People

Giles Hooker

Giles Hooker’s primary focus is on the interface of mathematical models for biological processes and data observed from them. He has particular expertise in using machine learning methods, functional data analysis and nonlinear dynamics. A particular focus of his research is in the interface of data mining with statistics, assessing the statistical evidence for patterns found in data and using machine learning models within more classical statistical modeling frameworks. His work is applied in ecology, epidemiology, evolution and in modeling large-scale bird ecology.

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