01 / MEET ME
Behind every data point,
there is a person.
I'm Tianyi Yu. I build research software to understand biomedical language, learn from medical images and examine predictions in health.
A clinical note holds someone's story. An image can carry a clue that is easy to miss. A risk score may shape what happens next. Those connections are what draw me to AI for health.
I'm especially interested in what happens after a promising result: does it survive a different hospital, a new population or the messiness of everyday care? I share the code so others can explore those questions with me.
04 / HOW I WORK
Keep the question open.
Make the method visible.
I care about the assumptions behind a result as much as the result itself. Sharing a pipeline makes room for someone else to notice a fragile choice, ask a better question or take the work somewhere new.
Each repository documents its inputs, environment and analysis steps. Some projects require credentialed clinical data or separately acquired datasets; their guides explain those boundaries. The illustrations here are conceptual artwork.