I am an interdisciplinary computational biologist interested in 1) applying and developing bioinformatic and spatial analysis tools for understanding population genomic variation and 2) testing the statistical performance of modern spatial population genomics methods using simulation. Thus far, most of my work falls under the subfields of population genomics referred to as landscape genetics and landscape genomics. Accordingly, I am experienced in various aspects of both spatial analysis and genomics analysis, such as the resolution of spatial patterns of gene flow and signatures of spatially divergent selection.

For my Ph.D., I am using next-generation sequencing data to study 1) how abiotic and biotic environmental variation impacts spatiotemporal patterns of genomic variation in the Tasmanian spotted-tailed quoll, a species impacted by the disease-driven decline of the Tasmanian devil and 2) the relative roles of gene flow, genetic drift, and natural selection in the context of the cane toad invasion of Australia. Third, I am using spatially explicit population genomic simulation to evaluate the performance of landscape genetics/genomics analyses. More information about these projects can be found on my website.

• Population genomics
• Spatial simulation
• Deep learning
• Genetic algorithms
• App development

• Identifying and fixing non-random missing data in population genetics (in progress)
• Simulate species presence-[absence] data for ecological niche models
• Simulate simple linear regression data