The statistical methods group develops modern methods for statistical modelling and inference. Particular interests include: graphical models, causal inference, medical statistics, phylogenetics, statistical genomics.

Faculty

Robin Evans

Graphical models, causality, algebraic statistics

Chris Holmes

Decision theory, biostatistics and precision medicine, probabilistic learning under model misspecification

Geoff Nicholls

Statistical modeling, Bayes Methods, Monte Carlo Methods.

Dino Sejdinovic

Statistical machine learning, kernel methods, nonparametric statistics

Graduate Students

Shahine Bouabid

Kernel Methods, Gaussian processes, Climate emulation

Christian Carmona Perez

Methods for Bayesian modeling under mispecification

Anthony Caterini

High-Dimensional Statistics, Monte Carlo Methods, Variational Inference

Alumni

• Benjamin Bloem-Reddy
• Jennifer Rogers