spatio-temporal statistics

Bayesian Modeling of Sub-Asymptotic Spatial Extremes

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B5 L5 R5220

In this thesis, we develop new flexible sub-asymptotic extreme value models for modeling spatial and spatio-temporal extremes that are combined with carefully designed gradient-based Markov chain Monte Carlo (MCMC) sampling schemes and that can be exploited to address important scientific questions related to risk assessment in a wide range of environmental applications. The methodological developments are centered around two distinct themes, namely (i) sub-asymptotic Bayesian models for extremes; and (ii) flexible marked point process models with sub-asymptotic marks. In the first part, we develop several types of new flexible models for light-tailed and heavy-tailed data, which extend a hierarchical representation of the classical generalized Pareto (GP) limit for threshold exceedances. Spatial dependence is modeled through latent processes. We study the theoretical properties of our new methodology and demonstrate it by simulation and applications to precipitation extremes in both Germany and Spain.

The Lambert Award for Young Statisticians Goes To Raphael Huser

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Today Raphael Huser, Assistant Professor at King Abdullah University of Science and Technology (KAUST), received the Lambert Award for Young Statisticians for his contribution in modeling the distribution of extreme weather events.

2015 Workshop on Computational Space-Time Statistics

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Organizers : Prof. Marc G. Genton , Chair of Spatio-Temporal Statistics and Data Science Group Prof. Raphael Huser, Chair of Extreme Statistics Group​ Prof. Ying Sun​, Chair of Environmental Statistics Group Confirmed speakers: Prof. Sudipto Banerjee, University of California Los Angeles, USA Prof. Souhaib Ben Taieb, Monash University, Australia Prof. Stefano Castruccio, Newcastle University, UK Prof. Miguel de Carvalho, Pontificia Universidad Catolica de Chile,​ Chile Prof. Clément Dombry, University of Franche-Comté , France Prof. Xuming He, University of Michigan, USA Prof. Hsin-Cheng Huang

New paper accepted in JABES

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New accepted paper: Castro-Camilo, D., Huser, R., and Rue, H. (2019+), A spliced Gamma-generalized Pareto model for short-term extreme wind speed probabilistic forecasting, Journal of Agricultural, Biological and Environmental Statistics, to appear [ PDF preprint]

KAUST Assistant Professor Raphaël Huser receives American Statistical Association award

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KAUST Assistant Professor Raphaël Huser recently received the American Statistical Association's (ASA) 2019 Section on Statistics and the Environment (ENVR) Early Investigator Award for his outstanding contributions to environmental statistics. He accepted the award at the 2019 Joint Statistical Meetings held in Denver, Colorado, U.S., from July 27 to August 1.

New paper accepted in Extremes

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New paper accepted: Zhang, Z., Huser, R., Opitz, T., and Wadsworth, J. L. (2021+), Modeling spatial extremes using normal mean-variance mixtures, Extremes, to appear [ arXiv][ PDF preprint]

Rishikesh Yadav

Ph.D. Student, Statistics
Rishikesh Yadav was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Rishikesh successfully defended his PhD thesis entitled " Bayesian Modeling of Sub-Asymptotic Spatial Extremes" on April 5th, 2022; see his PhD thesis here. His PhD committee was composed of Professors Raphaël Huser (chair), Philippe Naveau (external examiner from CNRS, France), Marc Genton, and Ajay Jasra. For his next career steps, Rishikesh has accepted a postdoctoral position at HEC Montréal, Canada, under the joint supervision

Raphaël Huser

Associate Professor, Statistics
Professor Huser develops novel statistical methodology and machine learning solutions to model and predict extreme events in various applications ranging from climate and earth sciences to finance and neuroscience.

Peng Zhong

Ph.D. Student, Statistics
Peng Zhong was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Peng successfully defended his PhD thesis entitled " Modeling and Simulation of Spatial Extremes Based on Max-Infinitely Divisible and Related Processes" on April 4th, 2022; see his PhD thesis here. His PhD committee was composed of Professors Raphaël Huser (chair), Daniel Cooley (external examiner from Colorado State University, US), Marc Genton, and Ajay Jasra. For his next career steps, Peng has accepted a postdoctoral fellowship

Matthew Sainsbury-Dale

Postdoctoral Research Fellow, Statistics
Matthew obtained his PhD in 2024 from the University of Wollongong (UOW), Australia, with a thesis titled "Efficient Inference for Spatial and Spatio-Temporal Statistical Models Using Basis-Function and Deep-Learning Methods", which received the Examiners Commendation for Outstanding Thesis. He is now a postdoctoral researcher at the King Abdullah University of Science and Technology (KAUST), working in the XSTAT group under Prof. Raphaël Huser's supervision. Education and Early Career Matthew obtained his PhD in 2024 from the University of Wollongong (UOW), Australia. He joined KAUST as a

Daniela Cisneros

Ph.D. Student, Statistics
Daniela Cisneros was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Daniela successfully defended her PhD thesis entitled " Extreme-Value Models and Graphical Methods for Spatial Wildfire Risk Assessment" on September 11th, 2023; see her PhD thesis here. Her PhD committee was composed of Professors Raphaël Huser (chair), Jorge Mateu (external examiner from Universitat Jaume I, Castillón, Spain), Hernando Ombao, and Matteo Parsani. For her next career steps, Daniela will return to Mexico where