Bio
Dr. Josh Gillard is a Canadian biomedical data scientist with experience in bioinformatics, machine learning, and immunology. After completing a BSc and a MSc in Experimental Medicine at McGill university, he relocated to the Netherlands for his PhD in bioinformatics at Radboud University in Nijmegen. During his PhD, he gained experience analyzing and interpreting complex immunological data (bulk and single-cell transcriptomics, high-dimensional cytometry, high-throughput proteomics) derived from human observational or intervention studies (vaccination and experimental human infection) in order to discover molecular and cellular correlates of clinically important endpoints such as disease severity, symptom progression, and antibody responses. In 2022, Josh relocated to Stanford to join the Gaudilliere lab to develop and apply multi-omic data integration and machine learning techniques, establishing that early gestational immune dysregulation can predict preterm birth. Since 2024, in the Ashley lab, Josh is focused on applying deep learning models to investigate aberrant splicing in cardiovascular disease.
