Giles Hooker

Giles Hooker is a Professor of Statistics and Data Science at the University of Pennsylvania's Department of Statistics and Data Science. His research interests include Machine Learning, Functional Data Analysis, Differential Equations, Computational Statistics, and Statistical Ecology. He teaches courses such as STAT4700 and STAT5800, focusing on data analysis and advanced statistical computing. Hooker's work has been published in journals such as Ecology Letters and Machine Learning, and he maintains an active research profile through his website.

Giles Hooker is a Professor of Statistics and Data Science at the University of Pennsylvania, specializing in Statistics, Machine Learning, and Dynamical Systems. His research focuses on developing statistical methods for complex data analysis, including functional data analysis, model interpretation, and uncertainty quantification. Hooker's work addresses challenges in ecological modeling, biodiversity studies, and the evaluation of machine learning models. He has contributed to the development of tools for model explanation, such as S-LIME and distill-and-compare, and has explored the application of statistical techniques in fields like environmental science and health diagnostics.