I'm a Computer Science student fascinated by the spaces where machine learning, full-stack engineering, and embedded systems collide. From training models on messy real-world data to wiring up ESP32 boards, I love shipping ideas end-to-end.
My focus is on building AI/ML systems that feel useful and trustworthy — clean pipelines, honest evaluation, and interfaces people actually understand.
I'm equally comfortable in a Jupyter notebook, a React codebase, or in front of a breadboard. I treat every project as a chance to learn the next layer of the stack.
Outside class, you'll find me reading ML papers, contributing to small open-source tools, and tinkering with IoT side projects.