitHub's public contribution data.}