scientific computing

KAUST Research Conference on Mathematical and Data Sciences

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KAUST Campus

Theory and applications of data science.

Empowering Natural Intelligence with Artificial Intelligence: a Mathematician's Perspective

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B9, L2, R2322

A Dean’s Distinguished Lecture on natural intelligence, artificial intelligence and scientific machine learning.

Observer-Relative Flow Visualization and Objective Feature Extraction

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B1 L4 R4214

This dissertation develops an integrated toolkit of novel visualization and feature extraction methods, grounded in a Riemannian geometry framework, to enable an objective, observer-relative, and physically consistent analysis of complex unsteady flows.

AI and Mathematics: Efficient Machine Learning Algorithms Inspired by Dynamical Systems, Complex Analysis, and Embedding Theory

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B9 L3 R3120

This talk describes a novel machine learning algorithm, inspired by complex analysis and dynamical systems theory, that significantly improves efficiency in solving partial differential equations and scientific computing, while providing a theoretical framework for reconstructing complex, unknown systems from partial observational data.
Georgios Grekas

Georgios Grekas

Postdoctoral Research Fellow, Applied Mathematics and Computational Science
Georgios Grekas research focuses on mathematical modeling (biomechanics, solid mechanics), numerical analysis, scientific and parallel computing, and scientific machine learning.

Scalable Hierarchical Algorithms for eXtreme Computing Workshop

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KAUST

The 2012 SHAX-C workshop focuses international expert attention on the prospects for the three great hierarchical algorithms of scientific computing: multigrid, fast transforms, and fast multipole methods. These methods are kernels in simulations based on formulations of partial differential equations, integral equations, and interacting particles – in short, they are scientific and engineering workhorses.

Deep Learning and Scientific Computing

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B9 L2 R2322

In this talk, I will first give an elementary introduction to basic deep learning models and training algorithms from a scientific computing viewpoint. Using image classification as an example, I will try to give mathematical explanations of why and how some popular deep learning models such as convolutional neural network (CNN) work. Most of the talk will be assessable to an audience who have basic knowledge of calculus and matrix. Toward the end of the talk, I will touch upon some advanced topics to demonstrate the potential of new mathematical insights for helping understand and improve the efficiency of deep learning technologies.

Dominik L. Michels receives the first Procter & Gamble Faculty Award

1 min read ·
Dominik L. Michels, Computer Science and Mathematics faculty in the Computer, Electrical and Mathematical Science and Engineering Division (CEMSE) and head of the Computational Sciences Group within the Visual Computing Center (VCC), recently received the first Procter & Gamble (P&G) Faculty Award.

PhD Defense of Tariq AlTurkestani

1 min read ·
Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems PhD Dissertation Defense by Tariq Alturkestani PhD Student, Computer Science Thursday, July 9, 16:00 - 17:00, https://kaust.zoom.us/j/94054511362 Contact Person: Tariq Alturkestani The execution rate of floating-point operations has typically increased by an order of magnitude every four years during the last 30 years of modern comput ing. This exponential growth in terms of computational power has benefited from the hardware technology scaling. However, memory and storage systems have not maintained

Dominik L. Michels appointed Associate Professor of Computer Science and Applied Mathematics

1 min read ·
KAUST faculty member Dominik L. Michels has recently been promoted to associate professor of computer science and applied mathematics.

Umberto Zerbinati

Theodoros Katsaounis

Research Scientist, Applied PDE Group
Short Bio Dr. Theodoros Katsaounis is a Professor of Mathematics at the University of Crete. He received his Ph.D in 1994 for the Univ. of Tennessee USA, in applied mathematics. After his postdoctoral studies in the Ecole Normale Superieure of Paris, he joined the Dept. of Applied Mathematics of Univ. of Crete, Greece as an Assistant professor in 2003. Dr. Katsaounis was a Research Scientist at KAUST from 2015 to 2020. His research interests are in the area of applied and computational mathematics. Education Profile Ph.D Mathematics, Univ. of Tennessee, USA, 1994 M.Sc. Mathematics, Univ. of

Steven Dufour

Steven Dufour is a Former Visiting ​Associate Professor from École Polytechnique de Montréal, at Professor Raul F. Tempone's Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Steven's research activities revolve around the development of numerical methodologies for the modeling of free surface flows that can be found in various industrial applications. The main challenge associated with the numerical modeling of multifluid flows is to accurately locate the interfaces between each fluid. More complex flows, such as the flow of

Jorge Alejandro Amador Herrera

Research Interest His research interests include scientific and visual computing, numerical simulations, machine learning, and the modelling of natural phenomena. He works on physically-based simulations. Honors and Awards During his studies at UNAM, Alejandro has been awarded many times. In 2013, he received the UNAM Scholarship from the university. He was also awarded the Telmex Foundation Scholarship from 2013 to 2016, and the CONACYT Fellowship from 2017 to 2018. He graduated with summa cum laude in 2018. Alejandro has also received multiple awards from his participation in academic

Haneen Mohammed

Haneen Mohammed was a Master student in Computer Science Program under the supervision of Professor Markus Hadwiger at Visual Computing Center (VCC) at King Abdullah university of Science and Technology (KAUST). Currently, she’s preparing her doctoral in Computer Science at Columbia University in the City of New York, United States. Education and Career Haneen earned her bachelor degree in Electrical and Computer Engineering from Effat University in Jeddah in 2015. She joined KAUST and received her master degree in Computer Science in 2017. Research Interest ​Her research interests are mainly

Grigorios Kounadis

Postdoctoral Research Fellow, Applied Mathematics and Computational Science
Short Bio Grigorios Kounadis is a Postdoctoral Research Fellow at the Applied PDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. He received a bachelor degree in Mathematics from National and Kapodistrian University of Athens (NKUA), Greece, in 2006, and graduated with a Ph.D degree in Applied Mathematics from NKUA in 2020. He joined KAUST and the Applied PDE group in March 2021. Grigorios' research interests lie in the area of numerical analysis and scientific computing

George Turkiyyah

Professor Turkiyyah's expertise lies in high-performance and GPU computing, numerical simulation and optimization and their application to machine learning and large-scale modeling.

Dominik L. Michels

Associate Professor, Computer Science
Professor Michels is a leading computer scientist who proactively designs strategies to face upcoming digitization challenges. His outstanding research has been recognized by the scientific community within and beyond KAUST.

Carlos Andrés Muñoz Moncayo

Carlos Andrés Muñoz Moncayo is an M.S./Ph.d. candidate in applied mathematics and computational sciences program and a member of The Numerical Mathematics Group under the supervision of Professor David Ketcheson at King Abdullah University of Science and Technology (KAUST). Research Interests Carlos' research interests include partial differential equations, numerical analysis, and scientific computing.