Events

Apr 14 - Apr 21, 2019

Part 1: Variational structures and Fourier approximation techniques for mean-field game systems

Dr. Levon Nurbekyan, Visiting Scholar, Université de Montréal

Apr 17, 14:00 - 16:00

B1 L3 R3119

Université de Montréal mean-field games Partial Differential Equations

Mean-field game (MFG) systems of partial differential equations (PDE) arise in modeling huge populations of indistinguishable rational agents that play non-cooperative differential games. Mathematically, an MFG system comprises of a Hamilton-Jacobi-Bellman PDE coupled with a Kolmogorov-Fokker-Planck PDE in a highly nonlinear fashion. Hence, theoretical and numerical treatments of MFG systems are highly challenging problems. Day 1: I will show how to transform suitable mean-field game (MFG) systems into infinite-dimensional convex optimization problems. Furthermore, I will present Uzawa’s algorithm and augmented Lagrangian approach for solving convex optimization problems. Finally, I will demonstrate how to apply these methods to approximate solutions of corresponding MFG systems.
On Strong Stability of Runge-Kutta Methods

Dr. Hendrik Ranocha, Technische Universitat Braunschweig

Apr 16, 14:00 - 15:00

B1 L4 R4214

TU Braunschweig pdes and odes Hyperbolic PDEs

Runge-Kutta methods are classical and widespread techniques in the numerical solution of ordinary differential equations (ODEs). Considering partial differential equations, spatial semidiscretisations can be used to obtain systems of ODEs that are solved subsequently, resulting in fully discrete schemes. However, certain stability investigations of high-order methods for hyperbolic conservation laws are often conducted only for the semidiscrete versions.

Apr 7 - Apr 14, 2019

Mar 31 - Apr 14, 2019

Mini Course Part 2-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

Prof. Jan Giesselmann, Technical University of Darmstadt, Germany

Apr 7, 16:00 - 17:00

B1 L3 R3119

Multi-face flows numerical methods

In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation

Mar 31 - Apr 7, 2019

Mar 17 - Mar 31, 2019

CEMSE Tutorial in Quantum Computing

Andrea Morello, Scientia Professor of Electrical Engineering and Telecommunications, UNSW Sydney

Mar 24, 09:00 - 17:00

B19 L3 H1

quantum computing Quantum Measurements

With the end of the Moore’s law, it became imperative to find new principles for computing that can avoid the current physical limitations. Among the promising approaches is Quantum Computing which has resulted in substantial national investments in research and development in this area by many nations. This first tutorial is designed to target scientists, engineers and mathematicians who are interested in this rapidly growing field but have not yet invested enough time in learning about it.

Mar 17 - Mar 24, 2019

Mar 10 - Mar 17, 2019

Nov 11 - Nov 18, 2018

2018 Workshop on Statistics and Data Science

Nov 12, 08:30 - Nov 15, 17:00

Auditorium 0215 between Buildings 4 & 5

data science high dimensional statistics modeling biological processes physical processes

The Statistics Program at KAUST is proud to host the 2018 Workshop on Statistics and Data Science. This workshop gathers the leading experts on statistical data science to discuss the current needs, challenges and opportunities of modeling massive and high dimensional data, predicting complex biological and physical processes. The workshop will run from November 12-14. Talks and posters presentations will take place in Auditorium 0215 (between Buildings 4 & 5). View Workshop's Agenda.

Nov 4 - Nov 11, 2018

Spatio-Temporal Data Analysis by Transformed Gaussian Processes

Yuan Yan, PhD Student of Prof. Marc Genton, KAUST

Nov 5, 17:15 - 18:15

B2 L5 R5220

spatio-temporal data analysis statistics

In the analysis of spatio-temporal data, statistical inference based on the assumption that the data follow a Gaussian distribution is ubiquitous due to its many attractive properties. However, data collected from different fields of science, such as meteorology, astronomy, biology and medicine, rarely meet the assumption of Gaussianity. One option is to apply a monotonic transformation to the data such that the transformed data have a distribution that is close to Gaussian. In this thesis, we focus on a flexible two-parameter family of transformations, the Tukey g-and-h (TGH) transformation

Oct 14 - Oct 21, 2018

Solution structure and high order numerical methods for time-dependent problems

Dr. Hailiang Liu, Professor of Mathematics, Iowa State University (ISU)

Oct 15, 16:00 - 17:00

B1 L3 R3422

The course discusses the solution structure and high order structure-preserving numerical methods for several time-dependent problems, modeled by partial differential equations balanced with diffusion, convection, and various interactions. The main topic focuses on the model structure and the construction of stable, accurate approximate algorithms for these problems, and the interplay between analytical theory and computational aspects of such algorithms with real applications. Here is a list of topics to be discussed: (1) Optimization, entropy and differential equations (2) Critical threshold

Mar 18 - Mar 25, 2018

Computational and Statistical Interface to Big Data

Xin Gao, Program Chair, Computer Science

Mar 19, 08:00 - Mar 21, 17:00

B9 L2 H2

We are now in the fourth paradigm of science: Data Science. The massive amount of structured and unstructured data has posed new challenges and opportunities to the fields of computer science and statistics. Traditional computational and statistical methods for data storage, curation, sharing, querying, updating, visualization, analysis, and privacy have been shown to fail in the big data scenario due to the unprecedented volume, velocity, variety, veracity and value of the big data. This conference will bring together a number of prominent researchers in Computer Science and Statistics with common interests and active research in big data, as well as the researchers at KAUST who regularly generate or face big data, such as those in bioscience and red sea research.

Feb 11 - Feb 25, 2018

Fifth KAUST-NVIDIA Workshop on Accelerating Scientific Applications Using GPUs

Timothy Lanfear , Brent Leback

Feb 18, 08:00 - Feb 20, 17:00

B4 B5 A0215

supercomputing

The KAUST Supercomputing Laboratory is co-organizing with NVIDIA, a leader in accelerated computing and artificial intelligence, a full-day workshop on accelerating scientific applications using GPUs on Tuesday, February 20th, 2018 in the auditorium between buildings 4 and 5.

Dec 3 - Dec 10, 2017

Big Data Analyses in Evolutionary Biology

Dec 4, 08:00 - Dec 6, 17:00

B9 H2

big data Big data analysis evolutionary biology

This event is organized by CBRC with financial support from the KAUST Office of Sponsored Research

May 21 - May 28, 2017

PCCFD - Predictive Complex Computational Fluid Dynamics

David Keyes, Senior Associate to the President, King Abdullah University of Science and Technology

May 22, 08:45 - May 24, 05:00

B9 L2 H1

CFD algorithms applied mathematics numerical analysis Computer science

The PCCFD workshop will focus on cutting-edge research in the field of algorithmic development for CFD and multi-scale complex flow simulations.

May 15 - May 29, 2016

Welcome at Kaust UQ School On Numerical Methods For Direct And Inverse Problems 2016 22-28 May

Raul Tempone, Professor, Applied Mathematics and Computational Sciences

May 22, 12:00 - May 28, 12:00

B9 H1 R2322

numerical methods stochastic differential equations statistics

KAUST UQ SCHOOL 2016 is an annual base thematic conference at King Abdullah University of Science and Technology held by Raul Tempone, Professor of Applied Mathematics and Computational Sciences at CEMSE (Computer, Electrical and Mathematical Sciences & Engineering Division). Tempone’s interests in the mathematical foundation of computational science and engineering are reflected in this summer school. The school’s goal is to provide participants with an overview on the most recent research progress in the field of uncertainty quantification, with emphasis to • Multi-Level and Multi-Index

Mar 3 - Mar 10, 2013

Parametric Problems, Stochastic, and Identification By Prof. Hermann Matthies (ISCTUB, Germany)

Prof. Hermann Matthies, Institute of Scientific Computing TU Braunschweig, Geramany

Mar 6, 15:00 - 16:00

B1 R4102

Parameter identification problems are formulated in a probabilistic language, where the randomness reflects the uncertainty about the knowledge of the true values. This setting allows conceptually easily incorporating new information, e. g. through a measurement, by connecting it to Bayes's theorem. The unknown quantity is modelled as a (may be high-dimensional) random variable. Such a description has two constituents, the measurable function and the measure.

Apr 22 - Apr 29, 2012

Scalable Hierarchical Algorithms for eXtreme Computing Workshop

David Keyes, Senior Associate to the President, King Abdullah University of Science and Technology

Apr 28, 08:00 - Apr 30, 16:00

KAUST

scientific computing

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.