INLA

MetricGraph

MetricGraph: A Statistical Framework for Modeling Gaussian Fields on Metric Graphs

Raphaël Huser’s article among the top downloaded articles in Springer’s Environmental Sciences Journals

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Luigi Lombardo, Thomas Opitz, and Raphaël Huser’s article “Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster”, published in the scientific journal Stochastic Environmental Research and Risk Assessment (SERRA), in July 2018, is among the top downloaded articles in Springer’s Environmental Sciences Journals for the year 2018. Huser is an Assistant Professor of statistics in the CEMSE division and principal investigator of the Extreme Statistics (extSTAT) Research Group at KAUST.

Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA book

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Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real

High-resolution Bayesian mapping of landslide hazard with unobserved trigger event

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New paper accepted: Opitz, T., Bakka, H., Huser, R. , and Lombardo, L. (2021+), High-resolution Bayesian mapping of landslide hazard with unobserved trigger event , Annals of Applied Statistics, to appear [ arXiv][ PDF preprint ].

Jonatan A. González

Postdoctoral Research Fellow, Statistics
Jonatan's research interests lie between spatial statistics and coding, emphasising point processes, epidemiology, infectious disease modelling and, generally, application-focused methods. He has a bachelor's degree and a master's background in mathematics. He completed his PhD in spatial and spatio-temporal point processes at the University Jaume I. Jonatan's research projects include techniques for dealing with point patterns: replicated observations, spatio-temporal analysis, graphical methods, hypothesis testing, experimental design and local characteristics. In addition to the core

Daniela Castro-Camilo

Postdoctoral Research Fellow, Statistics
Dr. Daniela Castro-Camilo was a postdoctoral fellow in the Extreme Statistics Research Group of Prof. Raphaël Huser from November, 2015, to May, 2019, doing research on the theory and applications of multivariate and spatial extremes. After her postdoc at KAUST, Daniela moved to the University of Glasgow, United Kingdom, where she embraced an academic career by becoming a Lecturer (equivalent to Assistant Professor in the UK) of Statistics. See her personal webpage. Education and early career Daniela Castro-Camilo received her Ph.D. from Pontificia Universidad Católica de Chile in August 2015