Lillian Brixi builds high-throughput tools to measure the physical basis of how proteins work.
Brixi is currently developing methods to measure how proteins move and change shape. While machine learning can now predict static protein structures, it is how proteins fold, move, and interact that underlies biology and disease. By creating measurements across diverse proteins at scale, she can reveal how mutations alter function and how drugs bind their targets. Through this work, Brixi aims to co-design the data and models for protein AI that moves from static to dynamic.
Earlier, Brixi worked on the molecular mechanisms of gene regulation, the genetic underpinnings of complex diseases, and crop-yield prediction from satellite imagery. She is a Cameron Impact Scholar and a Regeneron Science Talent Search first-place winner.
Brixi was born in Denver, Colorado, and grew up running, hiking and skiing in the beautiful mountains of northern New Mexico.
