
Computational Statistics

Machine Learning

Statistical Methodology

Statistical Theory
Computational Statistics
Machine Learning
Statistical Methodology
Statistical Theory
The statistical theory group works on the investigation of fundamental principles to perform estimation, inference and prediction in largescale highdimensional models, with expertise in both asymptotic and nonasymptotic methods, graphical models and causal inference, Monte Carlo methods, learning theory and optimisation for machine learning.
Faculty
George Deligiannidis
Computational Statistics, Monte Carlo methods
Robin Evans
Graphical models, causality, algebraic statistics
Patrick Rebeschini
Learning theory, Optimization, Implicit Regularization
Judith Rousseau
Bayesian statistics, Asymptotics, Nonparametric statistics
Graduate Students
Tyler Farghly
Learning theory, Optimisation, Monte Carlo methods
Jake Fawkes
Causal Inference, Machine Learning, Fairness