Daniela Castro-Camilo
Daniela Castro-Camilo
Senior Lecturer in Statistics, University of Glasgow
I develop statistical methods to understand, predict and attribute environmental and disaster-related extremes. My work lies at the interface of extreme value theory, spatial and spatio-temporal statistics, Bayesian inference and causal inference, with most applications in the natural environment.
A recurring theme in my work is the development of practical, user-friendly methods that promote the need to adequately capture extreme observations within the usual statistical analysis centred around mean values.
I’m co-founder of GLE²N (Glasgow-Edinburgh Extremes Network). Visit our homepage!
Research at a glance
Extreme-event attribution and causal inference
Dependence modelling in space and time
Fast Bayesian inference for spatial models
Hazard assessment and susceptibility modelling
Statistical methods for environmental and ecological extremes
Weather-driven risk for energy systems and critical infrastructure