Events

Jan 17 - Jan 31, 2021

• 

  Biosensors challenges and opportunities

  Khaled Salama, Professor, Electrical and Computer Engineering

  Jan 24, 12:00 - 13:00

  KAUST

  Biosensors challenges opportunities

  No summary is available.
• 

  Building Latency-Critical Datacenter Systems

  Marios Kogias, Researcher, Computer Science, Microsoft Research, Cambridge

  Jan 24, 10:00 - 11:00

  KAUST

  In the first part of the talk, I will focus on ZygOS[SOSP 2017], a system optimized for μs-scale, in-memory computing on multicore servers. ZygOS implements a work-conserving scheduler within a specialized operating system designed for high request rates and a large number of network connections. ZygOS revealed the challenges associated with serving remote procedure calls (RPCs) on top of a byte-stream oriented protocol, such as TCP. In the second part of the talk, I will present R2P2[ATC 2019]. R2P2 is a transport protocol specifically designed for datacenter RPCs, that exposes the RPC abstraction to the endpoints and the network, making RPCs first-class datacenter citizens. R2P2 enables pushing functionality, such as scheduling, fault-tolerance, and tail-tolerance, inside the transport protocol, making it application-agnostic. I will show how using R2P2 allowed us to offload RPC scheduling to programmable switches that can schedule requests directly on individual cores.

Jan 17 - Jan 24, 2021

• 

  Elliptic PDEs: Regularity under minimal assumptions - Session 2

  Giuseppe Di Fazio,Professor of Mathematics at the University of Catania, Italy

  Jan 21, 10:00 - 13:00

  KAUST

  Elliptic PDE are ubiquitous both in Mathematics and in the applications of Mathematics. The regularity of the generalized solutions is a very important issue that it is necessary to handle in proper way if one want to obtain useful information. The goal of my lectures is to introduce the audience to the topic of regularity for elliptic PDE under assumptions on the coefficients that are of minimal requirements.
• 

  Elliptic PDEs: Regularity under minimal assumptions - Session 1

  Giuseppe Di Fazio, Professor of Mathematics at the University of Catania, Italy

  Jan 19, 10:00 - 13:00

  KAUST

  Elliptic PDE are ubiquitous both in Mathematics and in the applications of Mathematics. The regularity of the generalized solutions is a very important issue that it is necessary to handle in proper way if one want to obtain useful information. The goal of my lectures is to introduce the audience to the topic of regularity for elliptic PDE under assumptions on the coefficients that are of minimal requirements.

Jan 10 - Jan 24, 2021

• 

  Building Scalable Network Stacks for Modern Applications

  Ahmed Saeed, Postdoctoral Associate, Computer Science, MIT

  Jan 17, 15:00 - 16:00

  KAUST

  This talk covers two research directions that address the shortcomings of existing network stacks. The first is on scalable software network stacks, solving problems in different components of operating systems and applications to allow a single server to handle data flows for tens of thousands of clients. The second is on Wide Area Network (WAN) congestion control, focusing on network-assisted congestion control schemes, where end-to-end solutions fail. The talk will conclude with a discussion of plans for future research in this area.

Jan 3 - Jan 17, 2021

• 

  Overcoming the curse of dimensionality: from nonlinear Monte Carlo to deep learning

  Arnulf Jentzen, Professor, Applied Mathematics Münster: Institute for Analysis and Numerics, University of Münster

  Jan 10, 14:00 - 15:00

  KAUST

  nonlinear Deep learning monte carlo algorithms

  In this talk we prove that suitable deep neural network approximations do indeed overcome the curse of dimensionality in the case of a general class of semilinear parabolic PDEs and we thereby prove, for the first time, that a general semilinear parabolic PDE can be solved approximatively without the curse of dimensionality.

Jan 3 - Jan 10, 2021

• 

  Mean Field Games: Numerical Methods and Applications

  Mathieu Laurière, Postdoc, Department of Operations Research and Financial Engineering, Princeton University

  Jan 5, 15:00 - 16:00

  KAUST

  mean-field games numerical methods

  In this talk, several numerical methods will be presented and illustrated on examples. Borrowing tools from stochastic analysis, optimization, partial differential equations and machine learning, these methods enable us to solve mean field games with possibly complex sources of noise or high dimensional state variables.

Dec 20 - Dec 27, 2020

• 

  What’s the Story with UAV Cellular Communications?

  Prof. Giovanni Geraci, Assistant Professor, University Pompeu Fabra (UPF) in Barcelona, Spain

  Dec 22, 16:00 - 17:15

  KAUST

  UV Communications

  What will it take for UAVs—and the associated ecosystem—to take off? Arguably, ubiquitous high-capacity links paired with hyper-reliable command and control all along. And indeed, meeting these aspirations may entail a full-blown mobile network support. While the understanding of UAV cellular communications has been advancing, many fundamental challenges remain to be addressed, with new applications demanding original solutions. In this talk, we blend academic and industrial views, navigating from 4G to 6G UAV use cases, requirements, and enabling technologies

Dec 13 - Dec 20, 2020

• 

  Wireless Communications using Light - not all wireless is at RF

  Prof. Steve Hranilovic, Associate Dean, McMaster University, Canada and Dr. Imran Shafique Ansari, Assistant Professor, University of Glasgow, United Kingdom

  Dec 15, 16:00 - 17:15

  KAUST

  FSO systems

  Due to the increasing scarcity of RF spectrum and growing interference due to multiple users, deploying next generation high-speed wireless networks is becoming increasingly difficult. The use of unlicensed optical bands for wireless communications has been heralded as an exciting development for future broadband access for indoor, underwater and space communication links.

Dec 6 - Dec 13, 2020

• 

  Geospatial Data Science for Public Health Surveillance - Graduate Seminar

  Dec 10, 12:00 - 13:00

  KAUST

  Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. In this talk, I will give an overview of my research which focuses on the development of geospatial methods and interactive visualization applications for health surveillance. I will present disease risk models where environmental, demographic and climatic data are used to predict the risk and identify targets for intervention of lymphatic filariasis in sub-Saharan Africa, and leptospirosis in a Brazilian urban slum. I will also show the R packages epiflows for risk assessment of travel-related spread of disease, and SpatialEpiApp for disease mapping and the detection of clusters. Finally, I will describe my future research and how it can inform better surveillance and improve population health globally.

Nov 29 - Dec 13, 2020

• 

  Redesigning CMOS Electronics: What, Why and How?

  Dec 6, 12:00 - 13:00

  KAUST

  Redesigning CMOS electronics

  A little more than half of the world’s population enjoy benefits of information technology which is enabled by complementary metal oxide semiconductor (CMOS) electronics. Going forward, we will enjoy further augmentation of quality of life through integrated CMOS electronic systems consisting of logic, memory, communication devices, energy storage and harvester, power management units, sensors and actuators. Their main attributes will include but not limited to high performance and storage capacity for data management; seamless connectivity; energy efficiency; hyper-scale integration density; appropriate functionalities based on their applications and operational environment; reliability and safety; and finally affordability and simplicity to expand their user base to include those who do not have any access to them today. Even using last fifty years’ wealth of knowledge and experience, such integrated electronic system development and deployment is a monumental engineering challenge. From that perspective, redesigning CMOS electronics might seem to be an overly ambitious goal specially, if that means transformation of such physically rigid complex electronic systems into a fully flexible one. To address this intriguing challenge, we have developed a unique coin like architecture based soft singular platform, which can be used as the building block of standalone fully flexible CMOS electronic system with all the aforementioned characteristics. We have devised an effective heterogeneous integration strategy based on mature and reliable CMOS technology only to integrate hybrid materials and diverse set of devices for multi-disciplinary applications. These will be the focus of this talk.

Nov 29 - Dec 6, 2020

• 

  Mini Courses by Prof Piermarco Cannarsa - Session 2

  Professor Piermarco Cannarsa, Mathematical Analysis at the University of Rome Tor Vergata, Italy

  Dec 3, 15:00 - 18:00

  KAUST

  The theory of Mean Field Games (MFG) has been developed in the last two decades by economists, engineers, and mathematicians in order to study decision making in very large populations of “small" interacting agents. This short course will be focused on deterministic MFG, which are associated with a first order PDE system. We will address the problem assuming that agents are subject to state constraints, when classical PDE techniques are of little help. First, we will show how to prove the existence of solutions by the so-called Lagrangian approach, which interprets equilibria as certain measures on the space of paths that each agent can choose. Then, we will address regularity issues for such generalized solutions, deriving point-wise properties that allow to recover the typical MFG system. Finally, we will study the asymptotic behavior of solutions to the constrained MFG system as time goes to infinity, borrowing ideas from weak KAM theory.
• 

  Modelling and Simulation of Biological Systems - 2020-12-03

  Gabriel Wittum, Professor, Applied Mathematics and Computational Sciences

  Dec 3, 12:00 - 13:00

  KAUST

  Biological systems are distinguished by their enormous complexity and variability. That is why mathematical modeling and computational simulation of those systems is very difficult, in particular thinking of detailed models which are based on first principles. The difficulties start with geometric modeling which needs to extract basic structures from highly complex and variable phenotypes, on the other hand also has to take the statistic variability into account. Moreover, the models of the processes running on these geometries are not yet well established, since these are equally complex and often couple many scales in space and time. Thus, simulating such systems always means to put the whole frame to test, from modelling to the numerical methods and software tools used for simulation. These need to be advanced in connection with validating simulation results by comparing them to experiments.
• 

  Conquering the Terahertz Band: From Theory to Practice

  Prof. Josep M. Jornet, Northeastern University, in Boston, MA

  Dec 1, 15:45 - 17:15

  KAUST

  THz sensing THz signal source

  The need for higher data-rates and more ubiquitous connectivity for an ever-increasing number of wirelessly connected devices motivates the exploration of uncharted spectral bands. In this context, Terahertz (THz)-band (0.1–10 THz) communication is envisioned as a key wireless technology of the next decade. The very large bandwidth available at THz frequencies (tens to hundreds of consecutive GHz) can alleviate the spectrum scarcity problem while enabling wireless Terabit-per-second (Tb/s) links in personal and local area networks, backhaul for urban and rural areas, and even space networks.
• 

  Mean Field Games with State Constraints - Session 1

  Professor Piermarco Cannarsa, Mathematical Analysis at the University of Rome Tor Vergata, Italy

  Dec 1, 15:00 - 18:00

  KAUST

  The theory of Mean Field Games (MFG) has been developed in the last two decades by economists, engineers, and mathematicians in order to study decision making in very large populations of “small" interacting agents. This short course will be focused on deterministic MFG, which are associated with a first order PDE system. We will address the problem assuming that agents are subject to state constraints, when classical PDE techniques are of little help. First, we will show how to prove the existence of solutions by the so-called Lagrangian approach, which interprets equilibria as certain measures on the space of paths that each agent can choose. Then, we will address regularity issues for such generalized solutions, deriving point-wise properties that allow to recover the typical MFG system. Finally, we will study the asymptotic behavior of solutions to the constrained MFG system as time goes to infinity, borrowing ideas from weak KAM theory.
• 

  Transparent and Robust Causal Inference in Data Science

  Carlos Cinelli, Ph.D. candidate, Department of Statistics, UCLA

  Nov 30, 16:30 - 17:30

  KAUST

  statistical inference data science

  The past few decades have witnessed rapid and unprecedented theoretical progress in the science of causal inference, ranging from the “credibility revolution” with the popularization of quasi-experimental designs, to the development of a complete solution to non-parametric identification with causal graphical models. Most of these theoretical progress, however, relies on strong, exact assumptions, such as the absence of unobserved common causes, or the absence of certain direct effects. Unfortunately, more often than not these assumptions are very hard to defend in practice. This leads to two undesirable consequences for applied quantitative work in the data-intensive sciences: (i) important research questions may be neglected, simply because they do not exactly match the requirements of current methods; or, (ii) researchers may succumb to making the required “identification assumptions” simply to justify the use of available methods, but not because these assumptions are truly believed (or understood). In this talk, I will discuss new theories, methods, and software for permitting causal inferences under more flexible and realistic settings. These tools empower scientists, and policymakers to both examine the sensitivity of causal inferences to violations of its underlying assumptions, and also to draw robust and trustworthy conclusions from settings in which traditional methods fail.
• 

  Enabling Accurate and Efficient Simulation in Visual Computing - Public Colloquium

  Dominik L. Michels, Associate Professor, Computer Science

  Nov 30, 14:30 - 16:00

  KAUST

  visual computing

  The overarching goal of Prof. Michels' Computational Sciences Group within KAUST's Visual Computing Center is enabling accurate and efficient simulations for applications in Scientific and Visual Computing. Towards this goal, the group develops new principled computational methods based on solid theoretical foundations. This talk covers a selection of previous and current work presenting a broad spectrum of research highlights ranging from simulating stiff phenomena such as the dynamics of fibers and textiles, over liquids containing magnetic particles, to the development of complex ecosystems and weather phenomena. Moreover, connection points to the growing field of machine learning are addressed and an outlook is provided with respect to selected technology transfer activities.
• 

  Research at the Image and Video Understanding Lab (IVUL) - Graduate Seminar - CS

  Bernard Ghanem, Professor, Electrical and Computer Engineering

  Nov 30, 12:00 - 13:00

  KAUST

  In this talk, I will give an overview of research done in the Image and Video Understanding Lab (IVUL) at KAUST. At IVUL, we work on topics that are important to the computer vision (CV) and machine learning (ML) communities, with emphasis on three research themes: Theme 1 (Video Understanding), Theme 2 (Visual Computing for Automated Navigation), Theme 3 (Fundamentals/Foundations).

Nov 22 - Dec 6, 2020

• 

  Aggregation-Diffusion PDEs: Gradient Flows, Long Time asymptotics and bifurcations - Session 3

  José A. Carrillo, Professor, Applied Mathematics at The Queen’s College, University of Oxford, UK

  Nov 29, 13:00 - 15:00

  KAUST

  The main goal of this mini course is to discuss the state-of-the-art in understanding the phenomena of long time asympotitcs and phase transitions for a range of nonlinear Fokker-Planck equations with linear and nonlinear diffusion. They appear as natural macroscopic PDE descriptions of the collective behavior of particles such as Cucker-Smale models for consensus, the Keller Segel model for chemotaxis, and the Kuramoto model for synchronization. We will discuss the existence of phase transitions in a variety of these models using the natural free energy of the system and their interpretation as natural gradient flow structure with respect to the Wasserstein distance in probability measures. We will discuss both theoretical aspects as well as numerical schemes and simulations keeping those properties at the discrete level.
• 

  Mobile Microrobotics

  Hussein Hussein, Postdoctoral Research Fellow, Electrical and Computer Engineering

  Nov 29, 12:00 - 13:00

  KAUST

  mobile Microrobotics

  The implementation of robotic solutions to accomplish automated tasks in industrial sectors has tremendously increased the human performance capacity and enhanced the cost, quality and delivery time for different tasks and products. Having already proven their utility at the macroscale, robots also show their usefulness when we approach the infinitely small dimensions, for applications such as inspection, cell manipulation, assembly, biopsy and drug delivery. The way to the microworld is not that simple; reducing the size of robots from macro scale to micro scale cannot be accomplished by merely miniaturizing the different parts of an existing robot. The variation in the scale of physical effects with the size scale and the difficulties of fabrication and assembly at the micro scale make the macro-solutions for actuation and sensing unsuitable for microdevices. Other actuation mechanisms with deformable structures and integrated sensing solutions are more efficient at microscale and compatible with microfabrication limitations. This talk focuses on different aspects related to mobile microrobots, including limitations and challenges, actuation mechanisms, power delivery, and current works in our team for the development of mobile microrobots.

Nov 22 - Nov 29, 2020

• 

  Aggregation-Diffusion PDEs: Gradient Flows, Long Time asymptotics and bifurcations - Session 2

  José A. Carrillo, Professor, Applied Mathematics at The Queen’s College, University of Oxford, UK

  Nov 26, 13:00 - 15:00

  KAUST

  The main goal of this mini course is to discuss the state-of-the-art in understanding the phenomena of long time asympotitcs and phase transitions for a range of nonlinear Fokker-Planck equations with linear and nonlinear diffusion. They appear as natural macroscopic PDE descriptions of the collective behavior of particles such as Cucker-Smale models for consensus, the Keller Segel model for chemotaxis, and the Kuramoto model for synchronization. We will discuss the existence of phase transitions in a variety of these models using the natural free energy of the system and their interpretation as natural gradient flow structure with respect to the Wasserstein distance in probability measures. We will discuss both theoretical aspects as well as numerical schemes and simulations keeping those properties at the discrete level.
• 

  The Tetracopter: A modular, self-similar flying robot

  Eric Feron, Professor, Electrical and Computer Engineering

  Nov 26, 12:00 - 13:00

  KAUST

  Modular robotics deals with robots that are an assemblage of smaller sized and often identical robots. The benefits of modular robots are many, chief among them being how easily they can be transported from one location to another. Moreover, their size can be adjusted according to the task at hand without requiring extensive redesign or specialization, therefore making them the object of significant research efforts.
• 

  Energy-Efficient Non-Orthogonal Multicast and Unicast Transmission of Cell-Free Massive MIMO Systems with SWIPT

  Prof. Minghua Xia, Sun Yat-sen University, China & Prof. Zilong Liu,University of Essex, United Kingdom

  Nov 24, 16:00 - 17:15

  KAUST

  SWIPT

  To suit massive connectivity of machine-type communications in smart cities, this talk discusses the energy-efficient resource allocation for layered-division multiplexing (LDM) based non-orthogonal multicast and unicast transmission in cell-free massive multiple-input multiple-output (MIMO) systems, where each user equipment (UE) performs wireless information and power transfer simultaneously. Non-orthogonal multiple access (NOMA) is an emerging paradigm for the enabling of massive connectivity in 5G networks and beyond.
• 

  Towards Accurate Biomedical Genomics Anywhere Anytime - Public Colloquium

  Xin Gao, Program Chair, Computer Science

  Nov 24, 14:00 - 15:30

  KAUST

  In this talk, I will first give an overview of the research activities in Structural and Functional Bioinformatics Group (http://sfb.kaust.edu.sa). I will then focus on our efforts on developing computational methods to tackle key open problems in Nanopore sequencing. In particular, I will introduce our recent works on developing a collection of computational methods to decode raw electrical current signal sequences into DNA sequences, to simulate raw signals of Nanopore, and to efficiently and accurately align electrical current signal sequences with DNA sequences. I will further introduce their applications in biomedicine and healthcare.
• 

  BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data

  Meini Tang, M.S. Student, Statistics

  Nov 24, 09:00 - 10:00

  KAUST

  Intrinsic connectivity networks (ICNs) refer to brain functional networks that are consistently found under various conditions, during tasks or at rest. Some studies demonstrated that while some stimuli do not impact intrinsic connectivity, other stimuli actually activate intrinsic connectivity through suppression, excitation, moderation or modification. Most analyses of fMRI data use ad-hoc methods to estimate the latent structure of ICNs. Modeling the effects on ICNs has also not been fully investigated. We propose a Bayesian Intrinsic Connectivity Network (BICNet) model, an extended Bayesian dynamic sparse latent factor model, to identify the ICNs and quantify task-related effects on the ICNs. BICNet has the following advantages: (1) It simultaneously identifies the individual and group-level ICNs; (2) It robustly identifies ICNs by jointly modeling rfMRI and tfMRI; (3) Compared to ICA-based methods, it can quantify the difference of ICN amplitudes across different states; (4) The sparsity of ICNs automatically performs feature selection, instead of ad-hoc thresholding. We apply BICNet to the rfMRI and language tfMRI data from the HCP and identify several ICNs related to distinct language processing functions.
• 

  Aggregation-Diffusion PDEs: Gradient Flows, Long Time asymptotics and bifurcations - Session 1

  José A. Carrillo, Professor, Applied Mathematics at The Queen’s College, University of Oxford, UK

  Nov 23, 13:00 - 15:00

  KAUST

  The main goal of this mini course is to discuss the state-of-the-art in understanding the phenomena of long time asympotitcs and phase transitions for a range of nonlinear Fokker-Planck equations with linear and nonlinear diffusion. They appear as natural macroscopic PDE descriptions of the collective behavior of particles such as Cucker-Smale models for consensus, the Keller Segel model for chemotaxis, and the Kuramoto model for synchronization. We will discuss the existence of phase transitions in a variety of these models using the natural free energy of the system and their interpretation as natural gradient flow structure with respect to the Wasserstein distance in probability measures. We will discuss both theoretical aspects as well as numerical schemes and simulations keeping those properties at the discrete level.
• 

  From a Virtual Red Sea to the Urban Scales of NEOM: A Decade of Progress Driven by Computational Sciences

  Ibrahim Hoteit, Professor, Earth Science and Engineering

  Nov 23, 12:00 - 13:00

  KAUST

  The talk will present our decade-long efforts to build an integrated data-driven modeling system to study and predict the circulation and climate of the Arabian Peninsula at all scales. Starting from a general description of the Virtual Red Sea Initiative at its achievements so far, I will then outline our ongoing research under the KAUST Centre of Excellence for NEOM to develop new tools to seamlessly project and study the environment at the urban scales of NEOM. I will in particular discuss the involved scientific opportunities and challenges in terms of computational Sciences, including our extreme computational requirements, and the handling, analysis and visualization of very large datasets.

Nov 15 - Nov 29, 2020

• 

  Efficient and Accurate Numerical Methods for Transient Electromagnetic Analysis - 2020

  Hakan Bagci, Associate Dean for Students, Computer, Electrical and Mathematical Sciences and Engineering

  Nov 22, 12:00 - 13:00

  KAUST

  Efficient numerical Methods Transient electromagnetic

  Electromagnetic devices and systems are at the heart of technological advances revolutionizing many fields of science and engineering including energy management, biomedical electronics, communications and computing, and even environmental monitoring and civil design. Many of these systems are electrically large, their frequency of operation has a wide dynamic range, their device components are geometrically intricate with dimensions varying by orders of magnitude, and finally their optimal design requires many repetitions of characterizations with different parameters.

Nov 15 - Nov 22, 2020

• 

  On Unbiased Estimation of the Score Function for a Class of Partially Observed Diffusions

  Nov 19, 12:00 - 13:00

  KAUST

  In this talk we consider the problem of estimating the score function (or gradient of the log-likelihood) associated to a class of partially observed diffusion processes, with discretely observed, fixed length, data and finite dimensional parameters. We construct an estimator that is unbiased with no time-discretization bias. Using a simple Girsanov change of measure method to represent the score function, our methodology can be used for a wide class of diffusion processes and requires only access to a time-discretization method such as Euler-Maruyama. Our approach is based upon a novel adaptation of the randomization schemes developed by Glynn and co-authors along with a new coupled Markov chain simulation scheme. The latter methodology is an original type of coupling of the coupled conditional particle filter. We prove that our estimator is unbiased and of finite variance. We then illustrate our methodology on several challenging statistical examples. This is a joint work with Jeremy Heng (ESSEC, Singapore) and Jeremie Houssineau (Warwick, UK)
• 

  Start your Research Journey at KAUST - Master and Ph.D. degrees in Applied Mathematics, Computer Science, Electrical Engineering and Statistics

  Aigars Ekers, Assistant Dean, Computer, Electrical and Mathematical Sciences and Engineering

  Nov 18, 16:00 - 17:00

  KAUST

  Did you know that courses are taught in English at KAUST? Did you know that the faculty and students are from more than 100 countries? Did you know that you will be fully funded when studying at KAUST? What you will learn from this webinar: Life at KAUST: What are KAUST and CEMSE? Degrees and Academic Programs Research Areas and Lab Facilities Eligibility and Admission Requirements KAUST Fellowship: Benefits of studying at KAUST How to Apply?
• 

  Federated Learning of a Mixture of Global and Local Models

  Filip Hanzely, Ph.D., Applied Mathematics and Computational Sciences

  Nov 16, 12:00 - 13:00

  KAUST

  We propose a new optimization formulation for training federated learning models. The standard formulation has the form of an empirical risk minimization problem constructed to find a single global model trained from the private data stored across all participating devices. In contrast, our formulation seeks an explicit trade-off between this traditional global model and the local models, which can be learned by each device from its own private data without any communication. Further, we develop several efficient variants of SGD (with and without partial participation and with and without variance reduction) for solving the new formulation and prove communication complexity guarantees.

Nov 8 - Nov 22, 2020

• 

  Waves Functional Materials - 2020-11-15

  Ying Wu, Professor, Applied Mathematics and Computational Sciences

  Nov 15, 12:00 - 13:00

  KAUST

  waves Functional Materials

  Wave functional materials are artificial materials that can control wave propagation as wish. In this talk, I will give a brief review on the progress of wave functional materials and reveal the secret behind the engineering of these materials to achieve desired properties. In particular, I will focus on our contributions on metamaterials and metasurfaces. I will introduce the development of effective medium, a powerful tool in modeling wave functional materials, followed by some illustrative examples demonstrating the intriguing properties, such as redirection, emission rate enhancement, wave steering and cloaking.

Nov 8 - Nov 15, 2020

• 

  The method of intrinsic scaling - Session 4

  Jose Urbano, Professor of Mathematics at the University of Coimbra, Portugal

  Nov 12, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to intrinsic scaling, a powerful method in the analysis of degenerate and singular parabolic PDEs. The local Hölder continuity of bounded weak solutions will be derived from scratch for the model case of the degenerate p-Laplace equation. Our approach is entirely self-contained and focused on the essence of the method, leaving aside technical refinements needed to deal with more general equations.
• 

  Optimization applied to energy systems, autonomous vehicles, and matching

  Ricardo Manuel Pinto de Lima, Research Scientist, Applied Mathematics and Computational Sciences

  Nov 12, 12:00 - 13:00

  KAUST

  In this talk, we start by introducing optimization and interesting optimization applications. We review some optimization formulations and focus on applications studied in our research, such as energy systems, and trajectory planning of autonomous underwater vehicles. After the introduction, we address the self-scheduling and market involvement of a virtual power plant using adaptive robust optimization under uncertainty in the wind speed and electricity prices.
• 

  Control Theoretic Approaches to Computational Modeling and Risk Mitigation for Large Crowd Management

  Mohammed M. Alrashed, M.S., Electrical and Computer Engineering

  Nov 11, 20:00 - 21:00

  KAUST

  resource management risk assessment computational models

  Abstract We develop a computational framework for risk mitigation in high population density events. With an increased global population, the frequency of high population density events is naturally increased. Therefore, risk-free crowd management plans are critical for efficient mobility, convenient daily life, resource management, and most importantly mitigation of any inadvertent incidents and accidents such as stampedes. The status-quo for crowd management plans is the use of human experience/expert advice. However, most often such dependency on human experience is insufficient, flawed
• 

  Exploring Entity Relationship in Pairwise Ranking: Adaptive Sampler and Beyond

  Lu Yu, Ph.D., Computer Science

  Nov 11, 16:00 - 18:00

  KAUST

  Living in the booming age of information, we have to rely on powerful information retrieval tools to seek the unique piece of desired knowledge from such a big data world, like using personalized search engines and recommendation systems. In this thesis, we aim at advancing the development of the methodologies and principles of mining heterogeneous information networks through learning entity relations from a pairwise learning to rank optimization perspective. More specifically we first show the connections of different relation learning objectives modified from different ranking metrics including both pairwise and list-wise objectives. We prove that most of popular ranking metrics can be optimized in the same lower bound. Secondly, we propose the class-imbalance problem imposed by entity relation comparison in ranking objectives, and prove that class-imbalance problems can lead to frequency clustering and gradient vanishment problems. As a response, we indicate out that developing a fast adaptive sampling method is very essential to boost the pairwise ranking model. To model the entity dynamic dependency, we propose to unify the individual-level interaction and union-level interactions, and result in a multi-order attentive ranking model to improve the preference inference from multiple views.
• 

  Civil drones traffic management: Wireless communication for safe UAV

  Prof. Sofie Pollin, KU Leuven

  Nov 10, 16:00 - 17:15

  KAUST

  UAV

  In this webinar, we describe the common terminology for these two communities. First, the traffic management system architecture, requirements, terminology, and services are discussed. A quick overview of existing technologies that can be useful for aerial deconfliction. Next, the focus will shift to wireless technologies used for the tactical (while flying) deconfliction: ADS-B, p2p LoRa, WiFi, FLARM.
• 

  The method of intrinsic scaling - Session 3

  Jose Urbano, Professor of Mathematics at the University of Coimbra, Portugal

  Nov 10, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to intrinsic scaling, a powerful method in the analysis of degenerate and singular parabolic PDEs. The local Hölder continuity of bounded weak solutions will be derived from scratch for the model case of the degenerate p-Laplace equation. Our approach is entirely self-contained and focused on the essence of the method, leaving aside technical refinements needed to deal with more general equations.
• 

  A Novel HVDC Architecture for Offshore Wind Farm Applications

  Otavio Dezem Bertozzi Junior, MS Student, Physical Science and Engineering

  Nov 10, 15:00 - 16:00

  KAUST

  Novel HVDC architecture Offshore wind

  Advances in power electronics have enabled many renewable energy applications. Wind energy harnessing is very promising and offshore farm installations have grown considerably in the past years. In this thesis, we introduce a novel power converter solution for the parallel connection of high-power offshore wind turbines, suitable for HVDC collection and transmission. For the parallel operation of energy sources in an HVDC grid, DC link voltage control is required. The proposed system is based on a full-power rated uncontrolled diode bridge rectifier in series with a partially-rated fully-controlled thyristor bridge rectifier. The thyristor bridge acts as a voltage regulator to ensure the flow of the desired current through each branch, where a reactor is placed in series for filtering of the DC current. AC filters are installed on the machine side to mitigate harmonic content. The mathematical modeling of the system is derived and the control design procedure is discussed. Guidelines for equipment and device specifications are presented. The concept is validated through simulation, and an experimental framework for testing of the system is suggested.
• 

  The equations of polyconvex thermoelasticity

  Myrto Galanopoulou, Ph.D. Student, Applied Mathematics and Computational Sciences

  Nov 9, 17:00 - 19:00

  KAUST

  In my thesis, I consider the system of thermoelasticity endowed with polyconvex energy. After presenting the equations in their mathematical and physical context, I embed the equations of polyconvex thermoviscoelasticity into an augmented, symmetrizable, hyperbolic system which possesses a convex entropy. This allows to prove many important stability results, such as convergence from thermoviscoelasticity (with Newtonian viscosity and Fourier heat conduction) to smooth solutions of the system of adiabatic thermoelasticity, and convergence from thermoviscoelasticity to smooth solutions of thermoelasticity in the zero-viscosity limit. In addition, I establish a weak-strong uniqueness result in the class of entropy weak solutions and in a suitable class of measure-valued solutions, defined by means of generalized Young measures that describe both oscillatory and concentration effects. Also, I construct a variational scheme for isentropic processes of adiabatic polyconvex thermoelasticity: I establish existence of minimizers which converge to a measure-valued solution that dissipates the total energy, while the scheme converges when the limiting solution is smooth.
• 

  Quantile Function Modeling and Analysis for Multivariate Functional Data

  Gaurav Agarwal, Ph.D., Statistics

  Nov 9, 16:00 - 18:00

  KAUST

  This thesis presents a set of quantile analysis methods for multivariate data and multivariate functional data, with an emphasis on environmental applications, and consists of four significant contributions.
• 

  Interactive Visual Data Analysis

  Eduard Gröller, Associate Professor of Practical Informatics at the Vienna University of Technology

  Nov 9, 12:00 - 13:00

  KAUST

  Visualization and visual computing use computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error, and tolerance information.
• 

  UAV Enabled IoT Network Designs for Enhanced Estimation, Detection, and Connectivity

  Osama Bushnaq, Ph.D. (former), Electrical and Computer Engineering

  Nov 9, 11:00 - 13:00

  KAUST

  The Internet of Things (IoT) is a foundational building block for the upcoming information revolution and imminent smart-world era. Particularly, the IoT bridges the cyber domain to everything and anything within our physical world which enables unprecedented ubiquitous monitoring, connectivity, and smart control. In this Ph.D. defense, we present Unmanned Aerial Vehicles (UAVs) enabled IoT network designs for enhanced estimation, detection, and connectivity. The utilization of UAVs can offer an extra level of flexibility which results in more advanced and efficient connectivity and data aggregation for the IoT devices.

Nov 1 - Nov 15, 2020

• 

  Developing smart systems to connect communities.

  Ahmed Eltawil, Associate Dean for Research, Computer, Electrical and Mathematical Sciences and Engineering

  Nov 8, 12:00 - 13:00

  KAUST

  smart systems connect communities

  In this talk, we address fundamental questions that should be asked when contemplating future smart and connected systems, namely, How, Where and What? How can we design computing and communication nodes that best utilize resources in a way that is cognizant of both the abilities of the platform, as well as the requirements of the network? Where are the nodes deployed? By understanding the context of deployment, one can architect unique solutions that are currently unimaginable. With the transformation to diverse applications such as body area networking, critical infrastructure monitoring, precision agriculture, autonomous driving etc., the need for innovative solutions becomes even more amplified. What benefit can be inferred from the data gathered by nodes in the capacity of computing, communication and sensing? The talk will discuss how recent advances in wireless computing and communication nodes can be harnessed to serve the multitude of deployment scenarios required to empower communities of the future with smart and connected systems.

Nov 1 - Nov 8, 2020

• 

  The method of intrinsic scaling - Session 2

  Jose Urbano, Professor of Mathematics at the University of Coimbra, Portugal

  Nov 5, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to intrinsic scaling, a powerful method in the analysis of degenerate and singular parabolic PDEs. The local Hölder continuity of bounded weak solutions will be derived from scratch for the model case of the degenerate p-Laplace equation. Our approach is entirely self-contained and focused on the essence of the method, leaving aside technical refinements needed to deal with more general equations.
• 

  Exploring Non-Linear Interactions in Multivariate Time Series

  Hernando Ombao, Professor, Statistics

  Nov 5, 12:00 - 13:00

  KAUST

  Linear Multivariate extremes Bayesian computational statistics

  Advances in imaging technology have given neuroscientists unprecedented access to examine various facets of how the brain “works”. Brain activity is complex. A full understanding of brain activity requires careful study of its multi-scale spatial-temporal organization (from neurons to regions of interest; and from transient events to long-term temporal dynamics). Motivated by these challenges, we will explore some characterizations of dependence between components of a multivariate time series and then apply these to the study of brain functional connectivity.
• 

  The method of intrinsic scaling - Session 1

  Jose Urbano, Professor of Mathematics at the University of Coimbra, Portugal

  Nov 3, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to intrinsic scaling, a powerful method in the analysis of degenerate and singular parabolic PDEs. The local Hölder continuity of bounded weak solutions will be derived from scratch for the model case of the degenerate p-Laplace equation. Our approach is entirely self-contained and focused on the essence of the method, leaving aside technical refinements needed to deal with more general equations.
• 

  Using Massive MIMO Arrays to Reject Radar-Generated Interference and to Perform Integrated Sensing and Communications

  Prof. Stefano Buzzi, University of Cassino and Lazio Meridionale, Italy

  Nov 3, 16:00 - 17:15

  KAUST

  MIMO

  This webinar will explore the potentiality of massive MIMO arrays in a scenario where radar and communication tasks coexist. The first part of the talk will be devoted to the discussion of a scenario where a wireless network is to co-exist with an external radar system sharing the same frequency band. The second part of the talk will be instead focused on a scenario where a base station equipped with a large scale antenna array simultaneously perform the task of radar surveillance of the surrounding environment and of data communication with mobile users.
• 

  Spatio-Temporal Prediction and Stochastic Simulation for Large-Scale Nonstationary Processes

  Yuxiao Li, Ph.D., Statistics

  Nov 2, 16:00 - 18:00

  KAUST

  Environmental statistics plays an important role in many related applications, such as weather-related risk assessment for urban design and crop growth. However, modeling the spatio-temporal dynamics of environmental data is challenging due to their inherent high variability and nonstationarity. This dissertation focuses on the modeling, simulation, and prediction of spatio-temporal processes using statistical techniques and machine learning algorithms, especially for nonstationary processes.
• 

  Making RPCs first class datacenter citizens

  Marios Kogias, Researcher, Microsoft Research

  Nov 2, 12:00 - 13:00

  KAUST

  I’ll cover thee different RPC policies implemented on top of R2P2. Specifically, we’ll see how R2P2 enables efficient in-network RPC load balancing based on a novel join-bounded-shortest-queue (JBSQ) policy. JBSQ lowers tail latency by centralizing pending RPCs in the middle box and ensures that requests are only routed to servers with a bounded number of outstanding requests. Then, I’ll talk about SVEN, an SLO-aware RPC admission control mechanism implemented as an R2P2 policy on P4 programmable switches. Finally, I’ll describe HovercRaft, a new approach to building fault-tolerant generic RPC services by integrating state-machine replication in the transport layer.