I am an evolutionary biologist interested in understanding the causes and consequences of genetic variation across time and space. One of the fundamental goals of evolutionary biology is to quantify patterns of genetic diversity within and between populations to enable the study of the processes that shape them. However, the development of key statistical methods in population genetics lags behind the rapid generation of modern genomic datasets that require analysis. In particular, methods for studying population structure, demography, and natural selection in continuous space are still lacking, leading to a gap in our ability to answer basic questions in evolutionary biology. My research is focused on the geography of evolution: describing and quantifying spatial patterns of genetic variation between individuals and species, and developing computational and statistical methods for learning about the fundamental forces generating and maintaining those patterns. This work is highly integrative, combining statistics, computational approaches, population genetics theory, and a knowledge of the empirical systems in which I apply my methods.
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Bayesian Methods / Data Visualization / Geographic Information / Mathematical and Statistical Modeling / Statistics
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