Eran Segal is a Professor at the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science, heading a lab with a multi-disciplinary team of computational biologists and experimental scientists in the area of Computational and Systems biology. His group has extensive experience in machine learning, computational biology, and analysis of heterogeneous high-throughput genomic data. His research focuses on Microbiome, Nutrition, Genetics, and their effect on health and disease. His aim is to develop personalized medicine based on big data from human cohorts. Prof. Segal published over 150 publications, and received several awards and honors for his work, including the Overton prize, awarded annually by the International Society for Bioinformatics (ICSB) to one scientist for outstanding accomplishments in computational biology, and the Michael Bruno award. He was also elected as an EMBO member and as a member of the young Israeli academy of science. Education: Prof. Segal was awarded a B.Sc. in Computer Science summa cum laude in 1998, from Tel-Aviv University, and a Ph.D. in Computer Science and Genetics in 2004, from Stanford University.
Models for Predicting Covid-19 Outbreaks
We will describe our models for predicting Covid-19 outbreaks in terms of cases, hospitalizations, and deaths, also modeling the effect of vaccination strategies.