Stilianos Louca, Ph.D.

Assistant Professor, University of Oregon

Stilianos Louca was initially trained as a physicist and mathematician in Germany and France, but soon became interested in biological systems and the idea of applying his quantitative skills and analytical thinking to understanding Life. He completed his doctorate in applied mathematics at the University of British Columbia, Canada. During that time, he became particularly fascinated by the ongoing sequencing revolution in microbiology, which started yielding massive datasets that could be analyzed using methods similar to statistical physics and differential equation models. His Ph.D. thesis, titled “The ecology of microbial metabolic pathways,” examined whether the rates and distribution of microbial metabolic pathways can be predicted purely from a gene-centric perspective. For his work, he was awarded the 2017 International Grand Prize for Young Scientists in the Life Sciences by Science/AAAS and SciLifeLab. Louca is now an assistant professor in the Department of Biology at the University of Oregon.

Louca is primarily driven by fundamental questions about life, rather than an interest in a particular organism or location. Over the years, his study systems have thus ranged from Saanich Inlet (off the coast of Vancouver Island) to Cariaco Basin (off the coast of Venezuela), microbial communities inside the water reservoirs of Bromeliad plants in Brazil, lake sediments in Vancouver, British Columbia, the global ocean microbiome (using data from Tara Oceans) and microbial mats in hot springs and soda lakes (e.g., Yellowstone National Park). Louca’s work generally has a strong quantitative component, including analyses of large genetic, genomic and metagenomic datasets, simulations of mathematical models (such as partial differential equation models for marine biogeochemistry) and phylogenetics, however his lab also conducts experiments in the lab and field surveys in remote areas. Louca’s lab also develops new computational tools, such as a software for predicting the phenotype of marine microorganisms based on their phylogenetic placement, and software for analyzing massive microbial phylogenies comprising hundreds of thousands of taxa.

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