Scott is a PhD student in the Bioinformatics and Computational Biology (BICB) program and a concurrent MS student in Computer Science. He earned his undergraduate degree from Washington University, where he majored in Biology with a focus on neuroscience and genomics and minored in Bioinformatics. As an undergraduate, he conducted research on the relationship between circadian rhythms and Alzheimer’s disease.
In the Hsieh lab, his current research focuses on developing novel computational methods to analyze pangenome graphs to understand and predict human disease. These graphs contain all types of genetic variation, including those often missed by standard approaches. By creating new machine learning methods operating natively on the pangenome, he aims to create more comprehensive models of the genetic architecture of complex diseases. Outside of his research, Scott enjoys producing music.
