We want to be able to predict how populations will evolve. (For example, when a new antibiotic is developed, we would like to know whether bacteria will become resistant in weeks, decades, or somewhere in between.) This goal is just starting to become realistic, thanks to rapidly advancing genetic sequencing technology. Now we need to solve a pair of theoretical problems in order to translate all the new sequence data into evolutionary predictions. First, we need to understand how to infer prevailing population dynamics from population genomic data. Second, given these patterns, we need to calculate the spectrum of possible evolutionary trajectories. Within these broad areas, our research focuses on several key questions listed below.

Projects:

• Multi-step adaptation: When can it happen? How, and how quickly?
• Inference from genomic data: What can we learn about populations from their genomes?
• Interference among genes: How do associations among alleles affect evolution?
• Pathogen evolution and population dynamics: How do pathogens spread and evolve?
• Spatial structure: How are populations structured in space? How does this structure affect adaptation?

Publication list at Google Scholar.