About

Hey, I’m Hunter. I’m a machine-learning engineer, and I’ve spent the better part of a decade building models and data pipelines. I grew up in the Bay Area, earned a master’s in Computational & Mathematical Engineering at Stanford, and did a double-major bachelor’s in Physics and Mathematics at Sonoma State. That quantitative background has carried me through academia, industry, and a few space-related projects.

The work has been a series of problem-focused sprints: pipelines that let hospitals monitor data drift across multiple sites, edge-deployed computer-vision models that cut hardware costs, synthetic-patient datasets that keep privacy intact while still supporting research. On the clinical side I’ve built ECG-based detectors for pulmonary hypertension, quantified long-term risks after traumatic brain injury, and written survival-analysis frameworks that surface hidden comorbidities. Some of it has ended up in good journals (JAMA Network Open, Nature Aging, Chest) and led to collaborations with pharma companies. I also got to work on the first batch of pocketqube satellites while at Sonoma State.

Away from the keyboard, I keep a small garden. Beets are my favorite; there’s something satisfying about watching them go from seed to plate. On weekends I’m usually rolling dice in a monthly Dungeons & Dragons campaign or arguing over a board game. I also write generative music that reacts to ambient sound and environmental data, so no two listens are quite the same.

I’m not one for buzzwords. I like clear, data-driven answers, and I’ll say so when I don’t know something. If you’re working on a hard problem and want a straight answer, feel free to reach out.