Learning human biology and evolution

We design, develop, and deploy new algorithms for predicting evolutionary variation from OMICS data sampled in humans, primates, and beyond!

Predicting adaptation & ancestry with statistical modeling

We are developing a number of systems to test fundamental evolutionary hypotheses about rapid evolution in nature using insects

Statistical Population Genomics: predicting adaptation & ancestry

We study population genomic variation using new predictive and Bayesian approaches for classifying genomic regions, predicting genetic ancestry, and reconstructing demography. We seek to apply these methods in several insect systems to illuminate the molecular basis of rapid adaptation.

Data science in Genomics ☕️

We are developing and applying an array of statistical learning algorithms for predicting drivers of functional trait evolution (e.g., gene expression), and models of genome evolution.

Mathematical & Algorithmic Phylogenetics:

putting the genome into phylogenomics

We are developing and applying an array of new approaches for dissecting chromosome-scale variation in genealogical history, and for testing hypotheses concerning variation among individuals, populations, and species

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We are actively recruiting undergraduate and graduate student researchers!

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