Ben Augustine is a biologist and quantitative ecologist with 10+ years translating complex ecological questions into novel statistical models and estimation algorithms, currently applying those skills at the U.S. Geological Survey. His work spans eDNA dynamics in river networks, spatial capture–recapture and mark–resight methods, and integrating machine/deep learning classification error into abundance estimation for birds and marine mammals. A collaborative interdisciplinary researcher and mentor, he routinely pairs ecological field work (from camera traps to GPS collars) with advanced statistical solutions to deliver actionable wildlife management insights. Ben’s blend of rigorous mathematical training (MSc in Mathematical Statistics, PhD in Fish and Wildlife Conservation) and applied experience gives him a rare ability to move methods from theory to operational monitoring, including early invasive species detection. An active academic author with a public Google Scholar profile and a GitHub presence, he combines open research practices with practical tools for conservation science.
10 years of coding experience
10 years of employment as a software developer
Ph.D, Fish and Wildlife Conservation, Ph.D, Fish and Wildlife Conservation at Virginia Tech
M.SC., Mathematics Statistics, M.SC., Mathematics Statistics at University of Kentucky
Models fit: 2-Flank spatial partial identity model (SPIM), categorical SPIM, conventional and generalized categorical SMR. You should probably email me if you want to use this package. ben.augustine@cornell.edu.
Contributions:79 pushes, 1 branch in 7 years 10 months
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