Events

Dec 3 - Dec 10, 2023

• 

  Nonlinear stability of splitting methods for Cahn-Hilliard equations

  Prof. Tao Tang's personal website

  Dec 4, 15:30 - 17:00

  B3 L5 R5220

  nonlinear stability splitting methods Cahn-Hilliard equations

  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.

Nov 26 - Dec 10, 2023

• 

  Splitting methods: merits and pitfalls

  Prof. Alexander Ostermann

  Dec 3, 16:00 - 17:00

  B2 L5 R5220

  splitting methods numerical integration computational efficiency pitfalls

  Coffee Time: 15:30 - 16:00. Splitting methods are a well-established tool for numerically integrating time-dependent partial differential equations. These methods split the vector field into disjoint components, which are integrated separately using an appropriate time step. The individual flows are then combined to obtain the desired numerical approximation.
• 

  High speed BLDC motor control method

  Prof. Marcin Baszynski

  Dec 3, 12:00 - 13:00

  B9 L2 H2

  power electronics

  This talk presents a method for obtaining good accuracy of the measured rotational speed and discusses the control algorithms and modulation technique of the high-speed BLDC motor.

Nov 26 - Dec 3, 2023

• 

  Resilient Cyber-Physical and Embedded Systems - Or how to cheat to get to n=f+1

  Prof. Marcus Völp, Head of the CritiX lab, the Interdisciplinary Centre for Security, Reliability and Trust (SnT), the University of Luxembourg.

  Nov 30, 15:30 - 16:30

  B5 L5 R5209

  ICT cyber-physical systems

  Our society keeps entrusting ICT systems with high value cyber-only assets, such as our most sensitive data, finances, etc. However, when it comes to cyber-physical systems and their ability to act in and with the physical world, lifes are at risk and require rigorous protection against accidental faults and cyberattacks.
• 

  Binary Diffractive Optical Elements for structured light applications

  Redha Al Ibrahim, Postdoctoral Research Fellow, Electrical and Computer Engineering

  Nov 30, 14:00 - 15:00

  B2 L5 R5209

  Light can be controlled through different degrees of freedom. An optical field is described through frequency, amplitude, phase, polarization, and wave-front structure. Many applications have been explored using these degrees of freedom, and some have great importance in our daily life.
• 

  Discretization and Optimization in Applied Geometry

  Nov 30, 12:00 - 13:00

  B9 L2 H2

  Many problems in applied geometry amount to the solution of a typically nonlinear partial differential equation. We will discuss why it may not be a good idea to discretize the equation, but to take the viewpoint of discrete differential geometry and discretize the theory.
• 

  Broadband Wireless Communication Using Free-space Optics and Radio Frequency

  Ming-Cheng Tsai, Ph.D. (former), Electrical and Computer Engineering

  Nov 29, 16:30 - 18:30

  B1 L2 R2202

  In the first part of this thesis, we have discussed the Cram ́er-Rao lower bound (CRLB) to evaluate the performance of beam tracking for a joint beam tracking and symbol detection scheme in deep-space optical communications.
• 

  Symmetry and Beyond

  Prof. Jiping Zhang

  Nov 29, 15:00 - 16:00

  B3 L5 R5220

  symmetry groups symmetric polynomials monstrous moonshine

  A fascination with symmetric forms seems to be an innate feature of human perception and for millennia it has influenced art and natural philosophy. The concept of symmetry is one of the very few on which mathematicians and physicists agree, namely that Symmetry ≡ Groups. We describe some special symmetries and related problems including symmetric polynomials and monstrous moonshine.
• 

  Basic Algebraic Structures

  Prof. Efim Zelmanov

  Nov 29, 14:00 - 15:00

  B3 L5 R5220

  Structures Galois

  We will give an overview of the development of Abstract Algebra from Galois to our time. The talk will be accessible to general audience with basic mathematical background.
• 

  Numerical approximation of PDEs on complex geometries: fluid-structure interaction problems and virtual element methods

  Fabio Credali, Ph.D. Student, Applied Mathematics and Computational Sciences

  Nov 28, 16:30 - 18:30

  KAUST

  The studies in numerical approximation of partial differential equations are characterized by the necessity of managing complex geometries and their discretization. We focus our attention on two different fields where complex geometries are very common: the mathematical modeling of fluid-structure interaction problems and the family of virtual element methods.
• 

  Derivative-Free Global Minimization: Relaxation, Monte Carlo and Sampling

  Diogo Gomes, Program Chair, Applied Mathematics and Computational Sciences

  Nov 27, 11:30 - 12:30

  B9 L2 H2 H2

  minimization Gradient flows Monte Carlo Monte Carlo Methodology

  We develop a derivative-free global minimization algorithm that is based on a gradient flow of a relaxed functional. We combine relaxation ideas, Monte Carlo methods, and resampling techniques with advanced error estimates. Compared with well-established algorithms, the proposed algorithm has a high success rate in a broad class of functions, including convex, non-convex, and non-smooth functions, while keeping the number of evaluations of the objective function small.
• 

  KAUST Research Conference on 4th 6G Summit: Super Connect the Connected - Connect the Unconnected

  Mohamed-Slim Alouini, Al-Khawarzmi Distinguished Professor, Electrical and Computer Engineering

  Nov 27, 08:00 - Nov 29, 16:30

  B18 L4 Fellowship Hall

  The Internet and Communication Technology (ICT) have undeniably revolutionized various aspects of human life. As the standardization of the fifth generation (5G) of wireless communication systems (WCSs) has been completed, 6G is expected to be the next focus in wireless communication and networking and aims to provide new superior communication services to meet the future hyper-connectivity demands in the 2030s. With this background, this Summit aims to go over the recently proposed solutions not only to connect the unconnected/under-connected but also to super-connect the connected.

Nov 19 - Dec 3, 2023

• 

  Semiconductor Epitaxy for Micro-LEDs and Novel Lasers

  Kazuhiro Ohkawa, Professor, Electrical and Computer Engineering

  Nov 26, 12:00 - 13:00

  B9 L2 H2

  semiconductor laser

  InGaN-based monolithic RGB LED arrays would be the key to producing micro-LED displays. The micro-LED displays will reduce the frequency of battery charging for mobiles and make head-mount displays thinner and lighter weight. It will become a game changer.
• 

  Analysis and Design of Linear Classifiers for High-Dimensional, Small Sample Size Data Using Asymptotic Random Matrix Theory

  Lama Burhan Niyazi, Ph.D. (former), Electrical and Computer Engineering

  Nov 26, 11:30 - 13:30

  B1 L3 R3119

  Due to a variety of potential barriers to sample acquisition, many of the datasets encountered in important classification applications, ranging from tumor identification to facial recognition, are characterized by small samples of high-dimensional data. In such situations, linear classifiers are popular as they have less risk of overfitting while being faster and more interpretable than non-linear classifiers. They are also easier to understand and implement for the inexperienced practitioner.

Nov 19 - Nov 26, 2023

• 

  FADO: A Federated Learning Attack and Defense Orchestrator

  Nuno Neves, Professor at the Department of Computer Science, Faculty of Sciences, the University of Lisboa (FCUL), Portugal.

  Nov 23, 15:30 - 16:30

  B5 L5 R5209

  Federated learning machine learning

  Federated Learning (FL) is a distributed machine learning approach that allows multiple parties to train a model collaboratively without sharing sensitive data.
• 

  Efficient Inference for Joint Models of Multivariate Longitudinal and Survival Data Using INLAjoint

  Denis Rustand, Postdoctoral Research Fellow, Statistics

  Nov 23, 12:00 - 13:00

  B9 L2 H2

  Clinical research often requires the simultaneous study of longitudinal repeated measurements and time-to-event (i.e., survival) data. Joint models, which can combine these two types of data, are invaluable tools in this context.
• 

  Natural Language Models For Unnatural Languages

  Wamiq Para, Ph.D. Student, Computer Science

  Nov 20, 14:00 - 16:00

  B1 L2 R2202

  Generative models for language generation, particularly based on transformers have shown remarkable performance in domains dealing with language.
• 

  Multi-agent higher-order learning vs Nash equilibrium

  Jeff Shamma

  Nov 20, 12:00 - 13:00

  B5 L5 R5209

  The framework of multi-agent learning explores the dynamics of how individual agent strategies evolve in response to the evolving strategies of other agents. Of particular interest is whether or not agent strategies converge to well-known solution concepts such as Nash Equilibrium (NE).
• 

  Inferring effects of mutations from genomic evolutionary history

  Dr. Muhammad Saqib Sohail, Hong Kong University of Science and Technology

  Nov 20, 11:30 - 12:30

  B1 L3 R3119

  One of the fundamental problems in population genetics and molecular evolution is to understand the drivers of genetic change in a population: which mutations affect the ability of an organism to survive, reproduce, and pass its genes to the next generation, while which mutations are mere "passengers" that do not affect this ability? In principle, the evolutionary history of a population contains information of the effects of mutations (deleterious, beneficial or neutral) occurring in the population.
• 

  Improving Interpretation Faithfulness for Transformers

  Di Wang, Assistant Professor, Computer Science

  Nov 20, 11:30 - 12:30

  B9 L2 H2 H2

  transformers nlp interpretation faithfulness

  Currently, attention mechanism becomes a standard fixture in most state-of-the-art NLP, Vision and GNN models, not only due to outstanding performance it could gain, but also due to plausible innate explanation for the behaviors of neural architectures it provides, which is notoriously difficult to analyze. However, recent studies show that attention is unstable against randomness and perturbations during training or testing, such as random seeds and slight perturbation of input or embedding vectors, which impedes it from becoming a faithful explanation tool. Thus, a natural question is whether we can find some substitute of the current attention which is more stable and could keep the most important characteristics on explanation and prediction of attention.

Nov 12 - Nov 26, 2023

• 

  Future Electronics Beyond the FinFET and GAA-FETs

  Uttam Kumar Das, Ph.D. Student, Electrical and Computer Engineering

  Nov 19, 16:00 - 18:00

  B9 L2 H2322

  Quantum theory and relativity have shown the solid path for solid-state computation in the early 20th century. Since then, many theoretical breakthroughs accompanied by experimental discoveries have ultimately led us to this modern-day electronic society.
• 

  Interface engineering for GaN HEMTs

  Chuanju Wang, Ph.D. Student, Electrical and Computer Engineering

  Nov 19, 12:00 - 13:00

  B9 L2 H2

  semiconductor

  The junctions formed between the metal contact and semiconductors, gate dielectrics are crucial components of GaN based electronics and optoelectronics.

Nov 12 - Nov 19, 2023

• 

  Multiscale Learning of High-dimensional Cell Fate

  Prof. Qing Nie, Department of Mathematics, Department of Developmental and Cell Biology, NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine

  Nov 16, 15:30 - 17:00

  B9 L4 R4225

  Abstract Cells make fate decisions in response to dynamic environments, and multicellular structures emerge from multiscale interplays among cells and genes in space and time. The recent single-cell genomics technology provides an unprecedented opportunity to profile cells for all their genes. While those measurements provide high-dimensional gene expression profiles for all cells, it requires fixing individual cells that lose many important spatiotemporal information. Is it possible to infer temporal relationships among cells from single or multiple snapshots? How to recover spatial
• 

  How do periodic structures affect nonlinear waves?

  David Ketcheson, Professor, Applied Mathematics and Computational Sciences

  Nov 16, 12:00 - 13:00

  B9 L2 H2

  We are all familiar with the tendency of water waves to break in shallow water, for instance at the beach. Indeed, breaking is a universal behavior of solutions to first-order nonlinear hyperbolic PDEs, and manifests itself in phenomena ranging from traffic jams to shock waves.
• 

  Tensor-train Methods for Partial Differential Equations and its application to a Neutron Transport Problem

  Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering

  Nov 14, 15:30 - 17:00

  B9 L4 R4225

  Partial Differential Equations

  Tensor network techniques are known for their ability to approximate low-rank structures and beat the curse of dimensionality. They are also increasingly acknowledged as fundamental mathematical tools for efficiently solving high-dimensional Partial Differential Equations (PDEs). In this talk, we present a novel method that incorporates the Tensor Train (TT) and Quantized Tensor Train (QTT) formats for the computational resolution of time-independent Boltzmann Neutron Transport equations (BNTEs) in Cartesian coordinates.
• 

  The Partition of Unity Finite Element Method for the Schrödinger Equation

  Francesca Gardini, Associate Professor, Dipartimento di Matematica, Università di Pavia, Italy

  Nov 14, 14:30 - 15:30

  B9 L4 R4225

  A Schrödinger equation for the system’s wavefunctions in a parallelepiped unit cell subject to Bloch-periodic boundary conditions must be solved repeatedly in quantum mechanical computations to derive the materials’ properties.
• 

  Efficient Algorithms for Vision and Language Learning

  Jun Chen , Ph.D. Student, Computer Science

  Nov 14, 12:15 - 14:15

  B1 L3 R3426

  The development of advanced vision-language models necessitates considerable resources, both in terms of computation and data. There is growing interest in training these models efficiently and effectively and leveraging them for various downstream tasks. This dissertation presents several contributions aimed at improving both learning and data efficiency in vision-language learning, and how to leverage them into downstream tasks.
• 

  Experimental Design Statistical Workshop

  Hernando Ombao, Professor, Statistics

  Nov 14, 09:00 - Nov 15, 17:00

  B1 L4 R4102

  This workshop will cover the statistical essentials to designing experiments including power analysis, sample size calculation, regression, and variance analysis. A statistically sound experimental design is essential in applying for research grants. Detailed syllabi will be sent to those who register. Limited seats. Sign up now!
• 

  The SCION Research and Education Network

  Adrian Perrig, Professor, the Department of Computer Science, ETH Zürich, Switzerland

  Nov 13, 11:30 - 12:30

  B9 L2 H2 H2

  cybersecurity internet architecture

  Imagining a new Internet architecture enables us to explore new networking concepts without the constraints imposed by the current Infrastructure. In this presentation, we invite you to join us on our 14-year-long expedition of creating the SCION next-generation secure Internet architecture.

Nov 5 - Nov 19, 2023

• 

  Family of Mean-Mixtures of Multivariate Normal Distributions

  Prof. Narayanaswamy Balakrishnan, Department of Mathematics and Statistics, McMaster University

  Nov 12, 15:30 - 16:30

  B1 L4 R4102

  In this talk, I will describe the family of mean-mixtures of multivariate normal distributions and establish many of its properties, stochastic representations, moments, distributional shape characteristics, etc.
• 

  Learning Sequential Modeling Algorithms for Motion Forecasting, Reinforcement Learning, and Vision-Language Understanding

  Deyao Zhu, Ph.D. Student, Computer Science

  Nov 12, 15:00 - 16:30

  B1 L4 R4214

  Sequential modeling algorithms have made significant strides in a variety of domains, facilitating intelligent decision-making and planning in complex scenarios. This dissertation explores the potential and limitations of these algorithms, unveiling novel approaches to enhance their performance across diverse fields, from autonomous driving and trajectory forecasting to reinforcement learning and vision language understanding.
• 

  Models and Inference for Non-Gaussian Random Vectors and Fields

  Sagnik Mondal, Ph.D. Student, Statistics

  Nov 12, 12:30 - 14:30

  B5 L5 R5209

  The multivariate Gaussian distribution is widely used in many statistical applications due to its appealing features. However, real-world data often violate its assumptions, showing skewness and/or tail-thickness.
• 

  Mathematical Control Theory in Aeronautical Engineering: Boosted Maneuverability in Stall and Unconventional Stability of Insect Flight

  Haithem Taha, Visiting Professor, Computer, Electrical and Mathematical Sciences and Engineering, KAUST

  Nov 12, 12:00 - 13:00

  B9 L2 H2

  Aeronautical Sciences

  The great Russian Mathematician Vladimir Arnold once said, “Mathematics is the part of physics where experiments are cheap”. In this talk, I will present two modern applications in aeronautical engineering where simple, but rigorous, mathematical control theory led to game-changing results exploiting nonlinearities and time-variation rather than obviating them.

Nov 5 - Nov 12, 2023

• 

  Security and privacy in centralized and decentralized machine learning

  Josep Domingo-Ferrer, Distinguished Professor, Computer Science and an ICREA-Acadèmia, Research Professor, Universitat Rovira i Virgili, Tarragona, Catalonia.

  Nov 9, 15:30 - 16:30

  B4 L5 R5209

  cybersecurity machine learning Security and Privacy attacks

  Machine learning (ML) is vulnerable to security and privacy attacks. Whereas security attacks aim at preventing model convergence or forcing convergence to wrong models, privacy attacks attempt to disclose the data used to train the model.
• 

  Coded Super-MAC

  Mohammed Zafar Ali Khan

  Nov 8, 10:00 - 11:00

  B1 L3 R3426

  In this talk, we present a solution to the challenge of simultaneously enhancing the reliability and throughput of multiple radio access technologies (multi-RAT).
• 

  A Brief Overview of Arabic NLP

  Prof. Sakhar B. Alkhereyf

  Nov 7, 15:30 - 17:00

  B5 L5 R5209

  nlp Arabic natural language processing

  Arabic, being one of the six official languages of the United Nations and the sixth most commonly spoken language across the globe, holds a significant stance in the linguistic landscape. The diglossic nature of Arabic, where Classical Arabic (CA), Modern Standard Arabic (MSA), and various dialects coexist, coupled with its complex morphological structure, presents a unique set of challenges and opportunities for the domain of Natural Language Processing (NLP).
• 

  Interpretable Learning on Heterogeneous Graphs

  Qiang Yang, Ph.D. Student, Computer Science

  Nov 7, 15:00 - 17:00

  B3 L5 R5220

  Graph Representation Learning has gained substantial attention in recent years within the field of data mining. This interest has been driven by the prevalence of data organized as graphs, such as social networks and academic graphs, which encompass various types of nodes and edges-forming heterogeneous graphs.
• 

  Adaptive Optimization Algorithms for Machine Learning

  Slavomir Hanzely, Ph.D. Student, Applied Mathematics and Computational Sciences

  Nov 7, 10:00 - 11:00

  B1 L4 R4214

  artificial intelligence machine learning

  Machine learning assumes a pivotal role in our data-driven world. The increasing scale of models and datasets necessitates quick and reliable algorithms for model training. This dissertation investigates adaptivity in machine learning optimizers.
• 

  The Prospect of Generative Language Processing

  Prof. Muhammad Abdul-Mageed

  Nov 6, 11:30 - 12:30

  B9 L2 H2 H2

  nlp generative language processing artificial intelligence

  In the evolving landscape of artificial intelligence, generative models are revolutionizing our interface with computational systems and reshaping societal paradigms. For example, foundation models have the potential to transform content creation across languages, offering discovery and productivity pathways for humans to engage with one another and their environment. This talk sketches the core methodologies propelling this groundbreaking progress, charting a grand vision for generative natural language processing.
• 

  The KAUST 2023 Workshop on Statistics

  Nov 6, 09:00 - Nov 9, 17:00

  B18 R4203

  statistics data science modeling big data sustainability health environment

  The workshop will feature the latest research on statistical methods and modeling to address real-world challenges in health, environment, and sustainability.

Oct 29 - Nov 12, 2023

• 

  Atomic Layer Deposition Reaction Parameters Influence on ZnO's Electrical Properties on Cotton Fabric for Textile Electronics

  Huda Badghaish, Ph.D. Student, Electrical and Computer Engineering

  Nov 5, 16:00 - 18:00

  KAUST

  Textile electronics is a newly emerging field that is gaining the interest of researchers due to its wide range of applications and prospects. Despite the variety of materials and methods used to fabricate textile electronic devices, there is a lack of focus and direction needed for the rapid advancement of this field.
• 

  Smart Multifunctional Electronic Devices for IoT and Healthcare Applications

  Nazek El-Atab, Assistant Professor, Electrical and Computer Engineering

  Nov 5, 12:00 - 13:00

  B9 L2 H2

  CMOS electronics Multifunctional Electronic Devices

  This talk addresses these questions through two main projects: 1) Smart and multifunctional memory devices (MEMSOR) that can sense and compute, and 2) Wearable Octopus-skin-inspired 3D-printed biopatches for electrophysiological signal measurement.

Oct 29 - Nov 5, 2023

• 

  Scheduling tasks in energy harvesting IoT

  Stefano Chessa, Professor, Department of Computer Science, the University of Pisa, Italy.

  Nov 2, 15:30 - 16:30

  B4 L5 R5209

  IoT energy harvesting cybersecurity

  Internet of Things (IoT) applications can exploit energy harvesting systems to guarantee virtually uninterrupted operations. However, the use of energy harvesting poses issues concerning the optimization of the utility of the application while guaranteeing energy neutrality of the devices.
• 

  Free Boundary Problems in Science and Engineering

  Rafayel Teymurazyan, Research Scientist, Applied Mathematics and Computational Sciences

  Nov 2, 12:00 - 13:00

  B9 L2 H2

  Free boundary problems arise naturally in a range of mathematical models that describe physical, biological or financial phenomena, such as the melting of ice into water, the dynamics of a population or the behavior of stock markets, to mention just a few.
• 

  Spatial and Spatio-temporal Statistical Methods for Environment and Public Health Applications

  Andre Victor Ribeiro Amaral , Ph.D. Student, Statistics

  Nov 2, 11:45 - 14:30

  B9 L4 R4225

  This thesis proposes statistical spatial and spatial-temporal methods for addressing real-world challenges within the public health and environmental domains.
• 

  Scalable Spatial Data Science for Social Scientists

  Prof. Amr Magdy

  Oct 31, 16:30 - 17:30

  B4 L5 R5220

  data science Spatial data

  The proliferation of spatial data from modern and increasingly prevalent technologies has resulted in large datasets, ripe for extracting insightful knowledge that can drive many applications.
• 

  Quantum Computing with Xanadu

  Catalina Albornoz, Quantum Community Manager at Xanadu

  Oct 31, 15:30 - 17:00

  KAUST

  quantum computing PennyLane photonic architecture

  Xanadu is a Canadian quantum computing company with the mission to build quantum computers that are useful and available to people everywhere. Xanadu is one of the world’s leading quantum hardware and software companies and also leads the development of PennyLane, an open-source software library for quantum computing and application development.
• 

  Stochastic Optimal Control with Exercise Rate Optimization and Markovian Projections: Pricing American Options and Importance Sampling Applications

  Raul Tempone, Professor, Applied Mathematics and Computational Sciences

  Oct 31, 15:30 - 17:00

  B5 L5 R5209

  sampling Markovian projection

  This talk begins with the problem of pricing American basket options in a multivariate setting. In high dimensions, nonlinear PDE methods for solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation become expensive due to the curse of dimensionality.
• 

  Memory Forensics 2.0

  Davide Balzarotti, Professor and head of the Digital Security department, EURECOM, France.

  Oct 30, 11:30 - 12:30

  B9 L2 H2 H2

  cybersecurity

  The risk of security breaches is now higher than ever, and attackers routinely break into corporate networks, government services, and even critical infrastructures. As a result, it is not a matter of `if' a system will be compromised, but only a matter of `when' -- thus making the way we handle computer incidents and investigations of paramount importance.

Oct 22 - Nov 5, 2023

• 

  Pseudo-CMOS Monolithic Integrated Circuits based on Ultrawide Bandgap Semiconductors

  Dhanu Chettri, Ph.D. Student, Electrical and Computer Engineering

  Oct 29, 12:00 - 13:00

  B9 L2 H2

  ultra-wideband

  This seminar will articulate the growth, and fabrication methodologies employed, discuss the device characterization under high-temperature conditions, and extrapolate on the far-reaching implications of these advancements for the realm of electronics designed to operate under extreme environmental conditions.