Andrew studies the genetics of adaptation with a focus on the mechanisms by which epistasis, pleiotropy, and the underlying distribution of fitness effects (DFE) determine the properties of adaptive walks. Models of adaptation, such as Fisher’s geometric model, make assumptions about the properties of beneficial mutations and the relationships between genotype, phenotype, and fitness. Through the experimental evolution of viruses, he tests assumptions and hypotheses regarding the genetics of adaptation. In particular, he has investigated the underlying causes of epistasis and its effects on the interactions of beneficial mutations and constraints it imposes on adaptive trajectories and hybrid viability, characterized the distribution of beneficial mutational effects for adapting phages, and tested hypotheses regarding antagonistic pleiotropy and the cost of organismal complexity. His current work focuses on the development of new methods for inferring population genetic parameters from time-series polymorphism data that are applicable to viruses and other organisms with highly skewed offspring distributions, to analyze population genomic data from populations experimentally evolved under drug-induced selection.