I am a population geneticist and bioinformatician with a passion for data analysis and visualization, and a strong interest in data science and computation. I am a self-taught speaker of multiple programming languages, such as R and Python. I study the genomic diversity and structure of natural populations through space and time using next-generation DNA sequencing data. My approach is strongly data-driven, using advanced statistical techniques like approximate Bayesian computation, k-means clustering, linear modeling, artificial neural networks, data simulation, principal component analysis and supervised learning algorithms such as random forest classification. My primary goal is to understand how ecological and evolutionary processes shaped past and present natural populations, in particular in migratory marine vertebrates such as sea turtles, whales and seals. I also work on developing miscellaneous computational tools for working with population genetic data, as well as bioinformatic pipelines for the automated processing, analysis and visualization of large-scale population genetic data generated using next-generation sequencing approaches.
