I like the work between an idea and a system people can rely on.

I studied Computer Science and Molecular and Cell Biology at UC Berkeley, with a neurobiology emphasis. That combination shaped how I work: I enjoy technical problems, but I care just as much about the human setting in which a system has to make sense.

At Seed Health, I built a working personalization and learn-to-earn demo, measured it in a pilot, and saw the member experience integrated into the broader product. I also built an internal source-grounded article generator. At Foundations to Mastery, I co-founded a tutoring practice and became the founding engineer for a platform that connects learning evidence, educator review, instruction, and operations.

QuietDesk is a different scale of project. I conceived the Mac utility and directed and tested its AI-assisted Swift implementation. It is a useful example of how I approach product constraints, experiments, and review.

I’m interested in software engineering and product engineering roles with meaningful ownership, strong peers, and problems that demand clear thinking across interface, backend, data, and operations. Applied AI is part of that work when it genuinely helps users and can be evaluated responsibly.