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<> machine learning (11)

Hayssam Dahrouj

Senior Research Scientist at KAUST (King Abdullah University of Science and Technology)

Karen Sanchez

Postdoctoral Research Fellow
Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Hani A. Al Majed

M.S. Student
Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science
Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Saleh AlJazzar

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Muhammad Esmat

Visiting student at, King Abdullah University of Science and Technology (KAUST).

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahsan Mehmood

Intern (former), Information Science Lab
Visiting student at King Abdullah University of Science and Technology (KAUST).

Abdulkarem Badiea Alshaibani

Visiting Student at the Information Science Lab at the King Abdullah University of Science and Technology (KAUST).

Prof. Hailiang Liu visits our group

1 min read ·
Prof. Hailiang Liu from Iowa State University will be visiting our group during May.
<> Deep learning (7) <> Applied Partial Differential Equations (5)

Katerina Nik

Professor Nik studies partial differential equations that describe phenomena in biological growth processes, fluid dynamics, and mechanical engineering.

On Nonlocal Keller-Segel Type Equations

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B1 L3 R3119

In the first part of the talk we investigate a Keller-Segel model with quorum sensing and a fractional diffusion operator. This model describes the collective cell movement due to chemical sensing with flux limitation for high cell densities and with anomalous media represented by a nonlinear, degenerate fractional diffusion operator. The purpose here is to introduce and prove the existence of a properly defined entropy solution. In the second part of the talk we will analyze an equation that is gradient flow of a functional related to Hardy-Littlewood-Sobolev inequality in whole Euclidean space of higher dimensions.

Professor Athanasios Tzavaras elected Fellow of the European Academy of Sciences (EurASc)

1 min read ·
Athanasios (Thanos) Tzavaras has been elected Fellow of the European Academy of Sciences (EurASc). He was nominated for his contributions to the interface of nonlinear partial differential equations and applied mathematics in the physical sciences.

Min-Gi Lee

Postdoctoral Research Fellow, Applied PDE Group
Dr. Min-Gi Lee was a Postdoctoral Research Fellow at the Applied PDE group of the Applied Mathematics and Computational Science program (AMCS) at KAUST during the period September 2014 - December 2017. He is currently Assistant Professor in the Department of Mathematics, Kyungpook National University, South Korea. Education Profile ​​Ph.D. in Mathematics, KAIST, Korea, 2014 M.Sc. in Mathematics, KAIST, Korea, 2009 B.Sc. in Mathematics, KAIST, Korea, 2007

Daria Bolbot

Short Bio Ms. Daria Bolbot is a Ph.D student in the AppliedPDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. She graduated from Moscow Institute of Physics and Technology in 2013 with the Master degree in Applied Mathematics and Applied Physics. Ms. Daria got a Bachelor degree from the same institute (MIPT) 2 years earlier - 2011. Her research interests are Nonlinear Partial Differential Equations, Hyperbolic Conservation Laws, Dispersive-Diffusive Shock Waves and Dynamical
<> artificial intelligence (5)

Najmeddine Dhieb

Yasmeen Alsaedy

M.S. Student, Computer Science
She is an AI researcher specializing in generative AI and deep learning. With a strong academic foundation and hands-on experience in machine learning, data science and artificial intelligence, she is passionate about advancing AI applications in real-world scenarios. She has contributed to cutting-edge projects, published research, and collaborated on innovative solutions that bridge the gap between AI theory and practice. Her expertise includes designing and implementing advanced data models, AI-driven visual/text computing, and deep learning architectures.

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Ahmed Youssef Ragab Radwan

Visiting Student (former), Information Science Lab
Visiting student at the Information Science Lab, in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST)
<> Partial Differential Equations (5)

On the collapse mechanism of Wave Maps

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B1 L4 R4214

The Wave Map system describes the evolution of waves constrained on a (Riemannian) manifold. For the 2 + 1 dimensional problem, when the target manifold is a sphere, the solution collapses in finite time. The Analysis is due to the pioneering work of Merle, Paphael and Rodnianski. Motivated by their work I will present a somewhat novel approach of the collapsing mechanism which is based on a view of the equations as a nonlinear gauge system. This is joint work with Dan Geba.

Meet KAUST prospective student: Stefanos Georgiadis

1 min read ·
Stefanos Georgiadis is an applied mathematics graduate who will join KAUST from the School of Applied Mathematical and Physical Sciences, Athens, Greece. Stefanos will join KAUST this fall as a Ph.D. candidate and member of the Applied Partial Differential Equations (AppliedPDE) research group under the supervision of Professor Athanasios Tzavaras.

Stefanos Georgiadis

Stefanos Georgiadis is a Ph.D. candidate in a co-tutelle between KAUST and TU Wien, under the supervision of Professor Athanasios Tzavaras and Ansgar Jüngel. Before joining KAUST, Stefanos obtained his bachelor and master's degree in applied mathematics from the School of Applied Mathematical and Physical Sciences of the National Technical University of Athens in Greece. Research Interests Stefanos' research interests include the analysis of nonlinear partial differential equations as they apply to the modeling of multicomponent systems of gases.

Nuno J. Alves

Short Bio Mr. Nuno Alves is a Ph.D student in the AppliedPDE 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 has got bachelor and master's degrees from Instituto Superior Tecnico, University of Lisbon, Portugal. Mr. Nuno had been a visiting student at KAUST from March 2014 to July 2014. Moreover, during the academic year 2017/2018 he was working as an invited teaching assistant at Polytechnic Institute of Beja, Portugal. His work is essentially related with non-linear partial

Athanasios Tzavaras

KAUST Professor of Applied Mathematics and Computational Science Athanasios (Thanos) Tzavaras specializes in mathematical modelling, analysis and computation of partial differential equations pertaining to fluid mechanics or modeling of materials.
<> Computer Vision (4) <> numerical methods (4)

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

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B1 L3 R3119

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

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

-

B1 L3 R3119

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

Mini Course Part 1-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

-

B1 L3 R3119

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

Deterministic particle approximation for nonlinear transport equations

-

Building L3 R3119

Approximating the solution to an evolutionary partial differential equation by a set of "moving particles" has several advantages. It validates the use of a continuity equation in an "individuals-based" modeling setting, it provides a link between Lagrangian and Eulerian description, and it defines a "natural" numerical approach to those equations. I will describe recent rigorous results in that context. The main one deals with one-dimensional scalar conservation laws with nonnegative initial data, for which we prove that the a suitably designed "follow-the-leader" particle scheme approximates entropy solutions in the sense of Kruzkov in the many particle limit. Said result represents a new way to solve scalar conservation laws with bounded and integrable initial data. The same method applies to second order traffic flow models, to nonlocal transport equations, and to the Hughes model for pedestrian movements.
<> Signal processing (4) <> AI (3) <> Computational mathematics (3)

In January 2020 Prof. Dimitrios Mitsotakis visits Applied PDE research group

1 min read ·
Prof. Dimitrios Mitsotakis from Victoria University Wellington New Zealand will be visiting our group from January 3rd - February 29th. Dimitrios is an expert in modelling and computations of water wave propagation.

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

Ioanna Mousikou

Short Bio Ms. Ioanna Mousikou is a Ph.D student in the AppliedPDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. During her second year at KAUST, she received a Master's degree in Applied Mathematics where the thesis was focused on numerical methods for hyperbolic conservation laws. Before joining KAUST, Ms. Ioanna completed undergraduate degree in Mathematics at the University of Cyprus. Education Profile M.Sc. KAUST, Saudi Arabia, 2016 B.Sc. Mathematics, University of Cyprus
<> Mathematical modeling (3)

Ali O Balubaid

Ph.D Directed Research at KAUST (King Abdullah University of Science and Technology)

Meet KAUST prospective student: Stefanos Georgiadis

1 min read ·
Stefanos Georgiadis is an applied mathematics graduate who will join KAUST from the School of Applied Mathematical and Physical Sciences, Athens, Greece. Stefanos will join KAUST this fall as a Ph.D. candidate and member of the Applied Partial Differential Equations (AppliedPDE) research group under the supervision of Professor Athanasios Tzavaras.

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
<> mathematical modelling (3)

AMCS Mini Course: Mathematical and numerical modelling of water waves

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B1 L3 R3119

Abstract : The mathematical modelling of water waves continues to attract great interest both from a mathematical point of view, due to the difficulty of solving the systems of nonlinear partial differential equations that describe the relevant physical phenomena, and also from that of fluid mechanics, due to complexity of the physical phenomena that occur during the propagation of water waves and their importance in oceanography and coastal dynamics. The basic mathematical model is the system of the Euler equation for the motion of the free surface and the evolution of the velocity field of

Stefanos Georgiadis

Stefanos Georgiadis is a Ph.D. candidate in a co-tutelle between KAUST and TU Wien, under the supervision of Professor Athanasios Tzavaras and Ansgar Jüngel. Before joining KAUST, Stefanos obtained his bachelor and master's degree in applied mathematics from the School of Applied Mathematical and Physical Sciences of the National Technical University of Athens in Greece. Research Interests Stefanos' research interests include the analysis of nonlinear partial differential equations as they apply to the modeling of multicomponent systems of gases.

Athanasios Tzavaras

KAUST Professor of Applied Mathematics and Computational Science Athanasios (Thanos) Tzavaras specializes in mathematical modelling, analysis and computation of partial differential equations pertaining to fluid mechanics or modeling of materials.
<> MATLAB (3) <> Multi-face flows (3)

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

-

B1 L3 R3119

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

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

-

B1 L3 R3119

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

Mini Course Part 1-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

-

B1 L3 R3119

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
<> numerical methods for PDE's (3)

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

Ioanna Mousikou

Short Bio Ms. Ioanna Mousikou is a Ph.D student in the AppliedPDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. During her second year at KAUST, she received a Master's degree in Applied Mathematics where the thesis was focused on numerical methods for hyperbolic conservation laws. Before joining KAUST, Ms. Ioanna completed undergraduate degree in Mathematics at the University of Cyprus. Education Profile M.Sc. KAUST, Saudi Arabia, 2016 B.Sc. Mathematics, University of Cyprus

Grigorios Kounadis

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
<> scientific computing (3)
Georgios Grekas

Georgios Grekas

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

Grigorios Kounadis

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
<> AI4Science (2) <> Analysis of PDE's (2) <> applied mathematics (2) <> Conservation Laws (2) <> Dynamical Systems (2) <> Generative AI and LLMs (2) <> healthcare (2) <> IoT (2) <> Liquid Crystals (2) <> Localization (2) <> Network Design (2) <> Nonlinear Partial Differential Equation (2)

Gravitational Collapse of Self-similar stars

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B1 L4 R4102

The Euler-Poisson equations give the classical model of a self-gravitating star under Newtonian gravity. It is widely expected that, in certain regimes, initially smooth initial data may give rise to blow-up solutions, corresponding to the collapse of a star under its own gravity. In this talk, I will present recent work with Yan Guo, Mahir Hadzic and Juhi Jang that demonstrates the existence of smooth, radially symmetric, self-similar blow-up solutions for this problem. I will also comment on the stability of the obtained solution. At the heart of the analysis is the presence of a sonic point, a singularity in the self-similar model that poses serious analytical challenges in the search for a smooth solution.

Shuaikun Wang

Short Bio Shuaikun Wang received his bachelor's degree in Mathematics from University of Science and Technology of China in 2012 and a Ph.D degree in Mathematics from City University of Hong Kong in 2016. He was a postdoc in City University of Hong Kong in 2016-2017 and a Postdoctoral Research Fellow in the Applied PDE group at KAUST from September 2017 - December 2020. Currently he is an Associate Professor in the School of Mathematics, Shandong University, Jinan, China. Shuaikun Wang's research interests lie in the area of applied analysis, nonlinear partial differential equations and
<> numerical analysis (2) <> PDE (2)

Deterministic particle approximation for nonlinear transport equations

-

Building L3 R3119

Approximating the solution to an evolutionary partial differential equation by a set of "moving particles" has several advantages. It validates the use of a continuity equation in an "individuals-based" modeling setting, it provides a link between Lagrangian and Eulerian description, and it defines a "natural" numerical approach to those equations. I will describe recent rigorous results in that context. The main one deals with one-dimensional scalar conservation laws with nonnegative initial data, for which we prove that the a suitably designed "follow-the-leader" particle scheme approximates entropy solutions in the sense of Kruzkov in the many particle limit. Said result represents a new way to solve scalar conservation laws with bounded and integrable initial data. The same method applies to second order traffic flow models, to nonlocal transport equations, and to the Hughes model for pedestrian movements.

Myoungkeun Shin

PDE UWOC

Myoungkeun Shin is a MS/Ph.D student in the Communication Theory Lab (CTL) under the supervision of Professor Mohamed-Slim Alouini at King Abdullah University of Science and Technology (KAUST). Education and Early Career Myoungkeun obtained his bachelor degree in mathematics from Seoul National University (SNU) in 2011. Before joining KAUST, he taught mathematics to high school students in Korea. Research Interest Myoungkeun’s primary research interests are in PDE and UWOC. Education Profile M.S. in Applied Mathematics and Computational Science, Kind Abdullah University of Science and
<> Programming language (2) <> Viscoelasticity (2) <> Water wave propagation (2) <> 5G networks (1) <> 6g wireless systems (1) <> Action Recognition (1) <> Action understanding (1) <> Aggregation-diffusion equations (1) <> AI for healthcare (1) <> Applied PDE's (1) <> beamforming (1) <> biomechanics (1) <> Biomedical Signal Processing (1) <> bioscience (1) <> biotechnology (1) <> BLE communication (1) <> Cauchy problem (1) <> Cellular Networks (1) <> cloud- and fog-radio access networks (1) <> communication (1) <> communication networks (1) <> communication systems (1) <> Compressed Sensing Approach (1) <> computational methods (1) <> computer networks (1) <> Continual Learning (1) <> continuum physics (1) <> Cooperative networks (1) <> cross-layer optimization (1) <> Cucker-Smale orientation dynamics (1) <> data analysis (1) <> Data Analyst (1) <> Deep generative models (1) <> development (1) <> Diffusion equations (1) <> Digital Communications (1) <> Digital signal processing (1) <> Dispersive-diffusive systems (1) <> Electron Transport (1) <> embedded systems (1) <> Embedded systems. (1) <> energy efficiency (1) <> Euler equations (1) <> Euler flows (1) <> fluid dynamics (1) <> Fluid Mechanics (1) <> Fokker-Planck equations (1) <> free boundary problems (1) <> Gradient flows (1) <> Gravitational collapse (1) <> GSM (1) <> haps (1) <> High friction limits (1) <> Higher-gradient viscoelasticity (1) <> Hyperbolic PDEs (1) <> Hyperbolic-Parabolic Systems (1) <> interference management (1) <> intrusion detection (1) <> inverse problems (1) <> Keller-Segel-type models (1) <> Kinetic models (1) <> Kinetic Theory (1) <> living systems (1) <> Mathematical Biology (1) <> mathematics (1) <> McKean-Vlasov equations (1) <> Measure Valued Solutions (1) <> Medical imaging (1) <> microelectronics (1) <> Microgrids (1)