I got into oncology the way most people get into something that truly matters — not by plan, but by circumstance. Watching people close to me navigate a healthcare system that was, in theory, one of the best in the world, I kept hitting the same wall: diagnoses that came too late, too incomplete, with too much left to chance. If that was the reality in Europe, I couldn't stop thinking about what it looked like for someone facing the same disease in a low-resource setting, with a fraction of the access.

That question became an obsession. Imagine a system with access to all of it — one that learns from decades of patient records to understand which treatments will work, and which definitively will not. The world's oncologist. My entry point into that vision is pathology: tissue slides that are routinely collected in hospitals everywhere, yet rarely fully utilized. They contain biological signals too complex for the naked eye, too expensive to extract with standard assays at scale, but learnable — if you know how to teach a model to look. My research is about showing what's scientifically possible, publication by publication. StratifAI is about turning those possibilities into solutions that work in the clinic, not just in a paper — and making them accessible far beyond the top academic medical centres.

When I'm not building StratifAI, I read philosophy, seek out great coffee, and find quiet corners of the city to think. I'm drawn to people building things that are genuinely difficult and would have huge impact if they succeed. I grew up in the Netherlands with roots in Egypt, built my research career in Germany, and have since expanded to the US — pursuing my passion has made me a world citizen, and it's only the beginning.