spatial statistics

Spatial Self-Confounding: Smoothness-related estimation bias in spatial regression models

1 min read ·
Spatial regression models are widely used to capture the relationship between observations and covariates, employing Gaussian random fields to account for spatial variability not explained by the covariates. A new study by researchers David Bolin and Jonas Wallin addresses a critical yet often overlooked problem in these models: smoothness-related spatial self-confounding. The work examines how misspecified covariates, particularly when there are differences in smoothness between variables, can lead to severe and counter-intuitive biases in the estimation of regression parameters. These

excursions

excursions: A Framework for Probabilistic Excursion Sets and Contour Inference

rSPDE

rSPDE: A Computational Framework for Rational Approximations of Fractional Stochastic Partial Differential Equations
KAUST-CEMSE-STAT-STSDS-Sihan-Chen

On Computation and Robustness Issues in Spatial Statistics

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B2, L5, R5220

This thesis develops and evaluates robust statistical methods for the analysis and modeling of spatial data, with a focus on improving inference reliability in the presence of outliers and computational challenges.

MetricGraph

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

Mastering Network Spatial Statistics with the MetricGraph R Package

1 min read ·
A new open-access mini-course is expanding access to advanced network spatial statistics through practical training with the MetricGraph package R, a powerful tool developed by David Bolin (KAUST), Alexandre B. Simas (KAUST), and Jonas Wallin (Lund University) for modeling data on network structures such as road systems and river basins. Presented by Bolin and Simas at the University of Glasgow during the “ INLA: Past, Present, and Future” workshop, the mini-course provides step-by-step tutorials, real datasets, and comprehensive R code, all freely available online, opening new avenues for

Mapping risk on networks: A scalable model for spatial point processes earns international recognition

2 min read ·
KAUST Ph.D. student Damilya Saduakhas wins Best Paper Award for a new model mapping accident risk on complex road networks.

Damilya Saduakhas wins Best Paper Award at Spatial Statistics 2025 in The Netherlands

1 min read ·
Damilya Saduakhas, a KAUST Ph.D. candidate in statistics, has received the Best Paper Award at the Spatial Statistics 2025: At the Dawn of AI Conference, held from July 15 to 18 in Noordwijk, The Netherlands.

Kriging Asymptotics

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B1 L4 R4102

Spatial analyses often focus on spatial smoothing using the geostatistical technique known as kriging. Theoretical results regarding large sample convergence rates of kriging predictors remain elusive. By casting kriging as a variational problem, we develop an equivalent kernel approximation technique that can also lead to computational feasibility for large data problems.

A Distributed Implementation of the Multi-resolution Approximation for Very Large Spatial Data

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B1 L4 R4102

With data of rapidly increasing sizes in the environmental and geosciences such as satellite observations and high-resolution climate model runs, the spatial statistics community has recently focused on methods that are applicable to very large data. One such state-of-the-art method is the multi-resolution approximation (MRA), which was specifically developed with high performance computer architecture in mind.

Workshop on Statistical Process Monitoring and Risk Assessment for Engineering and Spatial Environmental Applications

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B1 L4 R4102

LIST OF SPEAKERS KAUST Environmental Statistics Group, CEMSE Division - Ying Sun (ying.sun@kaust.edu.sa), PI - Fouzi Harrou (fouzi.harrou@kaust.edu.sa), Postdoc - Huang Huang (huang.huang@kaust.edu.sa), PhD Student - Tianbo Chen (tianbo.chen@kaust.edu.sa), PhD Student - Rui Meng (rui.meng@kaust.edu.sa), Master Student - Sulaiman Binkhamis (sulaiman.binkhamis@kaust.edu.sa), Master Student Hydrology and Land Observation Group, BESE Division - Gaohong Yin (gaohong.yin@kaust.edu.sa), Master Student Collaborators - NorEddine Ghaffour (noreddine.ghaffour@kaust.edu.sa), co-I, WDRC - Matthew McCabe

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!

1 min read ·
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

1 min read ·
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

1 min read ·
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.

CEMSE New Faculty: David Bolin, Associate Professor of Mathematical Statistics

1 min read ·
David Bolin is an associate professor of mathematical statistics who joined the KAUST Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division earlier this month from the Department of Mathematical Sciences at the University of Gothenburg. Before joining KAUST, Bolin received both his Ph.D. degree in mathematical statistics and M.S.c in engineering mathematics from Lund University, Sweden, in 2012 and 2007, respectively. Upon completing his Ph.D., he spent one year at Umeå University, Sweden, working as a postdoctoral fellow before moving to the Chalmers University of Technology. In 2016, Bolin became an associate professor of mathematics at the University of Gothenburg, where a year later he received the title of Docent in mathematical statistics.

CEMSE Division student spotlight: Gaurav Agarwal

1 min read ·
Gaurav Agarwal firmly believes in the age-old adage that patience is a virtue. Without patience, life’s challenges cannot be overcome, and a steadfast belief in perseverance has served the statistics Ph.D. student well throughout his academic career.

New paper accepted in The American Statistician

1 min read ·
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

Yan Song

Postdoctoral Research Fellow, Statistics

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.

Kelvin J. R. Almeida-Sousa

Postdoctoral Research Fellow, Statistics
Kelvin J. R. Almeida-Sousa is a Brazilian mathematician with contributions to deterministic and stochastic partial differential equations, numerical analysis, mathematical statistics, and spectral theory.

Joydeep Chowdhury

Postdoctoral Research Fellow, Statistics
Joydeep Chowdhury is a postdoctoral fellow in the Spatio-Temporal Statistics & Data Science research group of Professor Marc G. Genton. His current research activities focus on problems in multivariate statistics, spatial statistics and functional data analysis.

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

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

Haavard Rue

Program Chair, Statistics
Professor Haavard Rue is an internationally recognized expert in Bayesian computational statistics.

Gaurav Agarwal

Ph.D., Statistics
Gaurav Agarwal obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Ying Sun in the Environmental Statistics group. His research focused on developing statistical models for dealing with the issues concerning the environment. Bringing data to life, with statistics and programming excites him. Besides research, he likes to dance and work out. Research Interest Gaurav's research interests included Multivariate quantiles, Non-parametric statistics, Functional data analysis, and Spatial Statistics. Awards and

David Keyes

David Keyes works at the interface of computational science and engineering and high performance computing, which he helped edit into the DNA of KAUST as a founding Dean in 2009 and then as director of the Extreme Computing Research Center. He currently serves as Senior Associate to the President, Chair of the KAUST RDIA Economies of the Future committee, and delegate to the Saudi Center for the Fourth Industrial Revolution.

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

Alexandre de Bustamante Simas

Senior Research Scientist, Statistics
Alexandre Simas is an expert on stochastic processes and spatial statistics, with a focus on stochastic partial differential equations and random fields on metric graphs.