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.
