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Study

Current Students

Current Students

Placement Test To facilitate the design of an individual study plan, all admitted students to the program without an M.S. degree must take a written assessment test upon arrival at KAUST. This test covers topics students are expected to have a solid understanding of from their undergraduate education. The following overview outlines the topics covered on the test and suggests resources for review. STAT Placement Test Overview Qualifying Exam To advance to PhD candidacy, all Ph.D. students must successfully pass a qualifying exam designed to assess their knowledge within their field of study

Prospective Students

Transform Your Potential with KAUST Statistics The KAUST Statistics (STAT) program is designed to prepare students for leading positions in industry, academia, and government. The program provides a deep understanding of analytics and modeling of complex real-world problems across various fields, including science, social science, humanities, environment, healthcare, and technology. Students benefit from superb facilities, including the latest supercomputing and visualization tools and well-equipped experimental laboratories, ensuring that resources support their research. The program's

Research

Extreme Events and Risk Analysis

Extreme events research at KAUST focuses on the study of rare, high-impact occurrences that significantly disrupt the norm, such as natural disasters, financial crises and extreme weather events. Research Focus Research in this field leverages computational and statistical methodologies to understand the underlying mechanisms of these phenomena and develop predictive models to anticipate their occurrence and mitigate their risk, involving fields like climatology, finance and engineering.

Health and Environmental Applications

The CEMSE STAT program extends its expertise in statistical methodologies to a variety of critical domains. Our interdisciplinary research efforts are aimed at advancing knowledge and addressing pressing issues. Research Focus Biostatistics: involves applying statistical methods to biological and medical research. This research area focuses on designing studies, analyzing data, and interpreting results to advance knowledge in health, medicine, and biology. Public Health and Epidemiology: focuses on studying the distribution and determinants of health and diseases in populations. It aims to

Research Areas

Developing Data-Driven Solutions for a Better World At KAUST, our Statistics program is a dynamic hub of research excellence, pushing the boundaries of statistical theory and its application to real-world challenges. Our world-renowned faculty lead diverse research groups, fostering collaboration and innovation to drive data-driven solutions in critical areas like healthcare, environmental sustainability, and beyond. Our research is defined by: Methodological Innovation: We constantly push the boundaries of statistical theory and computational techniques to extract knowledge from the most

Statistical Methodology

The CEMSE STAT program fosters a vibrant research environment dedicated to pushing the boundaries of statistical methodologies through cutting-edge research. Research Focus Computational Statistics: Focuses on using computational methods to analyze and interpret statistical data. This research area combines statistics and computer science to handle large datasets and complex models, which are crucial for fields like machine learning, bioinformatics and data mining. Bayesian Deep Learning: Merges Bayesian statistics with deep learning to enhance neural network models with uncertainty estimation

Info

About Statistics (STAT) Program

The KAUST Statistics (STAT) program plays a crucial role in tackling some of the fundamental challenges arising in modern Statistical Data Science. The interdisciplinary character of the program allows students to study and carry out research projects of global relevance and to engage in international collaborations. Nowadays, statistics crosses the borders of a vast array of disciplines offering conceptual and practical frames to design scientific investigations, to model real phenomena, predict events and quantify uncertainty out of an unprecedented amount of data made available by the
Current Students

Current Students

Placement Test To facilitate the design of an individual study plan, all admitted students to the program without an M.S. degree must take a written assessment test upon arrival at KAUST. This test covers topics students are expected to have a solid understanding of from their undergraduate education. The following overview outlines the topics covered on the test and suggests resources for review. STAT Placement Test Overview Qualifying Exam To advance to PhD candidacy, all Ph.D. students must successfully pass a qualifying exam designed to assess their knowledge within their field of study

Front Page

Statistics Program

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. Faculty and Groups Browse our faculty profiles and research groups to explore their expertise, research interests and impactful contributions that drive

Other

Al-Kindi Distinguished Statistics Lectures

The Al-Kindi Distinguished Statistics Lectures are an annual event in Statistics at King Abdullah University of Science and Technology (KAUST). A distinguished guest speaker presents a series of two lectures and remains in residence for some days. The first lecture is intended to demonstrate to a general audience the breadth of use of Statistics in applications. The second lecture is intended for a specialized audience. The lectures are named after Al-Kindi (801-873 CE), a prominent figure in the House of Wisdom, whose book entitled "Manuscript on Deciphering Cryptographic Messages" is

Al-Kindi Student Awards

‌ The annual Al-Kindi Student Awards (sponsored by the CEMSE division) celebrate the talent and achievements of the Statistics Program's students. The awards are presented in recognition of the academic accomplishments ( Al-Kindi Statistics Top Quals Student Award ) and research impact ( Al-Kindi Statistics Research Student Award ) of our leading students in the fields of Statistics. The awards are named after Al-Kindi (801-873 CE), a prominent figure in the House of Wisdom, whose book entitled "Manuscript on Deciphering Cryptographic Messages" is believed to be the earliest writing on

History

‌The Statistics (STAT) program at King Abdullah University of Science and Technology (KAUST) was established in the Fall of 2017 with Prof. Marc Genton as the Founding Chair. Preparation of the STAT Program started with the arrival at KAUST of Prof. Marc Genton in Fall 2012 and the support of Prof. Elmootazbellah Elnozahy as the new Dean at that time of the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. Statistics first developed as a track in the Applied Mathematics and Computational Science (AMCS) program and only in Fall 2017 became the 4th program of CEMSE

Visitors

2023 Spring Daniel Osorio Barreto (Assistant professor, Universidad Autónoma de Manizales , Colombia), visiting Prof. Hernando Ombao, from Jan 21- Mar 15 Aurea Cartanya Hueso ( Postdoctoral Fellow, Universitat Jaume I, Barcelona), visiting Prof. Paula Moraga, from Feb 1- Mar 1 Birgir Hrafnkelsson (Professor, University of Iceland, Iceland), visiting Prof. Raphael Huser , from Feb 5- 16 Ioannis Papastathopoulos (Lecturer, University of Edinburgh, UK), visiting Prof. Raphael Huser, from Geb 6- Mar 5 Ahamed El Machkouri (Associate professor, University of Rouen Normandy, France), visiting Prof