Eugene Katsevich

Eugene Katsevich is an Assistant Professor of Statistics and Data Science at the University of Pennsylvania's Department of Statistics and Data Science. His research focuses on high-dimensional variable selection, multiple testing, and applications to genetics and genomics. He holds a Ph.D. in Statistics from Stanford University and an A.B. in Mathematics from Princeton University. Katsevich has contributed to various research publications and has taught courses in modern data mining and statistical methodology at the University of Pennsylvania.

Eugene Katsevich is an Assistant Professor in the Wharton Statistics Department, specializing in multiple hypothesis testing, variable selection, high dimensional inference, and statistical genetics. His research focuses on developing statistical methods for complex biological data, including single-cell CRISPR screens, GWAS loci analysis, and cryo-EM heterogeneity. He has contributed to improving the calibration and sensitivity of CRISPR screen analysis, as well as advancing methods for simultaneous inference under dependence. His work also includes robust differential expression testing and integrating GWAS data with CRISPRi screens to uncover genetic etiology. Katsevich's research bridges statistical theory with applications in genomics and biomedical imaging.