Crafting AI with intent.
A short story of how I work, what I've shipped, and where I want to go next.
I'm a Computer Science Engineering student specializing in Artificial Intelligence and Machine Learning. My work sits at the intersection of applied research and product engineering — building computer vision systems, data analytics tools and retrieval-augmented AI assistants. I care about models that are accurate, observable, and useful in the real world, not just on a notebook.
Over the last two years I've built end-to-end ML systems: a CNN-based facial recognition attendance platform, a GitHub repository quality analyzer, and a retrieval-augmented legal advisor. Each project pushed me deeper into the lifecycle — data, modeling, evaluation and deployment.
I work primarily in Python with the scientific stack (NumPy, Pandas, scikit-learn, OpenCV) and serve models with FastAPI. I'm comfortable taking a problem from a vague brief to a measurable baseline, and iterating until it ships.
I'm currently exploring multimodal learning, RAG architectures, and on-device computer vision — and I'm open to ML engineering and applied research opportunities.