Dr. Matthew Stephens is a preeminent scholar whose pioneering work has fundamentally shaped the field of statistical genetics and genomic analysis. He currently serves as the Ralph W. Gerard Professor in both the Department of Statistics and the Department of Human Genetics at the University of Chicago, where he leads a renowned research laboratory dedicated to developing innovative statistical methodologies. After completing his BA in Mathematics and Diploma in Mathematical Statistics at the University of Cambridge, he earned his D.Phil in Statistics from the University of Oxford under Brian D. Ripley, followed by postdoctoral research with Peter Donnelly that established his trajectory as a leader at the statistics-genetics interface.
Dr. Stephens pioneered the Structure computer program with Jonathan Pritchard, which revolutionized population structure analysis and individual admixture estimation in genetic studies worldwide. His development of the influential Li and Stephens model provided an efficient framework for linkage disequilibrium analysis that has become foundational to modern genetic research. His laboratory has produced multiple widely adopted software packages including PHASE and fastPHASE for haplotype inference, GEMMA for association testing, and SuSiE for variable selection and fine mapping, which collectively represent transformative methodological contributions to the field. These innovations have enabled critical advances in understanding complex genetic architectures and have been cited extensively across the scientific literature.
Elected as a Fellow of the Royal Society in 2023, Dr. Stephens has received numerous prestigious honors including the Guy Medal in Bronze from the Royal Statistical Society in 2006 and recognition as a Medallion Lecturer by the Institute for Mathematical Statistics in 2014. He has championed reproducible research practices through initiatives like the workflowr R package and his transparent 'research in the open' approach, setting new standards for computational genomics. His current research focuses on advancing methods for sparsity, shrinkage, and false discovery rates in complex genetic datasets, alongside novel matrix factorization techniques for genomic applications. Dr. Stephens continues to shape the future of statistical genetics through his rigorous methodological contributions, commitment to open science, and leadership in training the next generation of quantitative geneticists.
