Simon Gravel
Simon Gravel obtained his BSc and MSc in Mathematics and Physics from the Universit茅 de Montr茅al and his PhD in Physics from Cornell University in 2009. His research in Genetics began during a short postdoc in the Physics department at the Universit盲t zu K枚ln and the Kavli Institute for Theoretical Physics in Santa Barbara, and continued in the Genetics department at Stanford University. He joined the Department of Human Genetics at 91社区 and the Genome Quebec Innovation Centre in 2013.
I am interested in learning about biology and evolution through creative analysis of high-throughput biological data. My group develops mathematical and statistical methods that take advantage of diverse data sources to refine our understanding of fundamental parameters of human history and biology. My recent research has focused on reconstructing human history in diverse populations, studying questions related to the origins of modern humans and to the successive waves of migrations that led to the formations of contemporary populations in the Americas. I am involved in the 1000 Genomes project, where I have been particularly interested in reconstructing the histories of populations of Puerto Rico, Colombia, and Mexico. I am generally interested in understanding the genetic history of diverse populations, and have projects involving rainforest Hunter-Gatherers (aka Pygmies), Canadian First Nations, and African-Americans. These efforts on minority populations are particularly important because these populations have been traditionally underrepresented by medical research. Increasing our understanding of the patterns of genetic diversity in these populations facilitates their inclusion in mainstream medical research. This research is largely data-driven, and it combines modeling at multiple levels: we first wish to understand the fundamental biology underpinning evolution, such as the processes of mutation, recombination, and selection. To understand human genomes, we also need to understand how recent and ancient human history affected patterns of genetic diversity: ancient population expansions, recent migrations, and marriage patterns all impact genomic diversity, and in many cases we can reconstruct these events through careful modelling. Finally, we need to understand the behavior of cutting edge technology involved in the latest datasets Our group has projects focusing on anthropology and history, technology development, biology, and medicine, and we are always happy to explore new opportunities involving new technologies and creative mathematical modeling.
Statistical genetics, Population genetics, demography, equity and representation