statistics

The KAUST 2022 Workshop on Statistics

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B2 B3 A0215

The workshop will cover current trends in statistics and the statistical modeling of big and complex data. Over four days, it will have talks by leading experts as well as two poster sessions where students and postdocs will present their work. All talks will be given Auditorium 0215, between Buildings 2 and 3 at KAUST. Speakers Aritz Adin (Public University of Navarre) Ahmadou Alioum (Bordeaux School of Public Health) Denis Allard (INRAE) Vera Baladandayupathani (University of Michigan) Emily Hector (North Carolina State University) Eduardo Garcia Portugues (Carlos III University of Madrid)

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

Postdoc Luigi Lombardo gets an Outstanding Student Poster and PICO EGU Award. Congratulations Luigi!

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The 2016 Outstanding Student Poster and PICO (OSPP) Award is awarded to Luigi Lombardo for the poster/PICO entitled Landslide triggering-thickness susceptibility, a simple proxy for landslide hazard? A test in the Mili catchment (North-Eastern Sicily, Italy). Regarding his work, Luigi said: " In the PICO presentation project we modeled the thickness at the crown of each landslide as the dependent variable. As a result, the predictive maps carried more information than classic susceptibility ones, enabling a better proxy to hazard prediction." You can find Luigi's poster here.

Getting a handle on extremes

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By tapping into the power of extreme value theory, an international team of researchers including Raphaël Huser from the University's Computer, Electrical and Mathematical Science and Engineering Division has developed a statistical model that overcomes the shortcomings of previous schemes to provide a reliable basis for climate research and the prediction of drought and flood. The model can accurately describe observed rainfall data and reliably predict the likelihood of future extreme events. The analysis of hourly or daily rainfall data presents many challenges for researchers and

2016 Workshop Statistics for High-Dimensional & Complex Data

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Workshop on Statistics for High-Dimensional and Complex Data, Nov. 6-9, 2016​ 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. David Bolin, Chalmers University of Technology, Sweden Prof. Probal Chaudhuri, Indian Statistical Institute, India Prof. Dan Cooley, Colorado State University, USA​ Prof. Subhajit Dutta, IIT Kanpur, India Prof. Amanda Hering, Baylor University, USA Dr. Anna Kiriliouk, Université

Letting the data speak for itself

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A new statistical approach for environmental measurements lets the data determine how to model extreme events.

2017 Workshop Modern Statistics for Complex Data Structures

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2017 Workshop Modern Statistics for Complex Data Structures

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.

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

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PhD student Sabrina Vettori has been selected by the International Biometric Society Eastern North American Region (ENAR) to receive a Distinguished Student Paper Award at the 2018 ENAR Spring Meeting in Atlanta ( https://www.enar.org/meetings/spring2018/index.cfm ) for her manuscript entitled " Bayesian Hierarchical Modelling of Air Pollution Extremes Using Multivariate Max-Stable Processes ". She will present her work at an oral contributed paper session, be invited to attend the ENAR President’s reception and publicly receive their award at the beginning of the ENAR President’s Invited

Challenging statistics of weather extremes

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More accurate statistical modeling of extreme weather will improve forecasting and disaster mitigation.

Point patterns help to predict landslides

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Rainfall simulations in statistical models could allow accurate prediction of dangerous landslides.

How extreme weather exacerbates air pollution

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Simultaneously modeling of air pollutants and weather under extreme conditions highlights the potential for serious health risks.

2018 Workshop on Statistics and Data Science

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The Statistics Program at KAUST is proud to host the 2018 Workshop on Statistics and Data Science. This workshop gathers the leading experts on statistical data science to discuss the current needs, challenges and opportunities of modeling massive and high dimensional data, predicting complex biological and physical processes. The workshop will run from November 12-14. Talks and posters presentations will take place in Auditorium 0215 (between Buildings 4 & 5). Details on the workshop (speakers, abstracts and schedule) can be found here.

Prof. Raphaël Huser appointed to serve as AE for JABES

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Prof. Raphaël Huser has been appointed to serve as an Associate Editor for the Springer Journal of Agricultural, Biological and Environmental Statistics ( JABES, 2017 Impact Factor: 1.072) starting from January 2019 . JABES publishes papers that introduce new statistical methods to solve practical problems in the agricultural sciences, the biological sciences, and the environmental sciences.

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.

Students Peng Zhong and Rustam Bekishev get their MS degree

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On December 14, 2018, KAUST welcomed 243 graduates at the University’s ninth Commencement ceremony. Among them, students Rustam Bekishev and Peng Zhong, who is now a Ph.D. student In Statistics in our group, got their MS degree. Congratulations!

Prof. Birgir Hrafnkelsson visits the extSTAT group

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Professor Birgir Hrafnkelsson from the Department of Mathematics at the University of Iceland, will visit extSTAT during February 24-March 2, 2019. His research interests include Bayesian hierarchical modeling, spatial statistics, spatio-temporal modeling, extreme value analysis and statistical modeling of environmental data.

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

Prof. Raphaël Huser now serving as AE of Econometrics and Statistics

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Prof. Raphaël Huser has been appointed to serve as an Associate Editor for the Econometrics and Statistics ( EcoSta) part B (Statistics) starting from May 2019.

3 Faculty Positions in Statistics 2020 at KAUST

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The 3 faculty positions are in the Statistics Program (http://stat.kaust.edu.sa) within the Computer, Electrical, and Mathematical Sciences and Engineering Division. Currently, the Statistics Program has 7 core faculty and 10 affiliated faculty. We are primarily interested in applicants with strong background in one of the following areas: (1) Statistical Data Science and AI, including network data analysis and high-dimensional statistics (https://apply.interfolio.com/69165); (2) Statistical Climatology, with expertise in statistical analysis of climate model output data, in particular regional climate models, and in physical systems (https://apply.interfolio.com/69167); (3) Statistics for Public Health, including smart health data analysis, personalized medicine, and disease mapping (https://apply.interfolio.com/69168).

Shaking up the landslide model

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Areas without earthquake monitoring systems could model the tremors by using data from local landslides.

A second wind for turbine design

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Better prediction of extreme winds at sparsely observed locations could help optimize the design of wind farms.

Prof. Raphaël Huser now serving as AE for the journal Environmetrics

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Prof. Raphaël Huser has been appointed to serve as an Associate Editor for Environmetrics, the Journal of The International Environmetrics Society ( TIES​), starting on March 16, 2020.

New paper accepted in Bayesian Analysis

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New paper accepted: Hrafnkelsson, B., Siegert, S., Huser, R., Bakka, H., and Jóhannesson, Á. V. (2020+), Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models, Bayesian Analysis, to appear [ arXiv].

A sharper view of flood risk

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Extreme weather patterns and regions at risk of flooding could be easier to spot using a new statistical model for large spatial datasets.

New paper accepted in Earth Science Reviews (ESR)

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New paper accepted: Lombardo*, L., Opitz, T., Ardizzone, F., Guzzetti, F., and Huser, R. (2020+), Space-time landslide predictive modelling, Earth Science Reviews, to appear [PDF preprint]

Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model

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New paper accepted: Hazra, A., and Huser, R. (2020+), Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model, Annals of Applied Statistics [ PDF preprint].

New paper accepted in Wiley Interdisciplinary Reviews (WIREs): Computational Statistics.

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New paper accepted: Huser, R. , and Wadsworth, J. L. (2020+), Advances in statistical modeling of spatial extremes , Wiley Interdisciplinary Reviews (WIREs): Computational Statistics, to appear [ PDF preprint ].

Today we celebrate World Statistics Day!

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Let’s discover the world of the statisticians at KAUST and be ready to be amazed by their cutting-edge research!

Modeling the neighborhood boosts landslide prediction

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A prediction model that considers multiple landslides over time in a given region may improve the accuracy of early warning systems.

Predicting future hotspots in the Red Sea

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Predicting areas of the Red Sea most susceptible to overheating by the end of the century could help conservation efforts to protect its precious coral reefs.

Heatwave model shows it is hotter in more places, more often

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New modeling shows that heatwaves across Europe have increased in both frequency and spatial extent over the past century.

Decrypting the interdependence of cryptocurrencies

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A team of KAUST statisticians has analyzed the price movements of the top five cryptocurrencies to further understand their market behavior. Their model will help investors assess the risks of investing in cryptocurrencies.

New book chapter accepted

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New book chapter accepted: Hazra, A., Huser, R. , and Jóhannesson, Á. V. (2021+), Bayesian l atent Gaussian models for high-dimensional spatial extremes , In Statistical Modeling Using Bayesian Latent Gaussian Models – With Applications in Geophysics and Environmental Sciences, editor B. Hrafnkelsson, Springer, to appear [ arXiv ][ PDF preprint ].

New paper accepted

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New paper accepted: Zhong, P., Huser, R., and Opitz, T. (2022+), Exact simulation of max-infinitely divisible processes, Econometrics and Statistics [ arXiv][ PDF preprint ].

Getting the tail straight

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KAUST’s Extreme Statistics Group has developed an improved statistical model for analyzing environmental data of extreme events, such as heavy rainfall or strong wind data.

Extreme analysis of seizures

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CEMSE researchers Matheus Guerrero, Raphaël Huser and Hernando Ombao developed a new approach for analyzing seizures in epilepsy patients by applying extreme value theory to real EEG seizure data.