About Sameh Abdulah Sameh Abdulah Senior Research Scientist, Applied Mathematics and Computational Science exageostat extreme computing parallel algorithms large-scale computing machine learning Statistical computing Dr. Sameh Abdulah specializes in HPC, scalable algorithms, and climate modeling, with innovations receiving the ACM Gordon Bell Prize for Climate Modelling. Articles Related News December 2025 KAUST researchers define the emerging field of high-performance statistical computing (HPSC) 4 min read · Sun, Dec 14 2025 News exascale GPU HPC mixed-precision computing Statistical computing KAUST researchers outline a new discipline for statistical computing at supercomputing scale. November 2024 KAUST wins the “Nobel” of high-performance computing for climate modeling 1 min read · Fri, Nov 22 2024 News Clip News HPC climate projections extreme computing computational simulations uncertainty quantification KAUST has been awarded the “Nobel" prize of high-performance computing—the ACM Gordon Bell Prize for Climate Modelling—in partnership with the NSF National Center for Atmospheric Research, U.S. and other partner institutions. July 2024 KAUST team selected as ACM Gordon Bell Prize for Climate Modelling finalists 4 min read · Tue, Jul 23 2024 News A new exascale climate emulator marks a significant advancement as the first to generate, display and evaluate hourly emulations. This breakthrough secured an interdisciplinary research team from KAUST, working alongside the NSF National Center for Atmospheric Research in the U.S. and other partner institutions, a spot as a finalist for the prestigious Gordon Bell Prize in Climate Modelling. March 2023 A little competition improves statistics 2 min read · Mon, Mar 6 2023 News A competition on spatial statistics showcases the global state of the art in analyzing vast spatial datasets. October 2022 A predictive eye on the prize 3 min read · Sun, Oct 16 2022 Awards News HPC weather forecast climate science Climate prediction models have had a mathematical makeover that has won attention from a computer science award. August 2022 A model for millions of locations 1 min read · Tue, Aug 23 2022 News climate change Environmental Statistics modeling statistics CEMSE statisticians developed a framework which enables modeling of a range of meteorological and environmental datasets from up to 2 million locations globally. July 2021 Mixing precision for model acceleration 1 min read · Mon, Jul 26 2021 News extreme computing supercomputing big data statistics A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time. February 2021 ECRC contributions to SIAM CSE21 4 min read · Sat, Feb 27 2021 News research conference HPC computational science and engineering ECRC @ SIAM CSE21! Follow us @KAUST_ECRC As in previous SIAM conferences on Parallel Processing (PP) and Computational Science and Engineering (CSE), ECRC members and their collaborators will have a strong presence at SIAM CSE21, nominally in Fort Worth, Texas, but held virtually due to the pandemic. ************************************************** SIAM CSE21 will run virtually with live sessions. ************************************************** Registration to SIAM CSE is required to gain access to the online platform and attend live sessions. Once registered, please use your personal September 2020 Turning your desktop to a Supercomputer with ExaGeoStatR 1 min read · Mon, Sep 7 2020 News Maximum Likelihood HPC Environmental Statistics Turning your desktop to a Supercomputer with ExaGeoStatR Download at https://github.com/ecrc/exageostatR. Remember the old times where you had to leave your R simulations running for the whole night on your desktop due to a large climate/weather dataset? ExaGeoStatR combines the user productivity of R with high performance computing linear algebra software libraries to deliver supercomputing-style environment right below your desk. ExaGeoStatR enables computing the maximum likelihood using large environmental datasets on R, while extracting performance from the underlying hardware resources February 2020 Pop stats for big geodata 1 min read · Mon, Feb 24 2020 News climate change statistics A universal high-performance computing interface allows popular statistical tools to run efficiently on large geospatial datasets. May 2019 Cutting datasets down to size 1 min read · Thu, May 16 2019 News applied mathematics computational science statistics environment A powerful statistical tool could significantly reduce the burden of analyzing very large datasets.
KAUST researchers define the emerging field of high-performance statistical computing (HPSC) 4 min read · Sun, Dec 14 2025 News exascale GPU HPC mixed-precision computing Statistical computing KAUST researchers outline a new discipline for statistical computing at supercomputing scale.
KAUST wins the “Nobel” of high-performance computing for climate modeling 1 min read · Fri, Nov 22 2024 News Clip News HPC climate projections extreme computing computational simulations uncertainty quantification KAUST has been awarded the “Nobel" prize of high-performance computing—the ACM Gordon Bell Prize for Climate Modelling—in partnership with the NSF National Center for Atmospheric Research, U.S. and other partner institutions.
KAUST team selected as ACM Gordon Bell Prize for Climate Modelling finalists 4 min read · Tue, Jul 23 2024 News A new exascale climate emulator marks a significant advancement as the first to generate, display and evaluate hourly emulations. This breakthrough secured an interdisciplinary research team from KAUST, working alongside the NSF National Center for Atmospheric Research in the U.S. and other partner institutions, a spot as a finalist for the prestigious Gordon Bell Prize in Climate Modelling.
A little competition improves statistics 2 min read · Mon, Mar 6 2023 News A competition on spatial statistics showcases the global state of the art in analyzing vast spatial datasets.
A predictive eye on the prize 3 min read · Sun, Oct 16 2022 Awards News HPC weather forecast climate science Climate prediction models have had a mathematical makeover that has won attention from a computer science award.
A model for millions of locations 1 min read · Tue, Aug 23 2022 News climate change Environmental Statistics modeling statistics CEMSE statisticians developed a framework which enables modeling of a range of meteorological and environmental datasets from up to 2 million locations globally.
Mixing precision for model acceleration 1 min read · Mon, Jul 26 2021 News extreme computing supercomputing big data statistics A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.
ECRC contributions to SIAM CSE21 4 min read · Sat, Feb 27 2021 News research conference HPC computational science and engineering ECRC @ SIAM CSE21! Follow us @KAUST_ECRC As in previous SIAM conferences on Parallel Processing (PP) and Computational Science and Engineering (CSE), ECRC members and their collaborators will have a strong presence at SIAM CSE21, nominally in Fort Worth, Texas, but held virtually due to the pandemic. ************************************************** SIAM CSE21 will run virtually with live sessions. ************************************************** Registration to SIAM CSE is required to gain access to the online platform and attend live sessions. Once registered, please use your personal
Turning your desktop to a Supercomputer with ExaGeoStatR 1 min read · Mon, Sep 7 2020 News Maximum Likelihood HPC Environmental Statistics Turning your desktop to a Supercomputer with ExaGeoStatR Download at https://github.com/ecrc/exageostatR. Remember the old times where you had to leave your R simulations running for the whole night on your desktop due to a large climate/weather dataset? ExaGeoStatR combines the user productivity of R with high performance computing linear algebra software libraries to deliver supercomputing-style environment right below your desk. ExaGeoStatR enables computing the maximum likelihood using large environmental datasets on R, while extracting performance from the underlying hardware resources
Pop stats for big geodata 1 min read · Mon, Feb 24 2020 News climate change statistics A universal high-performance computing interface allows popular statistical tools to run efficiently on large geospatial datasets.
Cutting datasets down to size 1 min read · Thu, May 16 2019 News applied mathematics computational science statistics environment A powerful statistical tool could significantly reduce the burden of analyzing very large datasets.
Engage ORCID ShareClipboard Related Sites Environmental Statistics (ES) Applied Mathematics and Computational Science (AMCS) Hierarchical Computations on Manycore Architectures (HiCMA) Statistics (STAT) Spatio-Temporal Statistics and Data Science (STSDS) Related Content Articles 11 Events 2 Related Links Publication list per year Also view Publications in the KAUST Repository. Sameh Abdulah personal webpage
