About

I spent fifteen years working to become an orthopaedic surgeon. Then, when the moment finally came, I decided not to. To understand why, you have to start on a cattle farm in rural Ohio.

It was physical work in a small community, and I grew up working with my hands and looking out for the people around me. Both stuck.

For as long as I can remember, what I wanted was to be a source of good in the world: to help the people who need it and be a reason for hope. My mom was a nurse practitioner, and growing up around her work, medicine was the first place I could see how to do that.

Between the farm and college, I spent two years as a missionary in South Korea, walking the streets of Seoul and learning enough Korean to spend my days teaching, and learning, about God. It was about as far from that farm as I could get, and the first time I gave myself fully to something bigger than my own plans. That set a pattern I never really broke.

I came back and walked on to the rugby team at Brigham Young University: no scholarship, no recruiting, just earning a spot. We won a national championship while I was there, still one of the things I'm proudest of.

After college I started medical school. The plan was orthopaedic surgery. I liked the directness of it: mechanical problems with mechanical solutions, the satisfaction of fixing something with your hands.

A few years in, when I was as broke as most medical students are, a pet of mine needed life-saving surgery I couldn't afford. I wasn't going to let the bill be the reason I lost an animal I loved, so I put the surgery on a credit card and started a hardwood-furniture business to pay it off. The building came easy. I'd spent my life doing manual labor, on the farm and in timber-frame construction, handy with tools long before I had a shop of my own. After several months and a lot of black walnut, the one-man garage operation had become an industrial-grade workshop — the first thing I ever built that was mine.

Those same years, I spent two summers on global-health expeditions, treating patients and assisting in surgeries in sub-Saharan Africa and the Himalayas. This was the medicine I'd wanted to practice all along: caring for people with almost no access to it. But it planted a worry I couldn't talk myself out of. A surgeon can only help the patients who make it to him, and I wasn't sure orthopaedics would ever take me back to the people who needed it most.

Late in med school I got quietly hooked on machine learning. It had nothing to do with what I was training for; it was just something I kept coming back to. So when a research year came up, I took a clinical-AI position at Harvard Medical School and taught myself to code to keep up with the engineers around me. About six months in, ChatGPT launched. I hadn't seen it coming, but it confirmed the instinct I'd been following on my own: what had felt like a private interest suddenly looked like where all of medicine was heading. The question had stopped being whether AI would change how disease gets treated, and started being who would do the work.

Even then, the plan was still surgery. What changed it was the timing. If AI was going to remake medicine, it would do it over the same thirty years I'd have spent as a surgeon. And it spoke to the worry those summers had planted: a scalpel only ever reaches the patient on the table, but software could reach the people who'd never get to a surgeon at all.

So I had a choice. I could stay on track for a secure, respected career, more money than a kid from a Rust Belt cattle farm is ever supposed to walk away from. Or I could step off and help build it myself.

I was already interviewing for residency when I made the call. When the Match came, I didn't put my name in.

So I enrolled at Carnegie Mellon for computer science instead, and took the long way in on purpose. Solving disease at scale was never going to come from off-the-shelf models pointed at clinical data; it meant learning computing and AI from first principles, deep enough to build the systems medicine doesn't have yet, not just apply the ones it does. Along the way I published some theoretical physics too, mostly out of curiosity: a different field, but the same pull toward understanding how things actually work, all the way down. Looking back, the things that had seemed like detours from medicine — the workshop, the physics, the machine learning — were never detours at all. They had been pointing at the same conviction the whole time.

Now I'm in San Francisco building Galen Health, working toward a virtual cell: a problem that lives exactly where physics, computing, and medicine meet, which is to say right where I've already spent my life. It's the one skill I'm sure I have, and the largest thing I could ever aim it at. Model a cell faithfully enough and its diseases become problems you can reason about from the root. Precision medicines designed instead of discovered. Conditions that are terminal today made survivable. Whole diseases solved at the source, not one patient at a time. The ceiling on that work isn't the room you're standing in; it's every life the disease will ever touch.

It's the answer to the worry those expeditions planted: a way to reach the people who'd never make it to a surgeon at all. It'll take years, and it's far from finished. But it's the truest version I've found of what I wanted from the start: to be a source of good in the world, and to do as much of it as a single life can. That's something the safe, respected path I left could never have promised, and the part I find most worth doing.