Stochastic Numerics PI Professor Raul Tempone (Chair) and Computational Probability PI Professor Ajay Jasra (Co-Chair)
Sunday, May 19, 2024, 08:00
- 17:00
KAUST, Auditorium 0215
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Dear Kaustians, We are excited to announce the upcoming Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2024, taking place at KAUST, Building 9, from May 19-30, 2024. Following the highly successful 2022 and 2023 editions, this year's workshop promises to be another engaging and insightful event for researchers, faculty members, and students interested in stochastic algorithms, statistical learning, optimization, and approximation. The 2024 workshop aims to build on the achievements of last year's event, which featured 28 talks, two mini-courses, and two poster sessions, attracting over 150 participants from various universities and research institutes. In previous two years attendees had the opportunity to learn from through insightful talks, interactive mini-courses, and vibrant poster sessions. This year, the workshop will once again showcase contributions that offer mathematical foundations for algorithmic analysis or highlight relevant applications. Confirmed speakers include renowned experts from institutions such as Ecole Polytechnique, EPFL, Université Pierre et Marie Curie - Paris VI, and Imperial College London, among others.
Prof. Francesca Gardini, Università di Pavia
Tuesday, April 30, 2024, 16:00
- 17:00
Building 1, Level 3, Room 3119
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We will discuss the solution of eigenvalue problems associated with partial differential equations (PDE)s that can be written in the generalised form Ax = λMx, where the matrices A and/or M may depend on a scalar parameter. Parameter dependent matrices occur frequently when stabilised formulations are used for the numerical approximation of PDEs. With the help of classical numerical examples we will show that the presence of one (or both) parameters can produce unexpected results.
Prof. Edgard Pimentel
Tuesday, March 26, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5220
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Hessian-dependent functionals play a pivotal role in a wide latitude of problems in mathematics. Arising in the context of differential geometry and probability theory, this class of problems find applications in the mechanics of deformable media (mostly in elasticity theory) and the modelling of slow viscous fluids. We study such functionals from three distinct perspectives.
Thursday, March 21, 2024, 12:00
- 13:00
Building 9, Level 2, Room 2325, Hall 2
In this work, we employ importance sampling (IS) techniques to track a small over-threshold probability of a running maximum associated with the solution of a stochastic differential equation (SDE) within the framework of ensemble Kalman filtering (EnKF).
Tuesday, March 19, 2024, 16:00
- 17:30
Building 9, Level 2, Room 2325
Artificial materials represent composite media that can be meticulously engineered to exhibit unique wave propagation behaviors. Our research endeavors are driven by the intriguing principles underlying these materials, such as effective models, and their broad applications, including perfect absorption. In this presentation, I will outline our recent advancements in our innovative design strategies for novel artificial materials from both forward first-principle physics-based modeling and data-driven approaches. Specifically, I will highlight our pioneering work in the designs of double-zero-index materials for both electromagnetic and acoustic waves. Additionally, I will discuss our discovery of the acoustic Purcell effect for enhanced emission, as well as our development of analytic and numerical solutions for space-time modulated wave systems. Furthermore, I will delve into our practical solution for achieving broad frequency cloaking of invisibility. These accomplishments hold significant promise for a wide range of applications spanning sound control, communication, sensing, imaging and more.
Fabio Credali, Postdoc at IMATI, Pavia
Tuesday, March 12, 2024, 14:30
- 15:30
B1, L4, seaside, R4214
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In 2019, diabetes caused 1.5 million global deaths, with 48% occurring before age 70. While Type 1 diabetes strongly depends on genetic components and is usually diagnosed in childhood, Type 2 diabetes is primarily caused by long term consumption of high calories foods. Lifestyle choices significantly influence the risk of Type 2 diabetes and obesity, including energy intake, diet composition, physical activity, and smoking.
Thursday, March 07, 2024, 12:00
- 13:00
B9, L2, R2325, H2
When pressure acoustic waves interact with rotating scatterers, they undergo peculiar and intriguing characteristics. In this talk, I will discuss our recent findings on the physics of acoustic scattering and propagation in spinning fluids.
Prof. Silvia Bertoluzza
Tuesday, March 05, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5209
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We present a theoretical analysis of the Weak Adversarial Networks (WAN) method, recently proposed in [1, 2], as a method for approximating the solution of partial differential equations in high dimensions and tested in the framework of inverse problems. In a very general abstract framework.
Prof. Christof Schmidhuber, ZHAW School of Engineering
Tuesday, February 27, 2024, 16:00
- 17:00
Building 9, Level 2, Room 2322
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Analogies between financial markets and critical phenomena have long been observed empirically. So far, no convincing theory has emerged that can explain these empirical observations. Here, we take a step towards such a theory by modeling financial markets as a lattice gas.
Jason Avramidis, Director of Innovation and International Flexibility Markets for OakTree Power, UK
Tuesday, February 13, 2024, 12:00
- 13:00
Building 1,Level 4, Room 4214
Until very recently, distribution-led local flexibility markets were exclusively an academic endeavor, with few practical applications, mostly limited to small-scale innovation projects. However, with European regulation finally catching up with the realities of modern distribution networks, local flexibility markets are slowly becoming a reality - new ones popping up across the continent, or some even becoming a BAU option in the most advanced countries.
Professor Norbert J Mauser, Mathematics, University of Vienna
Sunday, February 11, 2024, 16:00
- 17:00
Building 1, Level 3, Room 3119
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The Pauli-Poisswell equation models fast-moving charges in semiclassical semi-relativistic quantum dynamics. It is at the center of a hierarchy of models from the Dirac-Maxwell equation to the Euler-Poisson equation that is linked by asymptotic analysis of small parameters such as the Planck constant or inverse speed of light. We discuss the models and their application in plasma and accelerator physics as well as the many mathematical problems they pose
Prof. Ulrich Langer, Institute of Numerical Mathematics, Johannes Kepler University, Linz
Wednesday, February 07, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5209
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We consider the widely used continuous $Q_{k+1}-Q_k$ quadrilateral or hexahedral Taylor-Hood elements for the finite element discretization of the Stokes and generalized Stokes systems in two and three spatial dimensions.
Prof. Dr. Victorita Dolean, Mathematics and Computer Science, Scientific Computing, TU Eindhoven
Tuesday, February 06, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5220
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Wave propagation and scattering problems are of huge importance in many applications in science and engineering - e.g., in seismic and medical imaging and more generally in acoustics and electromagnetics.
Prof. Yong-Jung Kim, KAIST, Korea
Tuesday, February 06, 2024, 14:00
- 15:30
Building 2, Level 5, Room 5209
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A subtle difference in a diffusion model can lead to an opposite conclusion. We need to understand how each component involved in the diffusion phenomenon contributes to the diffusion model. In this talk, we will discuss how nonconstant persistence and permeability play a role in the diffusion phenomenon.
Professor Vincenzo Vespri, of Mathematics Department at the University of Florence, Italy
Monday, February 05, 2024, 16:00
- 17:00
Building 1, Level 3, Room 3119
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The term doubly nonlinear refers to the fact that the diffusion part depends nonlinearly both on the gradient and the solution itself. Such equations describe several physical phenomena and were introduced by Lions and Kalashnikov. These equations have an intrinsic mathematical interest because they represent a natural bridge between the more natural generalizations of the heat equation: the p-Laplacian and the porous medium equation.
Prof. Zhiming Chen, Academy of mathematics and Systems Science, Chinese Academy of Sciences
Wednesday, January 24, 2024, 14:30
- 16:00
Building 4, Level 5, Room 5220
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In this short course, we will introduce some elements in deriving the hp a posteriori error estimate for a high-order unfitted finite element method for elliptic interface problems. The key ingredient is an hp domain inverse estimate, which allows us to prove a sharp lower bound of the hp a posteriori error estimator.
Prof. Zhiming Chen, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Tuesday, January 23, 2024, 16:00
- 17:00
Building 2, Level 5, Room 5220
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Coffee time: 15:30–16:00. We consider high-order unfitted finite element methods on Cartesian meshes with hanging nodes for elliptic interface problems, which release the work of body-fitted mesh generation and allow us to design adaptive finite element methods for solving curved geometric singularities.
Prof. Bert Claessens, Ghent University, Belgium
Monday, January 22, 2024, 13:00
- 14:00
Building 3, Level 5, Room 5209
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In the last decade reinforcement learning has demonstrated tremendous progress in terms of being a model-free control paradigm for decision making in complex systems with uncertainty and partial observability, thus making it a candidate technology for demand response with a promise of true scalability.
Thursday, December 07, 2023, 12:00
- 13:00
Building 9, Level 2, Room 2325
In this talk, we consider Bayesian parameter inference associated to a class of partially observed stochastic differential equations (SDE) driven by jump processes. Such type of models can be routinely found in applications, of which we focus on the case of neuroscience.
Dr. Jeffrey M. Bradshaw, Institute for Human and Machine Cognition (IHMC), Florida, USA
Wednesday, December 06, 2023, 14:00
- 15:00
Building 1,Level 4, Room 4102
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Over the past decades, Jeff has been lucky enough to follow some of these developments from a front-row seat. He will share selected perspectives on current and past research including the various pendulum swings over the years between extremes, such as expertise-based knowledge engineering vs. data-centric machine learning, autonomous vs. mixed-initiative systems, publicly available chatbot capabilities vs. personalized, policy-governed multi-agent systems. In this talk, I will show what past research in AI has to teach us about the future.
Prof. Tao Tang
Tuesday, December 05, 2023, 16:00
- 17:00
Building 5, Level 5, Room 5209
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Coffee Time: 15:30 - 16:00. The phase-field model, a powerful modeling tool for dealing with interface problems, has been widely used in various fields such as computational physics, computational biology, materials engineering, and even image processing. The dissipation of free energy is an important and fundamental property of the phase-field model.
Professor, Suleyman Ulusoy, School of Arts and Sciences, American University of Ras Al Khaimah
Tuesday, December 05, 2023, 14:30
- 15:30
Building 1,Level 4, Room 4214
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We provide error estimates and stability analysis of deep learning techniques for certain partial differential equations including the incompressible Navier-Stokes equations. In particular, we obtain explicit error estimates (in suitable norms) for the solution computed by optimizing a loss function in a Deep Neural Network approximation of the solution, with a fixed complexity. This is a joint work with A. Biswas and J. Tian.
Giuseppe Di Fazio, Professor, Mathematics and Computer Sciences, University of Catania, Italy
Tuesday, December 05, 2023, 13:00
- 14:00
Building 1, Level 4, Room 4214
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Let us consider an elliptic equation of second order in variational form i.e. div(A(x)∇u) = divf in a bounded domain Ω ⊂ Rn where the function f belongs to some suitable function space.
Prof. Tao Tang's personal website
Monday, December 04, 2023, 15:30
- 17:00
Building 3, Level 5, Room 5220
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Splitting methods have been shown to a useful tool in solving phase field equations. However, rigorous nonlinear stability analysis has not been available. In this short course, we will discuss some recent development in this direction.