spatial statistics

The strength of multidisciplinary research: the joint example of statistics and geoscience

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B1 L4 R4102

Different scientific branches have the potential to develop topics which would provide visibility and fame. However, comparable if not greater milestones can be achieved when researchers from totally different fields join their efforts. This seminar will summarize the scientific journey of a former member of KAUST, which spent three years here as a postdoc in statistics coming from a pure geological background, combining the best out of the two worlds. Examples of the latest researches will be provided in the context of space, time and space-time statistics, bridging it with the underlying geoscientific research questions.

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.

Flexible Extremal Dependence Models for Multivariate and Spatial Extremes

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B5 L5 R5220

This dissertation consists of four major contributions to subasymptotic modeling of multivariate and spatial extremes. The dissertation proposes a multivariate skew-elliptical link model for correlated highly-imbalanced (extreme) binary responses, and shows that the regression coefficients have a closed-form unified skew-elliptical posterior with an elliptical prior.

A talk with PhD student Sabrina Vettori: Catastrophic events are forecastable, after all!

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Environmental disasters occur daily and hit almost every country around the world, taking a heavy toll on lives and economies. According to the United Nations Office for Disaster Risk Reduction, every year there are around 350 reported disasters causing more than 20,000 deaths and affecting the life of almost 100 million people with an overall economic damage of 66.5 billion US$. But this can change.

Best 2016 Paper in the Journal of Agricultural, Biological and Environmental Statistics

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Professor Huser will present the work in a special invited session (JABES showcase) at the International Biometric Conference taking place in Barcelona, Spain, in July 2018.

Students shine on the statistics stage

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KAUST Ph.D. alumna Sabrina Vettori and Ph.D. student Yuxiao Li have been selected by the Eastern North American Region (ENAR) of the International Biometric Society to receive a Distinguished Student Paper Award at the 2018 ENAR Spring Meeting.

New paper accepted in The American Statistician

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New paper accepted: Sainsbury-Dale, M., Zammit-Mangion, A., and Huser, R. (2023+), Likelihood-free parameter estimation with neural Bayes estimators, The American Statistician, to appear [ PDF preprint].

Zhuldyzay Baki

M.S. Student, Statistics
Zhuldyzay Baki obtained her MSc. in Statistics at the King Abdullah University of Science and Technology in December 2018. After her time at KAUST, she got a job as a Risk Insurance Associate at PwC, Kazakhstan. Areas of expertise and current scientific interests Zhuldyzay Baki's research interests focus on statistics of extremes with applications to environmental data.

Zhongwei Zhang

Ph.D. Student, Statistics
Zhongwei Zhang was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Zhongwei successfully defended his PhD thesis entitled " Flexible Extremal Dependence Models for Multivariate and Spatial Extremes" on October 25th, 2022; see his PhD thesis here. His PhD committee was composed of Professors Raphaël Huser (chair), Jonathan Tawn (external examiner from Lancaster University, UK), David Bolin, and Ajay Jasra. For his next career steps, Zhongwei has accepted a postdoctoral position at the University of

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

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

Noura Alotaibi

Ph.D. Student, Statistics
Noura Alotaibi is a Ph.D. candidate in the Extreme Statistics Research Group (XSTAT) under the supervision of Professor Raphaël Huser. Before joining KAUST, Noura obtained an MSc. degree in statistics from Ohio University, United States. Research interests Noura Alotaibi's research interests focus on Statistics of extremes and applications.

Jordan Richards

Postdoctoral Research Fellow, Statistics
Dr. Jordan Richards was a postdoctoral fellow in the Extreme Statistics Research Group of Prof. Raphaël Huser from October 2021 to January 2024, developing machine learning approaches for spatial extremes with environmental applications. After his postdoc at KAUST, Jordan moved to the University of Edinburgh, UK, where he embraced an academic career by becoming a Lecturer (equivalent to Assistant Professor) in Statistics. See his personal website here. Education and early career Jordan Richards received his Ph.D. from Lancaster University under the supervision of Jonathan A. Tawn, Jennifer L

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

Arnab Hazra

Postdoctoral Research Fellow, Statistics
Dr. Arnab Hazra was a postdoctoral fellow in the Extreme Statistics Research Group of Prof. Raphaël Huser from February 2019 until December 2021, doing research on spatial extremes with environmental applications and bayesian statistics. After his postdoc at KAUST, Arnab moved to the Indian Institute of Technology (IIT), Kanpur, India, where he embraced an academic career by becoming an Assistant Professor of Statistics. See his personal website here. Education and early career Arnab Hazra received his Ph.D. in Statistics from North Carolina State University, United States. His Ph.D. advisors