معرفی
Giles Hooker is a Professor of Statistics and Data Science at the Wharton School, University of Pennsylvania, with his office located at 409 Academic Research Building, 265 South 37th Street, Philadelphia, PA 19104. He teaches courses including STAT4700 (Data Analy & Stat Comp), STAT5030, STAT9916 (Sem in Adv Appl of Stat), STAT9950 (Dissertation), and STAT9999 (Independent Study).
Dr. Hooker's research focuses on the interfaces of statistical inference with models from machine learning and applied mathematics. His primary interests include Machine Learning, Functional Data Analysis, Differential Equations, Computational Statistics, and Statistical Ecology. He specializes in uncertainty quantification in random forests and ordinary differential equations models, as well as robust statistics. Much of his work is application-driven, particularly in ecology, epidemiology, environmental sciences, and medicine.
His recent publications (2021-2024) reveal a strong emphasis on interpretable machine learning, statistical stability in model distillation, and ecological modeling. He has developed significant software packages including fda for functional data analysis in R and Matlab, and CollocInfer for fitting differential equations to data, complete with extensive documentation.
Dr. Hooker has presented at conferences including the Conference on Applied Statistics in Ireland (2023) where he delivered a short course on Inference and Interpretation in Machine Learning. His methodological contributions span from profiled estimation of differential equations to functional data analysis techniques.
