extreme-value theory

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.

Prof. Raphaël Huser wins the Lambert Aw​ard 2015

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The Swiss Statistical Society (SSS) has established since 2013 the Johann Heinrich Lambert Award to recognize the work of young statisticians. The Lambert Award consists of a certificate and 1'000 Swiss Francs. It entitles to a plenary talk at the `Swiss Statistics Meeting'.

Dr. Sebastian Engelke (EPFL) visits extSTAT

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Sebastian is an Ambizione fellow at EPF Lausanne with Anthony Davison. Sebastian did his studies in Mathematics at University of Göttingen and UC Berkeley, and he finished his PhD as a Deutsche Telekom Foundation fellow in 2013 at the University of Göttingen with Martin Schlather. His research interests are in extreme value theory, spatial statistics, graphical models and data science.

Prof. Benjamin Shaby (Penn State University, USA) visits extSTAT

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Prof. Ben Shaby is an Assistant Professor in the Statistics Department and the Institute for CyberScience at Penn State, where he started in 2013. Before that, he was a postdoc with Cari Kaufman at UC Berkeley. Previous stop was in Durham at the Statistics and Applied Mathematical Institute (SAMSI) and Duke University. He did his Ph.D. work in Statistics at Cornell University with David Ruppert and Marty Wells. Before starting at Cornell, he spent his undergrad years at Stanford (go Cardinal!). He then spent two great years working for Chris Field at the Carnegie Institution's Department of

PhD student Sabrina Vettori selected for an ENVR Student Paper Award. Congrats!

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PhD student Sabrina Vettori has been selected to receive a Best Student Paper Award from the Section on Statistics and the Environment (ENVR) of the American Statistical Association (ASA) for her manuscript entitled "Bayesian clustering and dimension reduction in air pollutant multivariate extremes".

Yan Gong

Ph.D. Student, Statistics
Yan Gong was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Yan successfully defended her PhD thesis entitled " Flexible Multivariate, Spatial, and Causal Models for Extremes" on March 28th, 2023; see her PhD thesis here. Her PhD committee was composed of Professors Raphaël Huser (chair), Valérie Chavez-Demoulin (external examiner from HEC Lausanne at UNIL, Switzerland), David Bolin, and Mohammed-Slim Alouini. For her next career steps, Yan has accepted a short-term postdoctoral research position at

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

Matheus B. Guerrero

Ph.D. Student, Statistics
Matheus was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), doing research under the joint supervision of Prof. Raphaël Huser and Prof. Hernando Ombao. Matheus successfully defended his PhD thesis entitled " Modeling and Inference for Multivariate Time Series, with Applications to Integer-Valued Processes and Nonstationary Extreme Data" on April 4th, 2023; see his PhD thesis here. His PhD committee was composed of Professors Raphaël Huser (chair), Prof. Hernando Ombao (co-chair), Miguel de Carvalho (external examiner from the University of