Binbin Chen is a Genetics MD/PhD student at Stanford working with Russ Altman and Ash Alizadeh. His research applies machine learning to immunology, where he has developed leading algorithms to predict antigen presentation in MHC and to identify potential drug targets for rare diseases. He is a PD Soros and Stanford Bio-X Fellow, as well as a recipient of a Magic Grant from the Brown Institute for Media Innovation. Binbin’s work has been published in Nature, Nature Biotechnology, and Blood. Recently Binbin and his colleagues applied machine learning to identify vaccine candidates from SARS-CoV-2 genomes, the result of which is available online on BioRxiv.