Stephen Douglass is particularly interested in the intersection of computer science and biology. His research focuses on developing and applying computational methods to address biological questions. In his past research, Douglass applied machine learning and Bayesian statistics methodologies to study gene expression and splicing, genome assembly, and gene regulation by microRNAs with diverse applications, including ecology, agriculture, biofuel production, human health, and basic science.
Douglass’ current primary research emphasizes analysis of cutting-edge genomic technologies to simultaneously study the genome and population dynamics of local species.
Professor Douglass teaches courses in the computer science and biology departments. His teaching style emphasizes collaborative, hands-on learning, while providing context through discussions of applications and current research.
Professor Douglass mentors students with a wide array of interests from the biology and computer science departments. He enjoys helping students create personalized research projects to explore their areas of interest.