Events

Oct 11 - Oct 17, 2020

• 

  Post-processing and Feature Extraction Methods for Smart Biomedical Signal Monitoring: Algorithms and Applications

  Abderrazak Chahid, Ph.D. Student, Electrical and Computer Engineering

  Oct 14, 16:00 - 17:00

  KAUST

  Digital health solutions improve healthcare services and help achieve sustainable and higher standards of health and well-being. These solutions are mainly based on Digital Signal Processing (DSP) to record, interpret, and diagnose bio-signals such as Electrocardiogram (ECG) or Magnetoencephalography (MEG). In my thesis, a novel signal/image post-processing algorithm is proposed based on the Semi-Classical Signal Analysis method (SCSA) to enhance biomedical data quality. In addition, new feature extraction algorithms are proposed, based on the SCSA and the new Quantization-based Position Weight Matrix (QuPWM), which opens new tracks toward smart biomedical diagnosis and decision-making assistance in different fields such as predicting true Poly(A) regions in a DNA sequence, multiple hand gesture prediction.
• 

  3D Near Isotropic Antenna in Package for IoT Applications

  SU Zhen, Ph.D., Electrical and Computer Engineering

  Oct 14, 16:00 - 18:00

  KAUST

  Billions of IoT devices will need to communicate with each other in a wireless fashion in the future. Thus, new antenna designs, which perform irrespective of their orientation and position, and can be mass manufactured at lower costs are required. This work presents the theory and design of antennas with near isotropic radiation performance which can be additively manufactured on the packaging of the circuits.
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  Efficient Ensemble Data Assimilation and Forecasting of the Red Sea Circulation

  Habib Toye Mahamadou Kele, Ph.D. Student, Applied Mathematics and Computational Sciences

  Oct 13, 16:15 - 17:00

  KAUST

  This dissertation presents our efforts to build an operational ensemble forecasting system for the Red Sea, based on the Data Research Testbed (DART) package for ensemble data assimilation and the Massachusetts Institute of Technology general circulation ocean model (MITgcm) for forecasting. The Red Sea DART-MITgcm system efficiently integrates all the ensemble members in parallel, while accommodating different ensemble assimilation schemes. The promising ensemble adjustment Kalman filter (EAKF), designed to avoid manipulating the gigantic covariance matrices involved in the ensemble assimilation process, possesses relevant features required for an operational setting. We developed new schemes aiming at lowering the computational burden while preserving reliable assimilation results. The ensemble data assimilation system is implemented and tested on Shaheen, our world-class supercomputer, and will form the basis of the first ever operational Red Sea forecasting system that is currently being implemented to support Saudi Aramco operations in this basin.
• 

  The Infinity Laplacian (Session III)

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

  Oct 13, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to the analysis of infinity-harmonic functions. We detail the proof of the equivalence between enjoying comparison with cones and solving the infinity-Laplace equation in the viscosity sense, thus making a seamless connection with the previous mini-course. Further material includes the existence of infinity-harmonic functions in the case of an unbounded domain and an easy and self-contained proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen.
• 

  Integrated access and backhaul for 5G and beyond

  Dr. Behrooz Makki and Dr. Filip Barać

  Oct 13, 16:00 - 17:30

  KAUST

  5G

  In this talk, we review the main backhauling techniques, and present the main motivations/standardization agreements on IAB. Moreover, we present comparisons between the IAB networks and the cases where all or part of the small access points are fiber-connected.
• 

  Dynamic Programming Multi-Objective Combinatorial Optimization

  Michal A. Mankowski, Postdoctoral Research Fellow, Computer Science

  Oct 13, 15:00 - 16:00

  KAUST

  combinatorial optimization global sequence alignment multi-stage optimization algorithm

  In this dissertation, we consider extensions of dynamic programming for combinatorial optimization. We introduce two exact multi-objective optimization algorithms: the multi-stage optimization algorithm that optimizes the problem relative to the ordered sequence of objectives (lexicographic optimization) and the bi-criteria optimization algorithm that simultaneously optimizes the problem relative to two objectives (Pareto optimization).
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  Visualization and segmentation in Geology and Oil exploration

  Daniel Patel, Bergen University College, Norway

  Oct 12, 12:00 - 13:00

  KAUST

  The talk will consist of two parts. First an introduction to important subsurface structures in relation to hydrocarbon extraction are given, followed by an overview of techniques to segment out and visualize these structures. The talk will include topics such as ground truth visualization of measured seismic data, automated object extraction for getting computer assistance in segmenting important structures in the seismic data such as horizons and faults and creation, and visualizing and visual fusion of multiattribute seismic data using the GPU.
• 

  MXenes for Electronic and Sensing Applications

  Professor Husam Alshareef, Material Science and Engineering, KAUST

  Oct 11, 12:00 - 13:00

  KAUST

  MXenes Electronic Sensing Applications

  This talk will focus on the device applications of MXenes and MXene-derived functional materials. Our group has been developing device concepts that capitalize on the rich and promising properties of MXenes. For example, the excellent electrical conductivity of MXenes makes them good candidates as contact materials electronics (printed, wearable, and stretchable electronics) both as local and global contacts. We have demonstrated that MXenes can be used as electrical contacts in thin-film electronics, CMOS devices, quantum-dot transistors, LEDs, and solar cells.

Oct 4 - Oct 10, 2020

• 

  The Infinity Laplacian (Session II)

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

  Oct 8, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to the analysis of infinity-harmonic functions. We detail the proof of the equivalence between enjoying comparison with cones and solving the infinity-Laplace equation in the viscosity sense, thus making a seamless connection with the previous mini-course. Further material includes the existence of infinity-harmonic functions in the case of an unbounded domain and an easy and self-contained proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen.
• 

  ExaGeoStat: Moving Towards Large-Scale Geostatistical Modeling on Manycore Systems

  Sameh Abdulah, Sameh Abdulah > Appointments, Roles and Affiliations, Hierarchical Computations on Manycore Architectures

  Oct 8, 12:00 - 13:00

  KAUST

  Adaptive modeling

  We present Exascale GeoStatistics (ExaGeoStat) software, a high-performance library implemented on a wide variety of contemporary hybrid distributed-shared supercomputers whose primary target is climate and environmental prediction applications.
• 

  6G: A new frontier for the design of NOMA

  Prof. Zhiguo Ding, University of Manchester

  Oct 6, 16:00 - 17:15

  KAUST

  6G

  The aim of this talk is to provide an overview of the latest research results and innovations in NOMA technologies as well as their emerging applications. Future research challenges regarding NOMA in B5G and 6G are also presented.
• 

  The Infinity Laplacian (Session I)

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

  Oct 6, 16:00 - 17:30

  KAUST

  The mini-course is an introduction to the analysis of infinity-harmonic functions. We detail the proof of the equivalence between enjoying comparison with cones and solving the infinity-Laplace equation in the viscosity sense, thus making a seamless connection with the previous mini-course. Further material includes the existence of infinity-harmonic functions in the case of an unbounded domain and an easy and self-contained proof, due to Armstrong and Smart, of the celebrated uniqueness theorem of Jensen.
• 

  Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining - 2020

  Mikhail Moshkov, Professor, Applied Mathematics and Computational Sciences

  Oct 5, 12:00 - 13:00

  KAUST

  We developed extensions of dynamic programming which allow us (i) to describe the set of objects under consideration, (ii) to perform a multi-stage optimization of objects relative to different criteria, (iii) to count the number of optimal objects, (iv) to find the set of Pareto optimal points for the bi-criteria optimization problem, and (v) to study the relationships between two criteria.
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  Monolithic Integration of InAs Quantum Dot Lasers on Si Substrates

  Yating Wan, Postdoctoral fellow at of University of California, Santa Barbara

  Oct 4, 18:00 - 19:00

  KAUST

  monolithic Quantum Dots laser

  Here, I will talk about recent advances in the field of QD lasers with a focus on direct growth on Si. Si photonics has found widespread application, particularly for high volume applications and for co-integration with CMOS electronics. I will start with an overview of the field, followed with a summary of device performance and fundamental physics basis for the improved response.
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  Recent Advances in Sensor Design

  Khaled Salama, Professor, Electrical and Computer Engineering

  Oct 4, 12:00 - 13:00

  KAUST

  Recent sensor analog design optimization

  In this talk we will discuss the work conducted at KAUST sensors lab and KAUST sensor initiative

Sep 27 - Oct 3, 2020

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  Consensus formation models with delay

  Jan Haskovec, AMCS, KAUST

  Oct 1, 12:00 - 13:00

  KAUST

  Models Formation

  Individual-based models of collective behavior represent a very active research field with applications in physics (spontaneous magnetization), biology (flocking and swarming) and social sciences (opinion formation). They are also a hot topic engineering (swarm robotics). A particularly interesting aspect of the dynamics of multi-agent systems is the emergence of global self-organized patterns, while individuals typically interact only on short scales. In this talk I shall discuss the impact of delay on asymptotic consensus formation in Hegselmann-Krause-type models, where agents adapt their „opinions“ (in broad sense) to the ones of their close neighbors. We shall understand the two principial types/sources of delay - information propagation and processing - and explain their qualitatively different impacts on the consensus dynamics. We then discuss various mathematical methods that provide asymptotic consensus results in the respective settings: Lyapunov functional-type approach, direct estimates, convexity arguments and forward-backward estimates.
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  Nonlinear and dispersive waves: Theory, computations and applications

  Dr. Dimitrios Mitsotakis, Senior Lecturer, Victoria University of Wellington

  Sep 30, 12:00 - 13:00

  KAUST

  oceanic waves dispersive waves

  The study of waves in fluids is one of the most significant branches of fluid mechanics. Part of this study is the theory of nonlinear and dispersive waves which has recently emerged and is still under development. Nonlinear and dispersive waves appear in fluids of any form and have significant role in the fields of oceanic waves (surface and internal), atmospheric modelling, electromagnetism, nonlinear optics, ultra-cold matter and even in blood flow problems. In this presentation we will review relevant applications, such as tsunami waves, the El Nino southern oscillation, blood flow in arteries and solitons propagating in optical fibres. Mathematical modelling techniques for deriving equations that describe such phenomena will be introduced in the context of surface water waves. We will also review the minimum required theoretical background in order to proceed with safe numerical simulations. Finally, we will discuss the numerical modelling of such problems where methods such as standard and mixed Galerkin / Finite element methods are of central focus. We close this presentation by showcasing a topic of much current interest, namely, the development of modern mathematical models for nonlinear and dispersive waves by combining machine learning techniques with classical methodologies.
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  Wireless Communications with Reconfigurable Intelligent Surfaces

  Prof. Ertugrul Basar, Koç University, Istanbul

  Sep 29, 16:00 - 17:15

  KAUST

  Abstract Extensive research has already started on 6G and beyond wireless technologies of 2030 due to the envisioned new use-cases including multisensory augmented/virtual reality applications, wireless brain computer interactions, and fully autonomous systems. Although a plethora of modern physical layer solutions have been introduced in the last few decades with the context of 4G and 5G wireless systems, it is undeniable that a level of saturation has been reached in terms of the available spectrum, adapted modulation/coding solutions and accordingly the maximum throughput as well as
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  Personalized, Predictive and Preventive Visual Analytics for Cancer Treatment

  Renata Raidou, Assistant Professor (Tenure Track) in Medical Visualization and Visual Analytics, and a Rosalind Franklin Fellow at the Bernoulli Institute of the University of Groningen, Netherlands

  Sep 28, 12:00 - 13:00

  KAUST

  The term P4 medicine has been coined almost a decade ago to indicate novel ways of early detection and prevention of diseases. P4 stands for personalized, predictive, preventive, and participatory, to indicate that a diagnosis or treatment is tailored to each individual patient, risk factors are identified early and addressed before manifestation, and individuals are actively involved into all processes. Often, P4 approaches are accompanied by the acquisition of large and complex medical imaging data, and demanding computational processes–especially, when it comes to cancer radiotherapy, which is a data heavy and visual computing rich process.
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  Exploring the Potentials of EM Waves from Body-scale to Nano-communications for Healthcare and Next Generation Wireless Applications

  Akram Alomainy, Reader, Antennas and Applied Electromagnetics, Queen Mary University of London

  Sep 27, 12:00 - 13:00

  KAUST

  healthcare electromagnetic Radio frequency devices Biomedical Engineering

  With the advent of commercial products, such as Apple iWatch and Samsung Galaxy Gear, body-centric communication has increasingly garnered the public attention and smoothly translated state-of-the-art research work into reality. However, challenges still remains and these are often fundamental physical hurdles that need to be further explored and investigated to come up with efficient and scalable solutions applicable to many fields and areas. This becomes an important research area when you look at the scale or rather the multiple scales it needs to work at from body-size or larger networks to the nano-scale where there have been lots of interest recently on how to get nano-devices inside tissues and even inside intelligent materials around us. The talk will present recent development in the area of antennas, RF devices and electromagnetic solutions for applications such as healthcare, biomedical engineering and next generation wireless communications. It will look at the challenges from theoretical, numerical and experimental prospective to ensure that proposed concepts and outcomes are of benefit not only to those domains but other beyond such as agricultural technology and smart home and cities.

Sep 20 - Sep 26, 2020

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  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.
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  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.
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  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.
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  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.
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  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.
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  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.
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  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).
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  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

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  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.
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  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.
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  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.
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  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.
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  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.
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  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
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  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
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  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.
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  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.
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  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.
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  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.
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  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

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  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.
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  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.
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  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).