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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

Looking for Hands-On Research Opportunities?

The KAUST Visiting Student Research Program (VSRP) offers opportunities for undergraduate and master’s students to participate in cutting-edge research projects , work alongside our leading experts and gain valuable hands-on experience in their field.

Explore VSRP opportunities and application process

News

Professor Ying Sun elected as a Fellow of the American Statistical Association

3 min read · Tue, Apr 22 2025

News

spatio-temporal statistics Environmental Statistics computational statistics

KAUST climate research named finalist for ADIA Lab Climate Data Sciences Award

3 min read · Sun, Apr 20 2025

News

climate data stochastic computational science climate change

kaust-iit-collaboration-life-sciences-nanotechnology-research

KAUST collaboration to benefit life sciences and nanotechnology research

1 min read · Mon, Feb 3 2025

News Clip News

nanotechnology AI

more

Upcoming Events

The Signed Translation Transformed Depth: Order, Quantiles, Spread, Skewness, and Quantile Regression for Multivariate Functional Data

Emmanuel Ambriz, Postdoctoral Research Fellow, Statistics
May 15, 12:00 - 13:00

B9 L2 R2325

multivariate analysis

more

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Statistics (STAT)

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