Jonathan Marchini – Regeneron Genetics Center, Tarrytown – US
Jonathan Marchini is Head of Statistical Genetics and Machine Learning at the Regeneron Genetics Center. Jonathan’s research is broadly in the area of Statistical Genomics. He has published methodological papers on SNP and CNV genotype calling, Bayesian association tests, population structure inference, gene-gene interactions, haplotype estimation, genotype imputation, variant calling from sequencing, multi-phenotype analysis, tensor decomposition for rna-sequence analysis and multi-omics data integration, and gene-environment interactions.
Jonathan received his undergraduate degree in Pure Mathematics and Mathematical Statistics from the University of Exeter, UK. At Oxford he did his DPhil in Statistics of statistical image analysis of MRI and fMRI brain imaging, followed by a Wellcome Trust Fellowship in statistical genetics. From 2006 to 2018 he was Professor of Statistical Genomics at Oxford, a Group Leader at the Wellcome Center for Human Genetics and a Tutorial Fellow at Somerville College. He has played key roles in the statistical analysis of many large scale projects in human genetics, such as the HapMap project, the Wellcome Trust Case Control Consortium, the 1000 Genomes Project, the Haplotype Reference Consortium, the UK Biobank and Genomics England.
His research group at Regeneron focusses on developing and applying statistical methods to meet the challenges of working with sequencing and genotyping data at the scale of 1 million samples a year.