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Daniela Castro Camilo's research revolves around environmental disaster-related statistics, creating novel methods and applications to predict disaster occurrences and impacts. Her work combines theoretical and applied aspects of multivariate spatial extremes, spatio-temporal statistics, environmental statistics, causal inference, and Bayesian inference. Over the years, she has developed user-friendly methods that adequately capture extreme observations in statistical analysis, shifting the focus from mean values. Her methods are available through the R-INLA package on GitHub. Daniela actively contributes to the statistical community, serving as the meeting secretary for the Environmental Section of the Royal Statistical Society and as an associate editor for the journal Environmetrics. She is also a member of the International Environmetrics Society outreach liaison committee and an elected member of the International Statistical Institute.
University of Glasgow • Glasgow, Scotland
Teaching and researching in the field of statistics, focusing on environmental and disaster-related statistics.