Gene Katsevich is a third-year statistics PhD student at Stanford
University. He is interested in applying statistics to biomedical problems. In
particular, he is currently working with advisor Chiara Sabatti on statistical
methods for associating genetic variants to a set of phenotypes in a way that
controls appropriate false discovery rates and leverages biologically relevant
group structures.
Gene did his undergraduate studies in math at Princeton
University, where he worked on medical and biological inverse problems. Working
with Princeton Professor Amit Singer, he developed a statistical methodology
allowing biologists to visualize multiple functionally relevant structural
states of a molecule.
In his free time, Gene enjoys dancing, basketball, and cooking.