Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2026 Nov 22, 08:30 - Dec 2, 13:30 B2/3 A0215 Workshops stochastic algorithm numerical analysis statistical learning Bringing together experts in stochastic algorithms, numerical analysis and statistical learning with applications in climate modeling and quantitative finance.
Threshold Dynamics and Delayed Closure in a Moving-Boundary Model of Epidermal Wound Healing Zhang Zhiwen, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Sep 10, 12:00 - 13:00 B9 R2325 healthcare technologies numerical analysis analytical tools numerical simulations healthcare analytics We analyze how growth-factor production, diffusion, decay, activation thresholds, and wound geometry interact to determine whether epidermal wound closure begins, proceeds continuously, experiences repeated delays, or stops before completion.
The Event Horizon Telescope: From the First Images to the First Movies of Black Holes Laurent Loinard, Professor of Astronomy, Institute for Radio Astronomy and Astrophysics (IRyA), National Autonomous University of Mexico (UNAM) Sep 7, 16:00 - 17:00 B20 Auditorium Astrophysics Visualization High Performance Computing algorithms telescope statistical inference computational analysis galaxy black holes astrometry This lecture explores the Event Horizon Telescope's groundbreaking achievements in imaging supermassive black holes, details the complex global and computational infrastructure enabling these discoveries, and outlines the future transition from static images to dynamic, real-time movies of the universe's most extreme environments.
Geospatial Data Science for Public Health Surveillance Paula Moraga, Associate Professor, Statistics Sep 3, 12:00 - 13:00 B9 R2325 geospatial data analysis health monitoring spatio-temporal disease data climate data health policy This talk will provide an overview of statistical methods and computational tools for geospatial health data analysis and disease surveillance, with a focus on forecasting climate-sensitive diseases, the integration of health, climate, and digital data, and their role in informing public health policy.
Stochastic Optimal Control with Applications to Renewable Energy and Partially Observed Systems Eliza Rezvanova, Ph.D. Student, Applied Mathematics and Computational Science Aug 6, 15:00 - 17:00 B5 R5209; Zoom Meeting 4569553742 Partially Observed Stochastic Optimal Control Stochastic Optimal Control renewable energy Dynamic programming This thesis develops continuous-time dynamic programming frameworks and shows how dynamic programming and HJB methods can be extended to settings that do not satisfy the classical Markovian and full-observation assumptions through appropriate relaxation and state-reformulation techniques.
Gray Scott School 2026 Jun 29 - Jul 2, All day B3 L2 R2202 HPC Performance optimization parallel computing Join an international training program focused on GPU computing and HPC technologies.
Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization Grigory Malinovsky, Ph.D. Student, Applied Mathematics and Computational Science Jun 18, 15:45 - 19:00 B5 R5209 machine learning Federated learning distributed optimization applied statistics This thesis investigates seven critical challenges at the intersection of theory and practice, specifically focusing on the fundamental bottlenecks of Federated Learning and distributed optimization and develops novel algorithmic frameworks that provide sharp theoretical guarantees to bridge the gap between heuristic success and mathematical rigor.
Time Series Clustering: Pattern Recognition, Forecasting, and Amortized Inference Ángel López Oriona, Postdoctoral Research Fellow, Statistics May 14, 12:00 - 13:00 B9 R2325 Time Series Pattern Recognition forecasting statistical inference This talk presents innovative time series clustering techniques, highlighting a quantile-based approach for analyzing locally stationary data, a predictive framework for enhanced forecasting, and the use of amortized inference to overcome traditional algorithmic limitations.
Stability and Signal Generator Agnostic Moment Matching Alessandro Astolfi, Professor, Applied Mathematics and Computational Science May 10, 14:30 - 15:30 B1 R3119 moment matching model reduction interpolation Stability This talk explores advancements in model reduction that modernize traditional moment matching by introducing a data-driven procedure for unknown signal generators and a closed-loop interpolation framework that extends these techniques to unstable systems.
Fully Decentralized Inference for Spatial Data Using Low-Rank Models Jianwei Shi, Postdoctoral Research Fellow, Statistics May 7, 12:00 - 13:00 B9 R2325 statistical inference decentralized systems Geospatial Data geospatial statistics optimization This talk introduces a novel, fully decentralized optimization framework to enable scalable parameter inference in large spatial low-rank models, supported by both theoretical guarantees and empirical validation.
Event Status: Cancelled | Robust and Fuzzy Methods for High-Dimensional Time Series Clustering and Forecasting Ziling Ma, Ph.D. Student, Statistics Apr 30, 12:00 - 13:00 B9 R2325 These talks introduce several robust methods for clustering and forecasting multivariate time series data.
Mathematical Modeling and Analysis of Liquid Crystals: Ericksen-Leslie Model Majed Sofiani, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Apr 27, 14:00 - 15:00 B1 R3426 Ericksen-Leslie Model non-linear partial differential equations Liquid Crystals Navier-Stokes equation This talk I will provide an overview of the celebrated Ericksen-Leslie model for nematic liquid crystals.
Dynamical Systems in Data Science: From Kinetic Closure to Learning Dynamics Dr. Florian Kogelbauer, Senior Research Fellow, Swiss Federal Institute of Technology Zurich (ETH Zurich) Apr 27, 12:00 - 13:00 B2/3 A0215 This talk explores two ways in which ideas from dynamical systems can shape the mathematics of data science.
Rare-Event Simulation Methods for Outage Probability in GSC/MRC Systems under Rician Fading Mahmoud Hassan Ghazal , Ph.D. Student, Electrical and Computer Engineering Apr 23, 12:00 - 13:00 B9 R2325 Statistics of extremes Outage Probability Applied Probability This talk explores enhanced Monte Carlo (MC) techniques for estimating the OP of SIMO systems under Rician fading, where the selected signals are combined using maximum ratio combining (GSC/MRC).
Efficient Numerical Methods for Scalable Bayesian Inference Lisa Gaedke-Merzhäuser, Postdoctoral Research Fellow, Statistics Apr 16, 12:00 - 13:00 B9 R2325 numerical methods Efficient Bayesian Inversion Automated and scalable algorithms This talk will introduce and discuss the computational building blocks of Integrated Nested Laplace Approximations (INLA) and how these are implemented in software libraries such as R-INLA or DALIA.
Data Analytics to Outcome Impact for Transplantation and Clinical Practice Apr 9, 10:00 - 16:00 B3 R5209 Workshops AI for healthcare Mathematical modeling smart health bioinformatics Data Analytics Leveraging national data analytics and computational tools to advance transplantation and clinical practice.
The Role of Humans in Scientific Discovery in the Age of LLMs — Beyond Asking: Turning LLMs into Research Collaborators Sir Bashir M. Al-Hashimi, Vice President, Research & Innovation, King’s College London (KCL); Distinguished Professor, Department of Engineering, Faculty of Natural, Mathematical & Engineering Sciences, King’s College London (KCL) Apr 8, 12:00 - 14:15 B9 R2325 AI artificial intelligence LLM scientific research scientific knowledge Assistive Technology Rather than offering definitive conclusions, this talk seeks to stimulate dialogue, question assumptions, and inspire new forms of collective thinking about the future of scientific research and doctoral training in an AI-driven world.
Reduced-Order High Fidelity Simulations of Reacting Flows Using Low Dimensional Manifolds and Machine Learning Hong G. Im, Professor, Mechanical Engineering; Deputy Chair, Clean Energy Research Platform, King Abdullah University of Science and Technology (KAUST) Apr 7, 14:30 - 15:30 B1 R3119 machine learning Applied Machine Learning principal component analysis PCA computational singular perturbation renewable energy flow problems computational simulations This talk will provide an overview of historical developments in mathematical and computational approaches to reduced order models for accelerated high fidelity reacting flow simulations in modern computing hardware.
A Unified Monotonicity Framework for Mean-Field Games Rita A. Ferreira, Research Scientist, Mean-field Games and Nonlinear PDE Apr 2, 12:00 - 13:00 B9 R2325 gamma-convergence asymptotic analysis variational analysis Variational mean-field games In this talk, we discuss how monotone operator methods provide a unified approach to existence, uniqueness, and regularity in MFGs.
Extrapolated Linear Multistep Methods Lajos Lóczi, Research Scientist, Applied Mathematics and Computational Science Mar 12, 12:00 - 13:00 B9 L2 R2325 ODEs PDEs numerical methods linear multistep methods LMMs In this talk, we will discuss how linear multistep methods and classical extrapolation can be combined to obtain new classes of efficient time-integration methods.
Advances in Multiscale Hierarchical Decomposition Methods for Image Restoration Luminita Vese, Professor of Mathematics, University of California, Los Angeles (UCLA) Mar 10, 14:30 - 15:30 B1 L3 R3119; Zoom Meeting 99254591389 This talk will present the multiscale hierarchical decomposition method (MHDM) for image restoration and scale separation, building on the framework introduced by Tadmor, Nezzar, and me.
Mathematical Modelling of Solar Cells Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Mar 10, 11:00 - 12:30 B1 L3 R3119 solar cells Mathematical modeling PDEs numerical PDEs This talk presents the development and the numerical approximation of mathematical models for some well known solar cell architectures.
Event Status: Cancelled | Remote Sensing and Agroinformatics Insights in Saudi Arabia Using Machine Learning Ting Li, Postdoctoral Research Fellow, Environmental Science and Engineering Mar 5, 12:00 - 13:00 B9 L2 R2325 remote sensing machine learning sustainable agricultural agricultural productivity This talk explores how machine learning and high-resolution satellite remote sensing are being used to transform vast amounts of raw data into actionable agroinformatics at a national scale, providing the precision needed to manage these vital resources sustainably.
Approximation and Optimization for Neural Networks Gerrit Welper, Assistant Professor, Mathematics, University of Central Florida (UCF) Mar 4, 16:00 - 17:00 Zoom Meeting 95807131415 Neural Networks optimization deep neural networks Finite element methods In this talk, we consider new connections between the approximation and optimization of neural networks. Instead of relying on excessive over-parametrization to achieve zero training loss, we identify good minima by comparison with established approximation bounds.
Structure Preserving Methods for Schrodinger Type of Equations Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Mar 3, 14:30 - 15:30 B1 L3 R3119 Schrödinger equation cosmology waves This talk presents a class of structure preserving methods for Schrodinger type of equations with applications in the generation of rogue waves and cosmology.
Rigorous Model-Constrained Scientific Machine Learning for Digital Twins: A Computational Mathematics Perspective Tan Bui-Thanh, Professor, Endowed William J. Murray, Jr. Fellow in Engineering No. 4, Oden Institute for Computational Engineering & Sciences, Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin (UT Austin) Feb 26, 14:30 - 15:30 B1 L3 R3119 Scientific Machine Learning SciML Scientific Deep Learning SciDL deep learning machine learning digital twins uncertainty quantification Computational mathematics This talk will outline a principled pathway from traditional computational mathematics to rigorously grounded Scientific Machine Learning (SciML) and present recent Scientific Deep Learning (SciDL) methods for forward modeling, inverse and calibration problems, and uncertainty quantification, emphasizing mathematical structure, stability, and generalization.
Graphpcor: Prior for Correlation Matrices Elias Teixeira Krainski, Research Scientist, Statistics Feb 26, 12:00 - 13:00 B9 L2 R2325 correlation Bayesian Estimation expert knowledge integration This talk introduces a scalable, graph-based framework for modeling correlation matrices that integrate expert-informed priors.
Computing Heteroclinic Orbits for Dynamical Systems Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Feb 23, 11:00 - 12:30 B1 L3 R3119 Dynamical Systems heteroclinic orbits Numerical Modeling This course provides an overview of the most well known methods for computing heteroclinic orbits for dynamical systems.
C1+alpha Regularity for the Fractional p-Laplacian David De Jesus, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Feb 19, 12:00 - 13:00 B9 L2 R2325 Mathematical modeling In this talk, we will discuss a recent result obtained in collaboration with Davide Giovagnoli and Luis Silvestre, where we solve a standing conjecture asserting that, as in the local setting, solutions of the homogeneous equation are still Hölder differentiable.
A Dichotomy of Continuous Finite Element Spaces and Its Application to Energy-Conservative Galerkin Methods for Nonlinear and Dispersive Wave Equations Dimitrios Mitsotakis, Reader/Associate Professor, Engineering Mathematics, School of Mathematics and Statistics, Victoria University of Wellington (VUW) Feb 17, 14:30 - 15:30 B1 L3 R3119 dispersive waves optimization Finite elements This talk illustrates why energy-conservative Galerkin methods for nonlinear and dispersive wave equations achieve optimal convergence rate with odd-degree polynomials.
Data-driven Anomaly Detection in Industrial Processes Fouzi Harrou, Senior Research Scientist, Statistics Feb 12, 12:00 - 13:00 B9 L2 R2325 anomaly detection multivariate statistics artificial intelligence AI This talk presents a model-based anomaly detection framework, along with data-driven process monitoring approaches based on multivariate statistical methods and artificial intelligence techniques.
Mathematical Design and Analysis of Iterative Methods for Linear and Nonlinear Problems Jongho Park, Assistant Professor, School of Science and Engineering (SSE), The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen) Feb 10, 14:30 - 15:30 B1 L3 R3119 nonlinear models algorithms iterative methods This talk presents a systematic approach to the design and analysis of iterative methods for solving linear and nonlinear problems.
Jongho Park, Assistant Professor, School of Science and Engineering (SSE), The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen)
On the Modeling and Approximation of Phase Transitions in Elasticity Georgios Grekas, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Feb 5, 12:00 - 13:00 B9 L2 R2325 Phase transitions elasticity mathematical modelling This talk explores the mathematical modeling of phase transitions in elasticity, drawing motivation from observed phenomena in crystalline solids and biomaterials.
Energy-Efficient and Sustainable Spatial Modeling Using GPU Computing Sameh Abdulah, Senior Research Scientist, Applied Mathematics and Computational Science Jan 29, 12:00 - 13:00 B9 L2 R2325 HPC This talk highlights recent advances in energy-efficient and sustainable spatial modeling using GPU computing. It focuses on mixed-precision algorithms and scalable spatial statistical modeling that significantly reduce computational cost and power consumption while preserving scientific accuracy.
The Sharpness Condition for Constructing Finite Element From a Superspline Qingyu Wu, Ph.D. Student, Mathematics, Peking University Jan 28, 14:00 - 15:00 B1 L3 R3119 In this talk, I will discuss the sharpness conditions for constructing Cʳ conforming finite element spaces from superspline spaces on general simplicial triangulations and introduce the concept of extendability for pre-element spaces, which unifies both superspline and finite element spaces under a common framework.
KAUST Research Conference on Mathematical and Data Sciences Jan 26 - 28, All day KAUST Campus data science scientific computing Computer science Theory and applications of data science.
Empowering Natural Intelligence with Artificial Intelligence: a Mathematician's Perspective Alfio Quarteroni, Emeritus Professor, Politecnico di Milano and EPFL Jan 25, 14:00 - 15:00 B9, L2, R2322 Computational mathematics numerical methods Scientific Machine Learning scientific computing applied mathematics A Dean’s Distinguished Lecture on natural intelligence, artificial intelligence and scientific machine learning.
Programmable Wavefunction Dynamics for Topological and Nonlinear Acoustic Control Ze-Guo Chen, Associate Professor School of Advanced Manufacturing, Nanjing University, China Jan 21, 10:00 - 11:00 B1 L3 R3119 topological phenomena This talk presents a unified route to topological and nonlinear acoustic control through engineered time-dependent modulation of on-site parameters, couplings, gain/loss, and external driving.
Isotropic Geometry and Applications in Geometric Computing Khusrav Yorov, Ph.D. Student, Applied Mathematics and Computational Science Jan 15, 10:30 - 12:00 B3 L5 R5209 Isotropic Geometry geometry processing discrete differential geometry This thesis addresses challenges in computational design and fabrication, particularly in the geometry of architectural gridshell structures and their approximation, by solving nonlinear optimization problems.
Mean Field Games: From Many-Player Games to PDEs Melih Ucer, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Dec 11, 12:00 - 13:00 B9, L2, R2325 mean field games hamilton–jacobi equations monotone operator theory This talk will introduce the basic concepts of mean field games, beginning with the mean field limit that describes systems with infinitely many infinitesimal players.
Stochastic Interacting Particle Methods and Generative Learning for Multiscale PDEs Jack Xin, Distinguished Professor, Department of Mathematics, School of Physical Sciences, University of California, Irvine Dec 9, 14:30 - 15:30 B1 L3 R3119 PDEs machine learning This talk discusses stochastic interacting particle (SIP) methods for advection-diffusion-reaction PDEs based on probabilistic representations of solutions, and shows their self-adaptivity and efficiency in several space dimensions.
Tales of a Spur Hunter: The Wandering Spur Michael Peter Kennedy, Full Professor, School of Electrical and Electronic Engineering, University College Dublin Dec 7, 12:00 - 13:00 B9 L2 R2325 Prof. Michael Peter Kennedy presents the decade-long journey to diagnose and fix 'wandering spurs' in frequency synthesizers.
Nuclear Fusion Powered by AI and HPC Vladimir Pimanov, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Dec 4, 12:00 - 13:00 B9 L2 R2325 AI artificial intelligence Fusion simulation This talk presents advanced simulations with AI-driven optimization to improve the performance of a next-generation plasma-jet-driven magneto-inertial fusion concept.
Will AI Replace Professors? Pavel Pevzner, Ronald R. Taylor Chair and Distinguished Professor, Computer Science and Engineering, University of California, San Diego Dec 4, 12:00 - 13:00 B2/B3 L0 A0215 This talk explores Massive Adaptive Interactive Texts (MAITs) as a pioneering AI technology that aims to replace the one-size-fits-all lecture model with a responsive and scalable system for individualized instruction.
Leader-Follower Opinion Dynamics: Socio-Economic Factors and Optimal Control Bertram Düring, Professor of Mathematics Mathematics Institute, University of Warwick Dec 2, 14:30 - 15:30 B1 L3 R3119 PDEs This talk will discuss the partial differential equation-constrained optimal control for a leader-follower opinion formation model and derive first-order optimality conditions.
Mathematical Imaging in the Era of AI Carola-Bibiane Schönlieb, Professor, DAMTP, University of Cambridge Dec 2, 13:30 - 14:30 B1 L23 R3119 AI optimization In this talk, I will present mathematical imaging as a meeting point of classical analysis and modern AI. I will highlight how ideas from optimisation and mathematical modelling can guide the development of structure-preserving deep learning methods, offering new, principled approaches to large-scale inverse imaging problems.
C1-Conforming Virtual Element Method (VEM) for Optimal Control of Oseen Equations with a Stream-Function Formulation Harpal Singh, Ph.D. Student, Department of Mathematics, Indian Institute of Technology Roorkee Dec 1, 14:30 - 15:30 B1 L3 R3426 Virtual Element Method This talk presents a C¹-conforming Virtual Element Method for the optimal control of generalized Oseen equations, detailing its discretization strategies, theoretical error estimates, and numerical validation on polygonal meshes.
Finite Element Approximation of Eigenvalue Problems in Mixed Form Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering Nov 27, 12:00 - 13:00 B9 L2 R2325 This talk will discuss the finite element approximation of the eigenvalues associated with the Maxwell system.
Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering
Phenomenological and Mechanistic Modeling of Gene Regulatory Dynamics in Cell Differentiation Using Single-Cell Data Juan Pablo Bernal Tamayo, Ph.D., Applied Mathematics and Computational Science Nov 26, 10:00 - 12:00 B24 (Innovation Cluster) L3 R3302 This dissertation develops integrated phenomenological and mechanistic modeling frameworks that maintain biological interpretability while capturing regulatory dynamics during cellular differentiation.
KAUST Workshop on Distributed Training in the Era of Large Models Nov 24 - 26, All day Auditorium between B4 & 5, L0, R0215 machine learning Distributed algorithms generative models ML Join leading researchers and innovators to explore how distributed training is reshaping the next generation of large-scale AI models.
