RESEARCH TEAM

Nathan Layman

Data Scientist · University of Idaho

Nathan Layman is a University of Idaho data scientist with a Ph.D. in Biology from Washington State University. His background combines evolutionary theory, Bayesian modeling, and machine learning.

His published work includes using computer vision to predict the fine-scale distribution of animal reservoirs of zoonotic disease. He brings a computational ecology perspective to the Wildmarker team.