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.
A prediction model that considers multiple landslides over time in a given region may improve the accuracy of early warning systems.
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].
Let’s discover the world of the statisticians at KAUST and be ready to be amazed by their cutting-edge research!
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]
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: 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].
Throughout the world, organic waste generation is posing serious challenges, threatening food security and water purity and availability. Saudi Arabia is no exception.
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.
Prof. Raphaël Huser has been appointed to serve as an Associated Editor for the Journal of the Korean Statistical Society (JKSS) starting on January 1, 2020.
Areas without earthquake monitoring systems could model the tremors by using data from local landslides.