We develop integrative computational approaches to advance genome biology, functional annotation, and conservation genomics in plants, with a particular focus on forest trees and other species of conservation concern. Our work spans genome assembly and curation, transcriptome reconstruction, gene and repeat annotation, detection of conserved and adaptive genomic elements, and the application of machine learning and statistical methods to improve accuracy and scalability across these tasks.

To translate genomic resources into applied action for conservation and breeding, we build open source, web-based platforms that enable researchers to access, analyze, and visualize genomic, phenotypic, and environmental data. This includes developing FAIR repositories and geospatial tools that integrate genotypes, phenotypes, environmental metrics for improved data discovery and interoperability.

We develop computational frameworks to investigate genome evolution and the genetic basis of complex traits, with an emphasis on resilience to pests and pathogens, and adaptive potential to climate change. By connecting genomic data with ecological context, our research aims to support decision making for conservation and restoration.