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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

KAUST becomes first FIFA research institute in the Middle East and Asia

1 min read · Tue, Feb 10 2026

News Clip News Press Releases

artificial intelligence generative ai Computer Vision Sports

The right path: New dean Professor Omar Knio focuses on people, purpose, and impact

1 min read · Wed, Jan 28 2026

News Clip News

KAUST professor Peter Richtárik receives Charles Broyden Prize for second consecutive year

2 min read · Wed, Jan 21 2026

Awards News

optimization machine learning communication efficiency artificial intelligence big data algorithm

more

Upcoming Events

KAUST CEMSE STAT Ph.D. Dissertation Defense Paolo Victor Redondo Modeling Complex Dependence in Multivariate Time Series, with Applications to Brain Signals

Modeling Complex Dependence in Multivariate Time Series, with Applications to Brain Signals

Paolo Victor Redondo, Ph.D. Student, Statistics
May 5, 15:00 - 17:00

B2 R5209; Zoom Meeting 95773646717

extreme statistics Biostatistics brain signals multivariate statistics Time Series

KAUST CEMSE AMCS STAT Graduate Seminar Thursday, May. 7

Fully Decentralized Inference for Spatial Data Using Low-Rank Models

Jianwei Shi, Postdoctoral Research Fellow, Statistics
May 7, 12:00 - 13:00

B9 R2325

statistical inference decentralized systems Geospatial Data geospatial statistics optimization

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

more

Join KAUST

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

KAUST Students

Study at KAUST

Faculty Positions

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Researcher Positions

Partnership Opportunities

Statistics (STAT)

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