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Leading Statistical Innovation

The Statistics (STAT) Program at KAUST educates students to analyze and model complex real-world problems arising in modern Statistical Data Science. It boasts superb facilities and resources, including access to the latest supercomputing and visualization facilities. Combined with the state-of-the-art experimental laboratories, experimental studies at KAUST are almost unconstrained by physical resources.

Watch Stat Program on YouTube.

Faculty and Groups

Browse our faculty profiles and research groups to explore their expertise, research interests and impactful contributions that drive innovation and discovery at KAUST.

Faculty Profiles

Research Groups

Research

Research at the STAT Program pushes the boundaries of statistical theory and its application to address pressing national and global challenges in healthcare, environmental sustainability and beyond. Key research areas include:

Statistical Methodology
Health and Environmental Applications
Extreme Events and Risk Analysis

The Visiting Student Research Program (VSRP)

The KAUST VSRP is an exciting three-to-six-month research internship opportunity that provides research experience for highly qualified and motivated STEM students to work alongside leading faculty and researchers on impactful projects.

Find a research project that aligns with your study area and apply.

Learn more about VSRP

News

Building bridges between mathematical statistics and real-world impact

4 min read · Tue, Jan 6 2026

Spotlight News Research in Focus

mathematical statistics random fields stochastic partial differential equations computational statistics

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 named No. 1 in the Times Higher Education Arab University Rankings for third consecutive year

1 min read · Thu, Nov 27 2025

News Clip News Press Releases

more

Upcoming Events

KAUST CEMSE AMCS STAT Graduate Seminar Thursday, May. 14

Time Series Clustering: Pattern Recognition, Forecasting, and Amortized Inference

Ángel López Oriona, Postdoctoral Research Fellow, Statistics
May 14, 12:00 - 13:00

B9 R2325

Time Series Pattern Recognition forecasting statistical inference

KAUST CEMSE STAT Ph.D. Dissertation Defense Fernando Rodriguez Avellaneda Bayesian Spatio-Temporal Modeling for Environmental Monitoring and Epidemiology: Disaggregation and Disease Spread Dynamics

Bayesian Spatio-Temporal Modeling for Environmental Monitoring and Epidemiology: Disaggregation and Disease Spread Dynamics

Fernando Rodriguez Avellaneda, Ph.D. Student, Statistics
May 14, 14:00 - 16:00

B3 R5220

KAUST CEMSE STAT Ph.D. Dissertation Defense Xiran Zhang Scalable Methods for Multivariate Normal Probability Estimation with Applications in Confidence Region Detection, Transport Phenomena, and Parallel Computing Using RCOMPSs

Scalable Methods for Multivariate Normal Probability Estimation with Applications in Confidence Region Detection, Transport Phenomena, and Parallel Computing Using RCOMPSs

Xiran Zhang, Ph.D. Student, Statistics
May 14, 15:00 - 17:00

B2 R5209

geospatial statistics spatio-temporal statistics High Performance Computing HPC multivariate statistics GPU Algorithms

more

Join KAUST

Join world-class research on the shores of the Red Sea.

KAUST Students

Study at KAUST

Faculty Positions

KAUST ECE Researchers

Researcher Positions

Partnership Opportunities

Statistics (STAT)

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