Michael Zietz conducts research in the Department of Biomedical Informatics at Columbia University, advised by Nicholas Tatonetti. His research develops new statistical methods for analyzing large genetic and electronic health record datasets. He is particularly interested in understanding the genetic basis of common disease and deciphering the complex relationships between genotypes and phenotypes. Past and current projects include developing a new genetic risk estimation method, devising methods to increase the speed of pan-biobank GWAS, creating a summary-statistic-based GWAS method, and conducting observational research using electronic health records. He was previously at the University of Pennsylvania, where he worked with Casey Greene, receiving BA and MS degrees in Physics in 2019.