Originally trained in Industrial and Systems Engineering, he obtained his PhD in Statistics from the University of Michigan, while completing Masters degrees in Applied Mathematics and Human Genetics. Dr. Shojaie's research lies in the intersection of machine learning for high-dimensional data, statistical network analysis and applications in biology and social sciences. Dr. Shojaie's team has developed methods and publicly available software for network-based analysis of various types of “omics” data, as well as high-dimensional time course data from molecular biology and neuroscience. Dr. Shojaie is a PI of the Statistical Learning Applied to Biostatistics Lab (SLAB LAB) and is Director of the Summer Institute in Statistics for Big Data (SISBID).