Galen
Virtual cell models that help biology teams compare possible interventions before committing them to the lab.
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I'm a physician, computer scientist, and cofounder of Galen. We build virtual cell models that help biology teams identify valuable interventions.
Biology teams can map what exists and still struggle to choose what to change. Galen builds virtual cell models to help them compare possible interventions, focus expensive experiments, and keep every computational claim answerable to biology.
The longer arc is to move biology from maps to models to deliberate design—without losing contact with experiment or the people the work is meant to serve.
I learned on a cattle farm that care is concrete: notice what needs attention, find or create a solution, and stay until the work is done. Medicine brought me close to suffering and taught me how to treat it. Computing showed me a way to magnify that understanding for positive impact at scale.
That thread runs through everything here—from the operating room and a woodworking shop to scientific software and Galen. Read the story →
Virtual cell models that help biology teams compare possible interventions before committing them to the lab.
Visit Galen →A local, Git-audited loop for proposing, running, scoring, and keeping—or reverting—machine-learning experiments.
View the repository →A Rust genomics engine that treats memory as a contract and lets anyone inspect the result with a public verifier.
Verify it →You are building at the edge of biology and computation, developing scientific software or ML systems, bringing clinical judgment into technical work, assembling an unusually thoughtful team, or working on a problem where rigor and moral purpose both matter.