numerical analysis

Georgios Grekas

Georgios Grekas

PCCFD - Predictive Complex Computational Fluid Dynamics

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B9 L2 H1

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

Numerical methods for stochastic conservation laws with multiplicative rough drivers in the flux

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B1 L4 R4214

Abstract Stochastic conservation laws (SCL) with quasilinear multiplicative``rough'' path dependence in the flux arise in modeling of mean field games. An impressive collection of theoretical results has been developed for SCL in recent years by Gess, Lions, Perthame, and Souganidis. We present the first fully computable numerical methods for pathwise solutions of scalar SCL with, for instance, "rough" paths in the form of Wiener processes. Convergence rates are derived for the numerical methods and we show that for strictly convex flux functions, "rough" path oscillations lead to

An introduction to Patankar-type schemes

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B9 L3 R3229

We present order conditions for various Patankar-type schemes as well as a new stability approach that examines the non-hyperbolic fixed points of the schemes for a general linear test problem. We formulate sufficient conditions for the stability of such non-hyperbolic fixed points and the local convergence of the numerical approximation towards the correct steady-state solution of the underlying test problem. To illustrate the theoretical results, we consider several members of the modified Patankar-type family within numerical experiments.

Hierarchical ensemble-based data assimilation and rare event tracking

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B4 L5 R5220

This thesis consists of three papers considering, in general, two challenges: the minimization of computational cost in the ensemble Kalman filtering (EnKF) method and the problem of tracking a rare event within the framework of the EnKF.

Sadeed B. Sayed and Ismail E. Uysal ranked in the student paper competition at the ACES Conference

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Ph.D. students Sadeed B. Sayed and Ismail E. Uysal working in the Computational Electromagnetics Group led by Prof. Hakan Bagci ranked 3rd and 5th in the student paper competition at the 30th International Conference

KAUST Associate Professor Taous-Meriem Laleg-Kirati finalist at Leadership Excellence for Women Awards & Symposium

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Taous-Meriem Laleg-Kirati, KAUST associate professor of electrical engineering in the University's Computer, Electrical and Mathematical Science and Engineering Division, was selected as one of three finalists in the academic of distinction category at the recent Leadership Excellence for Women Awards & Symposium (LEWAS) in Bahrain.

CEMSE New Faculty: Daniele Boffi, Professor of Numerical Analysis

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Daniele Boffi is a professor of numerical analysis who recently joined the KAUST Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division.

Understanding the COVID wave

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As countries around the world work to "flatten the curve," a reference to slowing the progression of COVID-19 cases, David Ketcheson is putting mathematical modeling to work to understand how transmission is playing out.

A shock to the system

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The global, multifarious challenge posed by the COVID-19 pandemic has scientists tapping their wide-ranging fields of expertise to attack the problem on many fronts. Answering the call from KAUST President Tony Chan, and coordinated by the University's leadership team, KAUST researchers making up the Rapid Research Response Team (R3T) are turning this crisis into an opportunity to innovate.

KAUST mathematician named Fellow to European Academy of Sciences

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KAUST Distinguished Professor of Applied Mathematics and Computational Science, Dr. Peter Markowich, is named a 2020 Fellow to the European Academy of Sciences (EurASc) in recognition of his outstanding scholarship in the field of mathematical and numerical analysis of partial differential equations.

Mathematician Peter Markowich named 2022 AMS Fellow

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KAUST Distinguished Professor of Applied Mathematics and Computational Science Dr. Peter Markowich joins 45 mathematical scientists from around the world named 2022 Fellows of the American Mathematical Society (AMS) program.

Yang Liu

Education Profile B.Eng. Aerospace Engineering, Beihang University, Beijing, China, 2017. M.Sc. Applied Mathematics and Computational Science, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, 2019. Research Interests Yang's research interests include ​Probability Theory and Stochastic Processes, Numerical Analysis.

Waleed Alhaddad

Waleed Alhaddad obtained his Master's degree in Applied Mathematics and Computational Sciences from King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Raul F. Tempone at Stochastic Numerics Research Group (STOCHNUM). Research Interests Waleed's research interests include ​Mathematical Modeling, Probability Theory and Stochastic Processes, Numerical Analysis. Education Profile ​M.Sc. Applied Mathematics, Finance, King Abdullah University of Science and Technology (KAUST) 2016-2018. B.Sc. Physics, University of California Santa Barbara 2016. Awards and

Vaibhav Mehandiratta

Postdoctoral Research Fellow, Statistics
Vaibhav Mehandiratta is a Post-Doctoral fellow In the CEMSE Division, Statistics program, at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor David Bolin. Vaibhav received his PhD from the Department of Mathematics, Indian Institute of Technology Delhi in November 2022. He joined KAUST as a Post-Doctoral fellow in January 2023.

Sören Wolfers

Sören Wolfers obtained a Ph.D. degree in Applied Mathematics and Computational Sciences under the supervision of Professor Raul F. Tempone's at Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Sören's research interests included Numerical Analysis, Uncertainty Quantification, Sparse Approximation, Multilevel methods and Meshfree methods. Selected Publications Beck, J., Roberts, G., and Wolfers, S. (2018). Bayesian earthquake dating and seismic hazard assessment using chlorine-36 measurements (BED v1). Submitted to

Shuyu Sun

Shuyu Sun is a professor of Earth Science and Engineering and an affiliate professor of Applied Mathematics and Computational Science at KAUST. He specializes in computational methods for modeling subsurface flow and transport phenomena. His research focuses on advancing numerical techniques for large-scale geophysical simulations, with key applications in energy resources and environmental science.

Sadeed Bin Sayed

Sadeed Bin Sayed is a Ph.D. candidate in Electrical engineering at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Hakan Bagci. He received his B.Tech. degree in electronics and communication engineering from the National Institute of Technology Calicut, Calicut, India, in 2004, and the M.Tech. degree in communications engineering from the Indian Institute of Technology Delhi, New Delhi, India, in 2007. From July 2007 to May 2008, he worked as a Member with Technical Staff Digibee Microsystems, Bangalore, India. In May 2008, he joined as an

Raul Tempone

Professor Raul Tempone is an worlwide recognized researcher in numerical analysis and uncertainty quantification. Professor Raul Tempone at KAUST leads the stochastic numerics research group, significantly contributing to Saudi Arabia's Vision 2030 goals through advancements in computational science. His work in adaptive algorithms, Bayesian inverse problems, and scientific machine learning drives forward critical applications in technology and sustainability, embodying KAUST's commitment to global scientific leadership and economic diversification.

Najwa Alshehri

Career: Lecturer at the Royal Commission for Jubail and Yanbu. (current) PhD in Applied Mathematics and Computational Sciences. (current) Other interests: Beyond my academic and research pursuits, I am deeply committed to mentoring and empowering female students to pursue careers in science and research. At KAUST, I actively engage in initiatives that cultivate talent in mathematics, AI, and deep learning. Additionally, I place significant emphasis on developing my leadership and entrepreneurial skills through specialized programs and certifications along with other trainings in Key

Linda Alzaben

Linda Alzaben is a Ph.D. candidate in Applied Mathematics and Computational Science. Linda has a Bachelor's and a Master's degree, both in pure Mathematics, from King Abdulaziz University. In both her B.Sc. and M.Sc. she was first-class honors. Although she had been teaching for several years she decided to pursue her postgraduate studies in an engaging and interesting field at KAUST. She seized the opportunity to study and work under the supervision of Professor Daniele Boffi who is a distinguished professor in his field. Her main interest are in Finite elements and Mixed Finite elements and

Juncai He

I am currently a research scientist in Computer, Electrical and Mathematical Science and Engineering Division (CEMSE) at King Abdullah University of Science and Technology (KAUST). I received a B.S. degree in Mathematics and Applied Mathematics from Sichuan University in 2014. In the Summer of 2019, I received my Ph.D. degree in Computational Mathematics under the supervision of Prof. Jinchao Xu and Prof. Jun Hu at Peking University in Beijing, China. From 2019 to 2020, I worked as a Postdoctoral Scholar supervised by Prof. Jinchao Xu in The Center for Computational Mathematics and Application

Jongho Park

I am a research scientist in Computer, Electrical and Mathematical Science and Engineering Division (CEMSE) at King Abdullah University of Science and Technology (KAUST). I received a B.S. degree in Mathematical Sciences/Computer Science in 2013, and M.S. and Ph.D. degrees in Mathematical Sciences in 2015 and 2019, respectively (Advisor: Chang-Ock Lee), all from KAIST. From 2019 to 2020, I was a postdoctoral researcher in Department of Mathematical Sciences at KAIST (Mentor: Chang-Ock Lee). From 2020 to 2023, I was a research assistant professor in Natural Science Research Institute at KAIST

Håkon A. Hoel

Håkon Hoel was a visiting researcher in the Stochastic Numerics Group at KAUST. He holds an MSc degree in Computational Science from the University of Oslo (2016) and a Ph.D. in Numerical Analysis from KTH Royal Institute of Technology (2012). His main research interests are numerical analysis of stochastic differential equations, nonlinear filtering, and multilevel Monte Carlo (MLMC) methods. His research interests also include different aspects of implementation and error estimation of stochastic models in the following areas: adaptive weak approximation of stochastic differential equations

Gaukhar Shaimerdenova

Gaukhar Shaimerdenova is a Ph.D. candidate at Stochastic Numerics Research Group (STOCHNUM) under the supervision of Professor Raul F. Tempone at King Abdullah University of Science and Technology (KAUST). Research Interests Gaukhar's research interests include ​Stochastic Differential Equations, Numerical Analysis, Data Assimilation, Multilevel/Multi-index Monte Carlo methods, Ensemble Kalman Filtering and Computational Finance. Selected Publications Hoel, H., Shaimerdenova, G. and Tempone, R., 202 2 . Multi -index ensemble Kalman filtering. Journal of Computational Physics. Hoel, H

Erik von Schwerin

Given a mathematical model of a system with uncertainties, a computational method of approximation of that model, and a specific Quantity of Interest (QoI) of the system, how can we, with as small computational effort as possible, approximate the QoI within a user-specified accuracy? Most of Erik von Schwerin's research relates in some way or another to this question.

Evangelia Kalligiannaki

Evangelia Kalligiannaki worked as a Research Scientist at Professor Raul F. Tempone's Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Evangelia's research interests concerned the development, analysis, and implementation of model reduction (coarse-graining) techniques for high dimensional particle systems at multiple spaces and time scales, and included studying macro-molecular and stochastic lattice systems. She was particularly interested in the development of effective equilibrium and non-equilibrium coarse-grained models

David Keyes

Senior Associate to the President, King Abdullah University of Science and Technology
David Keyes works at the interface of computational science and engineering and high performance computing, which he helped edit into the DNA of KAUST as a founding Dean in 2009 and then as director of the Extreme Computing Research Center. He currently serves as Senior Associate to the President, Chair of the KAUST RDIA Economies of the Future committee, and delegate to the Saudi Center for the Fourth Industrial Revolution.

David Ketcheson

Professor Ketcheson is an expert in numerical analysis and computational science, specializing in the study of numerical methods for differential equations and the modeling and analysis of time-dependent nonlinear wave phenomena.

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.