Events

Sep 20 - Sep 26, 2020

• 

  Data-sparse Algorithms for Large-scale Applications on Emerging Architectures

  David Keyes, Senior Associate to the President, King Abdullah University of Science and Technology

  Sep 21, 12:00 - 13:00

  KAUST

  A traditional goal of algorithmic optimality, squeezing out operations, has been superseded because of evolution in architecture. Algorithms must now squeeze memory, data transfers, and synchronizations, while extra operations on locally cached data cost relatively little time or energy. Hierarchically low-rank matrices realize a rarely achieved combination of optimal storage complexity and high-computational intensity in approximating a wide class of formally dense operators that arise in exascale applications. They may be regarded as algebraic generalizations of the fast multipole method.
• 

  Gbit/s Visible Light Communications

  Boon Ooi, Professor, Electrical and Computer Engineering

  Sep 20, 12:00 - 13:00

  KAUST

  Gbit/s Visible light communications

  Visible light communication (VLC or LiFi) has been a topic of intense research after the idea was proposed in 2011. To date, a data rate of multiple 100s Mbps has been demonstrated using LED as light source. At KAUST, we are developing the next generation of SSL lighting using visible laser diodes (LDs) and superluminescent diodes (SLDs). Laser diodes and SLDs do not suffer efficiency droop at high current densities. This allows for the design of lamps using a single, small footprint, light-emitting chip operating at high current densities. Using a single chip reduces system costs compared with LEDs because the system uses less material per chip, requires fewer chips, and employs simplified optics and a simplified heat-sink. The chip area required for LED technologies will be significantly reduced using LD/SLD-based solid-state lighting. This technology will also enable highly controllable beams in term of tunable throw distance, tunable color temperature and rendering index. Multiple Gbit/s VLC links have been demonstrated using LD/SLD as transmitters. In this talk, I will focus on the recent progress of visible diode LD/SLD-based lighting technology and high-speed transmitters and receivers for multiple-Gbps VLC and underwater wireless optical communication.

Sep 13 - Sep 19, 2020

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  The Lipschitz Extension Problem (Session IV)

  Prof. José Miguel Urbano, Department of Mathematics, University of Coimbra, Portugal

  Sep 17, 16:00 - 17:30

  KAUST

  We will discuss the Lipschitz extension problem, its solution via MacShane-Whitney extensions, and its several drawbacks, leading to the notion of AMLE (Absolutely Minimizing Lipschitz Extension). We then present a rigorous and detailed analysis of the equivalence between being absolutely minimizing Lipschitz and enjoying comparison with cones. Finally, we explore some consequences of this geometric notion, chiefly the derivation of a Harnack inequality.
• 

  Estimating High-Resolution Red Sea Surface Temperature Hotspots, Using a Low-Rank Semiparametric Spatial Model

  Arnab Hazra, Postdoctoral Research Fellow, Statistics

  Sep 17, 12:00 - 13:00

  KAUST

  High Resolution X-ray Diffraction spatial modulation

  In this work, we estimate extreme sea surface temperature (SST) hotspots, i.e., high threshold exceedance regions, for the Red Sea, a vital region of high biodiversity. We analyze high-resolution satellite-derived SST data comprising daily measurements at 16703 grid cells across the Red Sea over the period 1985–2015. We propose a semiparametric Bayesian spatial mixed-effects linear model with a flexible mean structure to capture spatially-varying trend and seasonality, while the residual spatial variability is modeled through a Dirichlet process mixture (DPM) of low-rank spatial Student-t processes (LTPs). By specifying cluster-specific parameters for each LTP mixture component, the bulk of the SST residuals influence tail inference and hotspot estimation only moderately. Our proposed model has a nonstationary mean, covariance and tail dependence, and posterior inference can be drawn efficiently through Gibbs sampling. In our application, we show that the proposed method outperforms some natural parametric and semiparametric alternatives.
• 

  High-Speed GaN-Based Distributed-Feedback Lasers and Optoelectronics

  Jorge A. Holguin-Lerma, Ph.D. Student, Electrical and Computer Engineering

  Sep 17, 09:30 - 11:00

  KAUST

  Gallium nitride (GaN) is a semiconductor material highly regarded for visible light generation since it provides the most efficient platform for compact violet, blue, and green light emitters, and in turn, high-quality and ubiquitous white lighting. Despite this fact, the potential of the GaN platform has not been fully exploited. This potential must enable the precise control in the various properties of light, realizing functions beyond the conventional. Simultaneously, the field of the telecommunications is looking for candidate technologies fit for wireless transmission in the next generations of communication. Visible light communication (VLC) may play a significant role in the future of the last mile of the network by providing both a fast internet connection and a high-quality illumination.
• 

  The Lipschitz Extension Problem (Session III)

  Prof. José Miguel Urbano, Department of Mathematics, University of Coimbra, Portugal

  Sep 15, 16:00 - 17:30

  KAUST

  We will discuss the Lipschitz extension problem, its solution via MacShane-Whitney extensions, and its several drawbacks, leading to the notion of AMLE (Absolutely Minimizing Lipschitz Extension). We then present a rigorous and detailed analysis of the equivalence between being absolutely minimizing Lipschitz and enjoying comparison with cones. Finally, we explore some consequences of this geometric notion, chiefly the derivation of a Harnack inequality.
• 

  Automating Guidance in Nanovisualization - Graduate Seminar

  Ivan Viola, Professor, Computer Science

  Sep 14, 12:00 - 13:00

  KAUST

  Research in visualization and computer graphics has developed techniques to geometrically model objects from our everyday life, or from various branches of industry and science, including modeling life-forms that are of submicron in size. These are not visible to the naked eye and most of us are unfamiliar with structures that form life organized in an assembly of biomolecules. Here visualization techniques can be of tremendous help to guide the viewers to familiarize themselves with what they see and make the engaging visual exploration of these complex structures to an intellectual enrichment.
• 

  Learning from Scholarly Attributed Graphs for Scientific Discovery

  Uchenna Akujuobi, Ph.D., Computer Science

  Sep 14, 11:30 - 12:30

  KAUST

  Research and experimentation in various scientific fields are based on the knowledge and ideas from scholarly literature. The advancement of research and development has, thus, strengthened the importance of literary analysis and understanding. However, in recent years, researchers have been facing massive scholarly documents published at an exponentially increasing rate. Analyzing this vast number of publications is far beyond the capability of individual researchers. This dissertation is motivated by the need for large scale analyses of the exploding number of scholarly literature for scientific knowledge discovery and information retrieval. In the first part of this dissertation, the interdependencies between scholarly literature are studied. First, I develop Delve -- a data-driven search engine supported by our designed semi-supervised edge classification method. This system enables users to search and analyze the relationship between datasets and scholarly literature. Based on the Delve system, I propose to study information extraction as a node classification problem in attributed networks. Specifically, if we can learn the research topics of documents (nodes in a network), we can aggregate documents by topics and retrieve information specific to each topic (e.g., top-k popular datasets).
• 

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

  Bernard Ghanem, Professor, Electrical and Computer Engineering

  Sep 13, 12:00 - 13:00

  KAUST

  research image Video Understanding Lab IVUL

  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): We aim to extract meaningful semantic information from large-scale video data by tackling research problems such as object tracking, activity detection, moment retrieval, and language grounding in video. Theme 2 (Visual Computing for Automated Navigation): We develop methodology to enable more accurate, reliable, and robust perception of the visual world for automated navigation applications (e.g. self-driving cars and UAVs). In this theme, we tackle research problems such as object tracking, segmentation, and detection in 3D data, as well as transfer learning from simulation (sim2real). Theme 3 (Fundamentals/Foundations): In this theme, we tackle fundamental research problems in CV and ML that transcend specific applications with focus on deep network theory/analysis (e.g. robustness, certification, and interpretability) and structured optimization methods for large-scale CV/ML problems. Throughout the talk, I will highlight some of the interesting projects at IVUL to encourage students to get interested in the research field.

Sep 6 - Sep 12, 2020

• 

  The Lipschitz Extension Problem (Session II)

  Prof. José Miguel Urbano, Department of Mathematics, University of Coimbra, Portugal

  Sep 10, 16:00 - 17:30

  KAUST

  We will discuss the Lipschitz extension problem, its solution via MacShane-Whitney extensions, and its several drawbacks, leading to the notion of AMLE (Absolutely Minimizing Lipschitz Extension). We then present a rigorous and detailed analysis of the equivalence between being absolutely minimizing Lipschitz and enjoying comparison with cones. Finally, we explore some consequences of this geometric notion, chiefly the derivation of a Harnack inequality.
• 

  A cheap rotated characteristic decomposition technique for high-order reconstructions in multi-dimensions with application to instabilities in direct initiation of gaseous detonations in free space

  Matteo Parsani, Associate Professor, Applied Mathematics and Computational Sciences

  Sep 10, 12:00 - 13:00

  KAUST

  When constructing high-order schemes for solving hyperbolic conservation laws with multi-dimensional finite volume schemes, the corresponding high-order reconstructions are commonly performed in characteristic spaces to eliminate spurious oscillations as much as possible. For multi-dimensional finite volume schemes, we need to perform the characteristic decomposition several times in different normal directions of the target cell, which is very time-consuming. We propose a rotated characteristic decomposition technique that requires only one-time decomposition for multi-dimensional reconstructions. This technique not only reduces the computational cost remarkably, but also controls spurious oscillations effectively. We take a third-order weighted essentially non-oscillatory finite volume scheme for solving the Euler equations as an example to demonstrate the efficiency of the proposed technique. We apply the new methodology to the simulation of instabilities in direct initiation of gaseous detonations in free space.
• 

  The Lipschitz Extension Problem (Session I)

  Prof. José Miguel Urbano, Department of Mathematics, University of Coimbra, Portugal

  Sep 8, 16:00 - 17:30

  KAUST

  We will discuss the Lipschitz extension problem, its solution via MacShane-Whitney extensions, and its several drawbacks, leading to the notion of AMLE (Absolutely Minimizing Lipschitz Extension). We then present a rigorous and detailed analysis of the equivalence between being absolutely minimizing Lipschitz and enjoying comparison with cones. Finally, we explore some consequences of this geometric notion, chiefly the derivation of a Harnack inequality.
• 

  On Studying Computer Science - 2020-09-07

  Peter Wonka, Professor, Computer Science

  Sep 7, 12:00 - 13:00

  KAUST

  Computer science

  The talk will be pre-recorded and a youtube link will be provided to seminar participants. During the seminar time, Prof. Wonka will mainly answer some questions from the audience.
• 

  Flexible, Wearable, Disposable Wireless Communication and Sensing Systems Through Additive Manufacturing - 2020

  Atif Shamim, Program Chair, Electrical and Computer Engineering

  Sep 6, 12:00 - 13:00

  KAUST

  flexible Wearable disposable Wireless communication Sensing Systems additive manufacturing

  With the advent of wearable sensors and internet of things (IoT), there is a new focus on electronics which can be bent so that they can be worn or mounted on non-planar objects. Due to large volume (billions of devices), there is a requirement that the cost is extremely low, to the extent that they become disposable. The flexible and low-cost aspects can be addressed through additive manufacturing technologies such as inkjet, screen and 3D printing. This talk introduces additive manufacturing as an emerging technique to realize low cost, flexible and wearable wireless communication and sensing systems. The ability to print electronics on unconventional mediums such as plastics, papers, and textiles has opened up a plethora of new applications. In this talk, various innovative antenna and sensor designs will be shown which have been realized through additive manufacturing. A multilayer process will be presented where dielectrics are also printed in addition to the metallic parts, thus demonstrating fully printed components. Many new functional inks and their use in tunable and reconfigurable components will be shown. In the end, many system level examples of wireless sensing applications will be shown. The promising results of these designs indicate that the day when electronics can be printed like newspapers and magazines through roll-to-roll and reel-to-reel printing is not far away.

Aug 30 - Sep 5, 2020

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  Machine Learning Models for Biomedical Ontology Integration and Analysis

  Fatima Zohra Smaili, Ph.D. Student, Computer Science

  Sep 3, 16:00 - 17:00

  KAUST

  Biological knowledge is widely represented in the form of ontologies and ontology-based annotations. The structure and information contained in ontologies and their annotations make them valuable for use in machine learning, data analysis and knowledge extraction tasks. In this thesis, we propose the first approaches that can exploit all of the information encoded in ontologies, both formal and informal, to learn feature embeddings of biological concepts and biological entities based on their annotations to ontologies by applying transfer learning on the literature. To optimize learning that combines ontologies and natural language data such as the literature, we also propose a new approach that uses self-normalization with a deep Siamese neural network to improve learning from both the formal knowledge within ontologies and textual data. We validate the proposed algorithms by applying them to generate feature representations of proteins, and of genes and diseases.
• 

  The two faces of correlation

  Haavard Rue, Program Chair, Statistics

  Sep 3, 12:00 - 13:00

  KAUST

  Statistical Modeling computing

  Discussing the concept of correlation and how to interpret it alone (marginally) or within a more complex environment (conditionally). This rather simple observation is the key observation behind a lot of exciting developments and connections in statistics that can be leveraged for improved computations and better motivated statistical models.
• 

  Low Power Micro-electromechanical Resonator-Based Logic Circuits

  Sally Ahmed, Ph.D. Student, Electrical and Computer Engineering

  Aug 31, 16:00 - 17:00

  KAUST

  Abstract The notion of mechanical computation has been revived in the past few years, with the advances of nanofabrication techniques. Although electromechanical devices are inherently slow, they offer zero or very low off-state current, which reduces the overall power consumption compared to the fast complementary-metal-oxide-semiconductor (CMOS) counterparts. This energy efficiency feature is the most crucial requirements for most of the stand-alone battery-operated gadgets, biomedical devices and the internet of things (IoT) applications, which do not require the fast processing speeds
• 

  Large-Scale Visualization of Scientific Data: Volume Data and Flow Fields - 2020-08-31

  Markus Hadwiger, Professor, Computer Science

  Aug 31, 12:00 - 13:00

  KAUST

  ‌ Abstract Welcome to the new semester! This talk will give an overview of the research of the High-Performance Visualization research group (vccvisualization.org) at the KAUST Visual Computing Center (VCC). Interactive visualization is crucial to exploring, analyzing, and understanding large-scale scientific data, such as the data acquired in medicine or neurobiology using computed tomography or electron microscopy, and data resulting from large-scale simulations such as fluid flow in the Earth’s atmosphere and oceans. The amount of data in data-driven science is increasing rapidly toward the
• 

  Power Electronics Applications in Offshore Wind Farms

  Otavio Bertozzi, Ph.D. Student, Electrical and Computer Engineering

  Aug 30, 12:00 - 13:00

  KAUST

  Power electronics Applications Offshore Wind Farms

  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 seminar we will go through some of the fundamentals of these enabling technologies and their applications. We will also present a simple, reliable, efficient and cost-effective concept applied to parallel connection of offshore wind turbines.

Aug 9 - Aug 15, 2020

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  Semi-talk: Efficiency Improvement of AlGaN based Deep UV emitter grown by HT-MOCVD

  Dr. Byeongchan So, Postdoctoral researcher / Ph.D. Department of Nano-Semiconductor Engineering, ​Korea Polytechnic University

  Aug 13, 15:00 - 16:00

  KAUST

  In this seminar, the approaches for improving the efficiency of AlGaN based DUV emitters will be presented. The high-temperature metal organic chemical vapor deposition system has been used to grow high-quality AlGaN based epi-layers and nanostructure on the sapphire substrate.

Jul 26 - Aug 1, 2020

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  Additively Manufactured Vanadium Dioxide (VO₂) based Radio Frequency Switches and Reconfigurable Components

  Shuai Yang, Ph.D., Electrical and Computer Engineering

  Jul 30, 18:00 - 20:00

  KAUST

  Frequency-reconfigurable RF components are highly desired in a wireless system because a single frequency-reconfigurable RF component can replace multiple RF components to reduce the size, cost, and weight. Typically, the reconfigurable RF components are realized using capacitive varactors, PIN diodes, or MEMS switches, which are expensive, require tedious soldering steps, and are rigid and thus non-compatible with futuristic applications of flexible and wearable electronics. In this work, we have demonstrated vanadium dioxide (VO₂) based RF switches that have been realized through additive manufacturing technologies (inkjet printing and screen printing), which dramatically brings the cost down to a few cents. Also, no soldering or additional attachment step is required as the switch can be simply printed on the RF component. The printed VO₂ switches are configured in two types (shunt configuration and series configuration) where both types have been characterized with two activation mechanisms (thermal activation and electrical activation) up to 40 GHz. The measured insertion loss of 1-3 dB, isolation of 20-30 dB, and switching speed of 400 ns is comparable to other non-printed and expensive RF switches. Moreover, as an application for the printed VO₂ switches, a fully printed frequency reconfigurable filter has also been designed in this work.
• 

  Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters

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

  Jul 30, 16:00 - 18:00

  KAUST

  Many key problems in machine learning and data science are routinely modeled as optimization problems and solved via optimization algorithms. With the increase of the volume of data and the size and complexity of the statistical models used to formulate these often ill-conditioned optimization tasks, there is a need for new efficient algorithms able to cope with these challenges. In this thesis, we deal with each of these sources of difficulty in a different way. To efficiently address the big data issue, we develop new methods which in each iteration examine a small random subset of the training data only. To handle the big model issue, we develop methods which in each iteration update a random subset of the model parameters only. Finally, to deal with ill-conditioned problems, we devise methods that incorporate either higher-order information or Nesterov's acceleration/momentum. In all cases, randomness is viewed as a powerful algorithmic tool that we tune, both in theory and in experiments, to achieve the best results.

Jul 19 - Jul 25, 2020

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  Semi-talk: Ion beams in III-nitride research: Doping, characterisation and radiation resistant electronics

  Prof. Katharina Lorenz, Instituto Superior Técnico, University of Lisbon

  Jul 23, 16:00 - 17:30

  KAUST

  Katharina Lorenz's main research interests are the doping of WBS with optically active ions and the study of radiation effects in WBS materials for radiation detectors and radiation resistant electronics.

Jul 12 - Jul 18, 2020

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  Semi-talk: Recent advances in deep-UV photodetectors based on ultrawide band gap semiconductors

  Prof. Digbijoy Nath, Indian Institute of Science

  Jul 16, 14:30 - 16:00

  KAUST

  Brief Biography Education: PhD, Electrical Engineering, 2013, The Ohio State University, Columbus, USA. B. E. (Hons), Electrical & Electronics Engineering, 2008, Birla Institute of Technology and Science (BITS), Pilani.
• 

  The Interplay between Mean-Field Games and Machine-Learning (Session III)

  Prof. Levon Nurbekyan, Department of Mathematics, UCLA

  Jul 15, 21:00 - 23:00

  KAUST

  In this short course, I will discuss connections between mean-field games (MFG) systems and modern machine-learning (ML) techniques and problems. In the first part of the course, roughly the first two lectures, I will present how various ML techniques can be applied to solve high-dimensional MFG systems that are far out of reach for traditional methods. In the second part of the course, I will discuss the reverse relation, namely, how the MFG framework can be useful for solving specific ML problems.
• 

  The Interplay between Mean-Field Games and Machine-Learning (Session II)

  Prof. Levon Nurbekyan, Department of Mathematics, UCLA

  Jul 14, 21:00 - 23:00

  KAUST

  In this short course, I will discuss connections between mean-field games (MFG) systems and modern machine-learning (ML) techniques and problems. In the first part of the course, roughly the first two lectures, I will present how various ML techniques can be applied to solve high-dimensional MFG systems that are far out of reach for traditional methods. In the second part of the course, I will discuss the reverse relation, namely, how the MFG framework can be useful for solving specific ML problems.
• 

  The Interplay between Mean-Field Games and Machine-Learning (Session I)

  Prof. Levon Nurbekyan, Department of Mathematics, UCLA

  Jul 13, 21:00 - 23:00

  KAUST

  In this short course, I will discuss connections between mean-field games (MFG) systems and modern machine-learning (ML) techniques and problems. In the first part of the course, roughly the first two lectures, I will present how various ML techniques can be applied to solve high-dimensional MFG systems that are far out of reach for traditional methods. In the second part of the course, I will discuss the reverse relation, namely, how the MFG framework can be useful for solving specific ML problems.

Jul 5 - Jul 11, 2020

• 

  Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems

  Tariq Alturkestani, Ph.D. Student, Computer Science

  Jul 9, 16:00 - 17:00

  KAUST

  Out-of-Core simulation systems often produce a massive amount of data that cannot fit on the aggregate fast memory of the compute nodes, and they also require to read back these data for computation. As a result, I/O data movement can be a bottleneck in large-scale simulations. Advances in memory architecture have made it feasible to integrate hierarchical storage media on large-scale systems, starting from the traditional Parallel File Systems to intermediate fast disk technologies (e.g., node-local and remote-shared NVMe and SSD-based Burst Buffers) and up to CPU’s main memory and GPU’s High Bandwidth Memory. However, while adding additional and faster storage media increases I/O bandwidth, it pressures the CPU, as it becomes responsible for managing and moving data between these layers of storage. Simulation systems are thus vulnerable to being blocked by I/O operations. The Multilayer Buffer System (MLBS) proposed in this research demonstrates a general method for overlapping I/O with computation that helps to ameliorate the strain on the processors through asynchronous access. The main idea consists in decoupling I/O operations from computational phases using dedicated hardware resources to perform expensive context switches. By continually prefetching up and down across all hardware layers of the memory/storage subsystems, MLBS transforms the original I/O-bound behavior of evaluated applications and shifts it closer to a memory-bound or compute-bound regime.
• 

  Heterogeneous Integration Strategy for Obtaining Physically Flexible 3D Compliant Electronic Systems

  Sohail Faizan Shaikh, Ph.D. Student, Electrical and Computer Engineering

  Jul 9, 15:00 - 16:00

  KAUST

  In this thesis, we present a pragmatic heterogeneous integration strategy to obtain high-performance 3D electronic systems using existing CMOS technology. Critical challenges addressed during the process are; reliable flexible interconnects, maximum area efficiency, soft-polymeric packaging, and heterogeneous integration compatible with current CMOS technology. First, a modular LEGO approach presents a novel method to obtain flexible electronics in a lock-and-key (plug and play) manner with reliable interconnects. It includes a process to convert standard rigid IC into flexible LEGO without any performance degradation with a high-yield. For the majority of healthcare and environmental monitoring applications, a sensory array is essential for continuous spatiotemporal activity recording. Here we present an ultra- high-density sensory solution (1 million sensors) as an epitome of density and address each of the associated challenges. A generic heterogeneous integration scheme is devised to obtain a physically flexible standalone electronic system using 3D-coin architecture. Lastly, a feather-light non-invasive ‘Marine-Skin’ platform to monitor deep-ocean monitoring is presented using the heterogeneous integration scheme. Electrical and mechanical characterization establish the reliability, integrity, robustness, and ruggedness of the processes, sensors, and multisensory flexible system.
• 

  Semi-talk: Characteristics of gallium oxide based wide bandgap semiconductors

  Prof. Qixin Guo, Department of Electrical and Electronic Engineering, Saga University

  Jul 9, 09:00 - 10:30

  KAUST

  Prof. Dr. Guo received B. E., M.E., and Dr. E degrees in electronic engineering from Toyohashi University of Technology in 1990, 1992, and 1996, respectively. He is currently a Professor of Department of Electrical and Electronic Engineering, Saga University as well as Director of Saga University Synchrotron Light Application Center. His research interests include epitaxial growth and characterization of semiconductor materials. Prof. Guo has published more than 300 papers in scientific journals including Nature Communications, Advanced Materials, Physical Review B, and Applied Physics Letters with more than 7200 citations (h-index: 43).
• 

  The Lagrangian Approach to First Order Mean Field Games (Session II)

  Prof. Francisco J. Silva, Applied Mathematics, University of Limoges, France

  Jul 8, 14:00 - 17:00

  KAUST

  In this course, we will consider the so-called Lagrangian approach to mean-field games. We will introduce the problem by recalling some basic results for nonatomic games in a static framework. Next, based on recent results in collaboration with Markus Fischer (University of Padua), I will introduce the analogous setting in the deterministic and dynamic framework. In the second part of the course, I will present the details of a convergence result, obtained in collaboration with Saeed Hadikhanloo, of equilibria of a suitable sequence of discrete-time and finite mean-field games, as introduced by Gomes, Mohr, and Souza in 2010, to an equilibrium of the first-order mean-field game system. The convergence proof relies importantly on the Lagrangian formulation of equilibria.
• 

  The Lagrangian Approach to First Order Mean Field Games (Session I)

  Prof. Francisco J. Silva, Applied Mathematics, University of Limoges, France

  Jul 6, 14:00 - 17:00

  KAUST

  In this course, we will consider the so-called Lagrangian approach to mean-field games. We will introduce the problem by recalling some basic results for nonatomic games in a static framework. Next, based on recent results in collaboration with Markus Fischer (University of Padua), I will introduce the analogous setting in the deterministic and dynamic framework. In the second part of the course, I will present the details of a convergence result, obtained in collaboration with Saeed Hadikhanloo, of equilibria of a suitable sequence of discrete-time and finite mean-field games, as introduced by Gomes, Mohr, and Souza in 2010, to an equilibrium of the first-order mean-field game system. The convergence proof relies importantly on the Lagrangian formulation of equilibria.

Jun 28 - Jul 4, 2020

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  Hierarchical Approximation Methods for Option Pricing and Stochastic Reaction Networks

  Chiheb Ben Hammouda, Ph.D., Applied Mathematics and Computational Sciences

  Jul 2, 14:00 - 16:00

  KAUST

  hierarchical approximation methods option pricing Computational biology

  In biochemically reactive systems with small copy numbers of one or more reactant molecules, stochastic effects dominate the dynamics. In the first part of this thesis, we design novel efficient simulation techniques, based on multilevel Monte Carlo methods and importance sampling, for a reliable and fast estimation of various statistical quantities for stochastic biological and chemical systems under the framework of Stochastic Reaction Networks (SRNs). In the second part of this thesis, we design novel numerical methods for pricing financial derivatives. Option pricing is usually challenging due to a combination of two complications: 1) The high dimensionality of the input space, and 2) The low regularity of the integrand on the input parameters. We address these challenges by using different techniques for smoothing the integrand to uncover the available regularity and improve quadrature methods' convergence behavior. We develop different ways of smoothing that depend on the characteristics of the problem at hand. Then, we approximate the resulting integrals using hierarchical quadrature methods combined with Brownian bridge construction and Richardson extrapolation.
• 

  Regularity Theory for MFG Systems (Session II)

  Prof. Marco Cirant, Department of Mathematics, University of Padova, Italy

  Jul 2, 09:00 - 12:00

  KAUST

  In this short course, I will address some regularity aspects in the theory of Mean-Field Games systems, with special emphasis on stationary and uniformly elliptic problems. I will first describe some regularity results for linear uniformly elliptic PDEs and semi-linear PDEs of Hamilton-Jacobi type. Then, I will show how to use these tools to prove the existence (and in some cases uniqueness) of solutions to MFG systems.
• 

  Two-Scale Homogenization and Numerical Methods for Stationary Mean-Field Games

  Xianjin Yang, Ph.D. Student, Applied Mathematics and Computational Sciences

  Jul 1, 16:00 - 18:00

  KAUST

  mean-field games

  Mean-field games (MFGs) study the behavior of rational and indistinguishable agents in a large population. Agents seek to minimize their cost based upon statistical information on the population's distribution. In this dissertation, we study the homogenization of a stationary first-order MFG and seek to find a numerical method to solve the homogenized problem. More precisely, we characterize the asymptotic behavior of a first-order stationary MFG with a periodically oscillating potential. Our main tool is the two-scale convergence. Using this convergence, we rigorously derive the two-scale homogenized and the homogenized MFG problems. Moreover, we prove the existence and uniqueness of the solution to these limit problems. Next, we notice that the homogenized problem resembles the problem involving effective Hamiltonians and Mather measures, which arise in several problems, including homogenization of Hamilton--Jacobi equations, nonlinear control systems, and Aubry--Mather theory. Thus, we develop algorithms to solve the homogenized problem, effective Hamiltonians, and Mather measures.
• 

  Regularity Theory for MFG Systems (Session I)

  Prof. Marco Cirant, Department of Mathematics, University of Padova, Italy

  Jun 30, 09:00 - 12:00

  KAUST

  In this short course, I will address some regularity aspects in the theory of Mean-Field Games systems, with special emphasis on stationary and uniformly elliptic problems. I will first describe some regularity results for linear uniformly elliptic PDEs and semi-linear PDEs of Hamilton-Jacobi type. Then, I will show how to use these tools to prove the existence (and in some cases uniqueness) of solutions to MFG systems.
• 

  Semi-talk: Wearable Textile Electronics for Personalized Health Care

  Jun Chen, Department of Bioengineering, University of California Los Angeles

  Jun 29, 19:00 - 20:30

  KAUST

  Dr. Jun Chen is currently an assistant professor in the Department of Bioengineering, University of California, Los Angeles. His current research focuses on nanotechnology and bioelectronics for energy, sensing, environment and therapy applications in the form of smart textiles, wearables, and body area sensor networks.

Jun 21 - Jun 27, 2020

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  Mean Field Games with Local Coupling (Session II)

  Prof. Alessio Porretta, Mathematical Analysis, University of Rome Tor Vergata, Italy

  Jun 25, 14:00 - 17:00

  KAUST

  We introduce several PDE tools which are useful in the study of mean field game systems with local couplings. Due to the lack of regularity of solutions, refined compactness and renormalization arguments are needed for a general approach leading to existence and uniqueness results. If time is enough, congestion models will be treated by similar techniques.
• 

  Mean field games with local coupling (Session I)

  Prof. Alessio Porretta, Mathematical Analysis, University of Rome Tor Vergata

  Jun 22, 14:00 - 17:00

  KAUST

  We introduce several PDE tools which are useful in the study of mean field game systems with local couplings. Due to the lack of regularity of solutions, refined compactness and renormalization arguments are needed for a general approach leading to existence and uniqueness results. If time is enough, congestion models will be treated by similar techniques.

Jun 14 - Jun 20, 2020

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  Situational Awareness and Decision-Making Support for Crowd Management in Mina, A Grand Challenge Project Funded by the Ministry of Education

  Dr. Emad Felemban, Associate Professor in Computer engineering of Umm Al-Qura University

  Jun 17, 13:00 - 14:00

  KAUST

  Computer science communication engineering

  Recent real disastrous crowd incidents have shown that crowded places can be exposed to significant safety dangers and that the presence of many pedestrians can potentially result in injuries and fatalities at large scales if not planned and managed reasonably. This fact has resulted in significant challenges for managing the safety of large volumes of pedestrians in dense areas. In retrospect, many such real crowd disasters could have been avoided with better crowd management. Better tools and methodologies to predict crowd behavior during planning for potential emergencies would enable authorities to plan and prepare for improved public safety in crowded environments. Better still, real-time management of crowds might avert disasters if live event data could be used to make rapid predictions of crowd dynamics over the immediate future, allowing management to be optimized as an event unfolds. Such tools do not yet exist, and the technical demands of creating them are not trivial; they will require innovative approaches to both empirical research and modeling.
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  Semi-talk: MOCVD epitaxial growth and device fabrication of GaN-based laser diodes: from visible to ultraviolet

  Prof Ping Chen, Institute of Semiconductor, Chinese Academy of Sciences

  Jun 16, 16:00 - 17:00

  KAUST

  Dr. Ping Chen now works as a full Professor in the Institute of Semiconductors, Chinese Academy of Sciences (Beijing China). He received his bachelor’s degree of Physics from the University of Science and Technology of China (USTC) in 2003, and doctor’s degree of Microelectronics and Solid State Electronics from the Graduate School in University of Chinese Academy of Sciences in 2008. He worked in Georgia Institute of Technology (Atlanta, GA) as a Visiting Scholar from 2017 to 2019.

Jun 7 - Jun 13, 2020

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  Semi-talk: Low Cost Photonics

  Dr. Naresh Chand, Life Fellow of IEEE, Associate Vice President, Chapter Relations of the IEEE Photonics Society

  Jun 9, 16:00 - 17:30

  KAUST

  Dr. Naresh Chand is a Life Fellow of IEEE, Associate Vice President, Chapter Relations of the IEEE Photonics Society, and the Chair, Photonics Society, North Jersey Chapter. Dr. Naresh Chand was previously with US R&D Center of Huawei Technologies in NJ in 2011-2019 where he was working on developing low-cost advanced technologies for Ultra Broadband Optical Access Networks. Prior to this, he worked for BAE Systems (2003-11), Agere Systems and AT&T/Lucent Bell Laboratories (1986-2003), and Dept of Electronics, Government of India (1974-79).
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  Trajectory Planning for Autonomous Underwater Vehicles: A Stochastic Optimization Approach

  Sultan Albarakati, Director, KAUST Academy

  Jun 7, 16:00 - 18:00

  KAUST

  optimization

  In this work, we develop a new framework of trajectory planning for AUVs in realistic ocean scenarios. We divide this work into three parts. In the first part, we provide a new approach for deterministic trajectory planning in steady current, described using Ocean General Circulation Model (OGCM) data. The latter are used to specify both the ocean current and the bathymetry. We apply a NLP to the optimal-time trajectory planning problem. To demonstrate the effectivity of the resulting model, we consider the optimal time trajectory planning of an AUV operating in the Red Sea and the Gulf of Aden. In the second part, we generalize our 3D trajectory planning framework to time-dependent ocean currents. We also extend the framework to accommodate multi-objective criteria, focusing specifically on the Pareto front curve between time and energy. The scheme is demonstrated for time-energy trajectory planning problems in the Gulf of Aden. In the last part, we address uncertainty in the ocean current field. The uncertainty in the current is described in terms of a finite ensemble of flow realizations. The proposed approach is based on a non-linear stochastic programming methodology that uses a risk-aware objective function, accounting for the full variability of the flow ensemble. Advanced visualization tools are used to amplify simulation results.

May 31 - Jun 6, 2020

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  Semi-talk: Deep UV photodetectors based on Ga2O3 thin films grown on sapphire and muscovite mica

  Prof. Rajendra Singh, Indian Institute of Technology Delhi

  Jun 5, 16:00 - 17:30

  KAUST

  Dr. Rajendra Singh is presently a Professor at the Department of Physics, IIT Delhi. He did M.Sc. (Physics) from D.B.S. College, Dehra Dun (affiliated to H.N.B. Garhwal University) in 1995. After that he joined Inter University Accelerator Centre (formerly Nuclear Science Centre), New Delhi for Ph.D. His Ph.D. work was related to the study of the effect of swift heavy ion irradiation on electrical properties of Si and GaAs. He completed his Ph.D. in 2001 with degree from Jawaharlal Nehru University, New Delhi. He then joined Walter Schottky Institute (WSI), Technical University of Munich (TUM), Germany as a post doctoral fellow. There he worked on the design, fabrication and characterization of InP-based heterojunction bipolar transistors (HBTs). He extensively used Class 100 Cleanroom facilities at WSI working on various processing tools such as photolithography, wet etching, reactive ion etching, UHV metallization and rapid thermal annealing. In January 2004 he joined the Max Planck Institute of Microstructure Physics, Halle, Germany as a post doctoral fellow. There he worked in the area of direct wafer bonding and layer splitting of semiconductors for the fabrication of silicon-on-insulator (SOI) and strained silicon-on-insulator (sSOI). He worked in a Class 10 Cleanroom facility at MPI Halle using processing tools such as wet benches, wafer bonding system, plasma enhanced chemical vapour deposition (PECVD) and annealing furnaces.
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  Game-Theoretic Analysis of Smart Grid Markets: From Retail to Wholesale

  Khaled Alshehri, Assistant Professor, KFUPM

  Jun 4, 13:00 - 14:00

  KAUST

  game theory energy

  As end-consumers of electricity become more proactive and as many countries around the world push for a deeper penetration of renewable resources into the power grid, critical issues and challenges arise to the design and operation of deregulated electricity markets. In this presentation, we show how one can exploit tools from game theory to address some of these critical issues. Firstly, wholesale and retail markets are becoming more integrated due to the increasing adoption of distributed energy resources, creating a large gap in the current understanding of the impact of such small-scale energy resources on the larger power system operation and electricity market outcomes. This motivates us to develop a metric, called the Price of Aggregation, which quantifies the impact of integrating distributed energy resources in the retail-level on wholesale market efficiency. Secondly, evidence from real markets indicate that large-scale adoption of wind energy in the transmission system leads to significantly higher price volatility in wholesale markets. To mitigate the effects of price volatility, we propose an add-on centralized clearing mechanism that is applicable to any wholesale market, with the aim of allowing any market participant to hedge against profit volatilities, without changing the existing market operations. Finally, we develop a multiperiod-multicompany demand response framework in retail markets, which captures the behavior of competing companies and their price-responsive end-consumers. Using real-life data, we demonstrate potential savings that can exceed 30% for end-consumers, in addition to revealing desirable mathematical properties and deep insights.

May 24 - May 30, 2020

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  Semi-Talk: III-Nitride Nanowire Light-Emitting Diodes on Silicon and Patterned Substrates

  Prof Hieu Nguyen, Electrical and Computer Engineering, New Jersey Institute of Technology

  May 29, 18:00 - 19:00

  KAUST

  Prof. Hieu Nguyen received the B.S. degree in Physics from Vietnam National University in Ho Chi Minh City, Vietnam (2005), the M.S. degree in Electronics Engineering from Ajou University, South Korea (2009), and the PhD. degree in Electrical Engineering from McGill University, Canada (2012). In September 2014, he joined the Electrical and Computer Engineering Department, New Jersey Institute of Technology. He has authored/co-authored 1 book chapter, 1 patent, 48 journal articles, and more than 70 conference presentations.
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  Indoor 3D Scene Understanding Using Depth Sensors

  Jean Lahoud, Ph.D., Electrical and Computer Engineering

  May 28, 16:00 - 18:00

  KAUST

  Computer Vision 3D object detection Deep learning

  One of the main goals in computer vision is to achieve a human-like understanding of images. This understanding has been recently represented in various forms, including image classification, object detection, semantic segmentation, among many others. Nevertheless, image understanding has been mainly studied in the 2D image frame, so more information is needed to relate them to the 3D world. With the emergence of 3D sensors (e.g. the Microsoft Kinect), which provide depth along with color information, the task of propagating 2D knowledge into 3D becomes more attainable and enables interaction between a machine (e.g. robot) and its environment. This dissertation focuses on three aspects of indoor 3D scene understanding: (1) 2D-driven 3D object detection for single frame scenes with inherent 2D information, (2) 3D object instance segmentation for 3D reconstructed scenes, and (3) using room and floor orientation for automatic labeling of indoor scenes that could be used for self-supervised object segmentation. These methods allow capturing of physical extents of 3D objects, such as their sizes and actual locations within a scene.

May 17 - May 23, 2020

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  Semi-Talk: Role of 3D chemical imaging in advancing wide band gap technology

  Prof. Baishakhi Mazumder, Department of Materials Design and Innovation, School of Engineering and Applied Sciences, University at Buffalo

  May 22, 16:00 - 17:00

  KAUST

  No summary is available.

May 10 - May 16, 2020

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  Semi-Talk: III-Nitride Semiconductor Photonics and Nanoelectronics

  Prof. Jing Zhang, Electrical and Microelectronic Engineering, Rochester Institute of Technology

  May 15, 21:00 - 22:00

  KAUST

  Dr. Jing Zhang is currently the Kate Gleason Endowed Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology. She obtained B.S. degree in Electronic Science and Technology from Huazhong University of Science and Technology (2009), and Ph.D. degree in Electrical Engineering from Lehigh University (2013). Dr. Zhang’s research focuses on developing highly efficient III-Nitride and GaO semiconductor based photonic, optoelectronic, and electronic devices. Her research group is working on the development of novel quantum well active regions and substrates for enabling high-performance ultraviolet and visible LEDs/ lasers, as well as engineering of advanced device concepts for nanoelectronics.

May 3 - May 9, 2020

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  Modeling and Automated Storytelling of Mesoscale Molecular Models

  Ivan Viola, Professor, Computer Science

  May 4, 12:00 - 13:00

  KAUST

  multi-scale 3D visualization biological models

  In my talk, I will present techniques that allow biologists to model a mesocale entity in a rapid way in the timeframe of a few minutes to hours. This way we have created the first complete atomistic model of the SARS-CoV-2 virion that we are these days sharing with the worldwide scientific community. Mesoscale represents a scalar gap that is currently not possible to accurately image with neither microscopy nor X-ray crystallography approaches. For this purpose, scientists characterize it by observations from the surrounding nanoscale and the microscale. From this information, it is possible to reconstruct a three-dimensional model of a biological entity with a full atomistic model. The problem is that these models are enormously large and are not possible to model with traditional methods from computer graphics within a reasonable time.