ml + data science
i’m a senior at the university of washington finishing up a bs in applied math, and i'll be sticking around seattle this fall to start my ms in applied & computational mathematics.
my work sits at the intersection of machine learning and scientific computing—whether that’s engineering diffusion models for 3d protein reconstruction at deeptracer or building tools like benē to help people navigate complex government systems. i’m driven by the idea of making technical infrastructure more intuitive and accessible.
i also produce and spin deep/minimal house, obsessing over textures and basslines as much as i do over clean code.
track winner @ uw ai student collective hackathon
millions of people qualify for benefits they never claim. benē fixes that: answer 5 questions, get a full eligibility breakdown with estimated monthly value and next steps.
real-time object detection pipeline using YOLO and PyTorch, enabling rapid inference and classification of tennis balls in video streams. designed custom visualization tools to overlay bounding boxes and confidence intervals on raw video data, improving model interpretability and error analysis.
utilized logistic regression and gradient descent to create a model that predicts a student’s likelihood of securing a job after graduation; achieved 90.4% model accuracy.
pioneer xdj-xz — move your mouse over it