Events

Sep 26 - Oct 2, 2021

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  Advanced Ga2O3 flexible and electronic devices

  Xiao Tang, Research Scientist, Electrical and Computer Engineering

  Sep 26, 12:00 - 13:00

  KAUST

  Nowadays, the development of portable and wearable electronics becomes unprecedentedly significant because they allow for real-time communication, remote controlling, and monitoring of various potential environmental hazards regardless of location and time.

Sep 19 - Sep 25, 2021

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  Network-based clustering approaches for integrative multiomics data and drug response prediction

  Zehor Belkhatir, Senior Lecturer, Control Engineering, De Montfort University

  Sep 20, 15:00 - 16:00

  B1 L2 H2

  multiomics data integration Wasserstein distance gene ontology

  Biological data sets, such as gene expressions, copy number alteration, and pharmacogenomics, are often high-dimensional and thus difficult to analyze and interpret. This talk presents two data analysis methodologies that we recently developed based on network analysis via Wasserstein optimal transport combined with unsupervised classification techniques.
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  Resilience is the Cybersecurity of the XXI century, and here's why! - 2021-09-19

  Sep 19, 12:00 - 13:00

  KAUST

  In a nutshell, Resilient Computing is a new paradigm based on modelling, architecting and designing computer systems so that: they have built-in baseline defences; such defences cope with virtually any quality of threat, be it accidental faults, design errors, cyber-attacks, or unexpected operating conditions; provide incremental protection of, and automatically adapt to, a dynamic range of threat severity; provide sustainable operation. Resilient Computing will be a game changer in the craft of designing computer systems of today and future.

Sep 12 - Sep 18, 2021

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  Audio Event Recognition for Automatic Acoustic Monitoring

  Farook Sattar, Electrical and Computer Engineering, University of Victoria, Canada

  Sep 16, 16:00 - 17:00

  KAUST

  bioacoustics acoustic signals audio event recognition

  Nowadays acoustic sensors collect huge amount of data on a regular basis to monitor various activities. This necessitates automated audio event recognition using acoustic data. In this talk, we will present effective methods for detecting and classifying different audio events. Interesting ideas and results will be shown for the proposed methods related to biological/bioacoustic signals.
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  End-to-end Optics Design for Computational Cameras

  Qilin Sun, Ph.D. Student, Electrical and Computer Engineering

  Sep 15, 16:20 - 18:10

  KAUST

  Imaging systems have long been designed in separated steps: the experience-driven optical design followed by sophisticated image processing. Such a general-propose approach achieves success in the past but left the question open for specific tasks and the best compromise between optics and post-processing, as well as minimizing costs. Driven from this, a series of works are proposed to bring the imaging system design into end-to-end fashion step by step, from joint optics design, PSF optimization, phase map optimization to a general end-to-end complex lens camera.
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  Multiphysics Simulation of Semiconductor Optoelectronic Devices

  Liang Chen, Research Scientist, Electrical and Computer Engineering

  Sep 12, 12:00 - 13:00

  KAUST

  Multiphysics Simulation

  In this talk, I will introduce a simulator specifically formulated and implemented for photoconductive terahertz devices enhanced with nanostructures. The fundamental challenge in formulating this simulator is the rigorous modeling of the coupling mentioned above. My talk will focus on this aspect as well as the general concerns in building mathematical models for various physical processes and their numerical discretization. To this end, I will introduce a discontinuous Galerkin framework that can efficiently discretize the multiscale mathematical models formulated for coupled semiconductor physics and electromagnetics. Furthermore, I will present numerical results which demonstrate the applicability of this framework in characterizations of photoconductive terahertz antennas and photomixers.

Sep 5 - Sep 11, 2021

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  Microwave Water Cut Sensors for Oil Industry: From Design to Deployment in the Field

  Muhammad A. Karimi, Chief Technology Officer, Saher Flow Solutions

  Sep 5, 12:00 - 13:00

  KAUST

  This talk will be focused on developing low-cost sensors, which can increase oil production efficiency through real-time monitoring of oil wells. The mechanism behind the development of low-cost & printed microwave sensors will be introduced followed by a number of applications where these sensors can be utilized. A specific application to measure the composition of production fluid will be described in detail. Unique benefits of Microwave DMOR technology, utilized in the sensors, will be explained in comparison with existing technologies.

Aug 29 - Sep 4, 2021

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  Dark Vision: A Sensory Eye into Subsurface Wellbore Casings

  Shehab Ahmed, Professor, Electrical and Computer Engineering

  Aug 29, 12:00 - 13:00

  KAUST

  Dark Vision Sensory Eye Subsurface Wellbore

  After a quick overview of the ECE Graduate Seminar logistics, I will share a quick introduction to the wellbore construction process. This will help build the case for maintaining wellbore integrity in order to protect assets, people, the environment and production. The synergistic integration of electromagnetics, electronics and machine learning to create a novel mechatronic solution to address wellbore integrity needs is then discussed. The solution utilizes a full maxwell equations solver deployed on KAUST’s super computing platforms to enable next generation physics informed wellbore integrity solutions based on non-contact EM field propagation circuits. While downhole camera technologies are used today, they require illumination and an optically clear environment. Our electromagnetic ‘vision’ system overcomes these limitations and provides additional capability to ‘see through’ nested wellbore tubulars.

Aug 15 - Aug 21, 2021

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  Machine Learning in Healthcare: When Low Sample Size is not a Limitation

  Dr. Ricardo Henao, Biostatistics and Bioinformatics, Duke University

  Aug 17, 14:30 - 15:30

  KAUST

  In this talk, I will describe three use cases that highlight present challenges and opportunities for the development of machine learning methodology for applications in healthcare. First, I will describe the development of simple word embedding approaches for bag of-documents classification and its applications to diagnosis of peripheral artery disease from clinical narratives. Second, I will present an approach for volumetric image classification that leverages attention mechanisms, contrastive learning and feature-encoding sharing for geographic atrophy prognosis from optical coherence tomography images. Third, I will discuss machine learning approaches for multi-modal and multi-dataset integration for biomarker discovery from molecular (omics) data. To conclude, I will summarize the contributions and insights in each of these different directions in which relatively low sample sizes are the common denominator.
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  Applications of Magnetic Transition Metal Dichalcogenide Monolayers to the Field of Spinorbitronics

  Idris H. Smaili, Ph.D. Student, Electrical and Computer Engineering

  Aug 16, 11:00 - 13:00

  KAUST

  flexible nanodevices flexible solar cells nanomaterials thin films density functional theory

  Magnetic random access memory (MRAM) devices have been widely studied since the 1960s. During this time, the size of spintronic devices has continued to decrease. Consequently, there is now an urgent need for new low-dimensional magnetic materials to mimic the traditional structures of spintronics at the nanoscale. We also require new effective mechanisms to conduct the main functions of memory devices, which are: reading, writing, and storing data.

Jul 25 - Jul 31, 2021

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  Stochastic Optimization in Target Positioning and Location-based Applications

  Hui Chen, Ph.D. Student (former), Electrical and Computer Engineering

  Jul 27, 17:00 - 19:00

  KAUST

  stochastic algorithm optimization Hand Gestures Recognition

  This event has been postponed from 20th July to 27th July. Stochastic optimization refers to the minimization/maximization of an objective function in the presence of randomness. The randomness may appear in objective functions, constraints, or optimization methods. It has the advantage of dealing with uncertainties that deterministic optimizers cannot solve or cannot solve efficiently. In this work, we discuss the implementation of stochastic optimization methods in solving target positioning problems and tackling key issues in location-based applications.

Jul 4 - Jul 10, 2021

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  State Estimation for Nonlinear Dynamical Systems: Methods and Applications | Part 2C

  Prof. Ali Zemouche, Université de Lorraine and Khadidja Chaïb Draa, TechnOptiz

  Jul 7, 14:00 - 17:00

  KAUST

  nonlinear dynamics linear matrix inequalities Lyapunov methods

  Abstract In this lecture we will address the problem of observer design for nonlinear systems. It is mainly devoted to Linear Matrix Inequality (LMI) based methods and their use to improve observer design for a large class of nonlinear systems. A second part of this course will be dedicated to simple but useful contributions to high-gain observer design, where some techniques to improve performances of the standard high gain observer will be presented. Before tackling the problem of observer design, basic notions on stability by using direct and indirect Lyapunov methods will be thoroughly
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  State Estimation for Nonlinear Dynamical Systems: Methods and Applications | Part 2B

  Prof. Ali Zemouche, Université de Lorraine and Khadidja Chaïb Draa, TechnOptiz

  Jul 6, 14:00 - 17:00

  KAUST

  nonlinear dynamics linear matrix inequalities Lyapunov methods

  Abstract In this lecture we will address the problem of observer design for nonlinear systems. It is mainly devoted to Linear Matrix Inequality (LMI) based methods and their use to improve observer design for a large class of nonlinear systems. A second part of this course will be dedicated to simple but useful contributions to high-gain observer design, where some techniques to improve performances of the standard high gain observer will be presented. Before tackling the problem of observer design, basic notions on stability by using direct and indirect Lyapunov methods will be thoroughly
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  State Estimation for Nonlinear Dynamical Systems: Methods and Applications | Part 2A

  Prof. Ali Zemouche, Université de Lorraine and Khadidja Chaïb Draa, TechnOptiz

  Jul 5, 14:00 - 17:00

  KAUST

  nonlinear dynamics linear matrix inequalities Lyapunov methods

  Abstract In this lecture we will address the problem of observer design for nonlinear systems. It is mainly devoted to Linear Matrix Inequality (LMI) based methods and their use to improve observer design for a large class of nonlinear systems. A second part of this course will be dedicated to simple but useful contributions to high-gain observer design, where some techniques to improve performances of the standard high gain observer will be presented. Before tackling the problem of observer design, basic notions on stability by using direct and indirect Lyapunov methods will be thoroughly

Jun 27 - Jul 3, 2021

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  State estimation for nonlinear dynamical systems: Methods and applications | Part 1C

  Prof. Ali Zemouche, Université de Lorraine and Khadidja Chaïb Draa, TechnOptiz

  Jun 30, 14:00 - 17:00

  KAUST

  nonlinear dynamics linear matrix inequalities Lyapunov methods

  Abstract In this lecture we will address the problem of observer design for nonlinear systems. It is mainly devoted to Linear Matrix Inequality (LMI) based methods and their use to improve observer design for a large class of nonlinear systems. A second part of this course will be dedicated to simple but useful contributions to high-gain observer design, where some techniques to improve performances of the standard high gain observer will be presented. Before tackling the problem of observer design, basic notions on stability by using direct and indirect Lyapunov methods will be thoroughly
• 

  State Estimation for Nonlinear Dynamical Systems: Methods and Applications | Part 1B

  Prof. Ali Zemouche, Université de Lorraine and Khadidja Chaïb Draa, TechnOptiz

  Jun 29, 14:00 - 17:00

  KAUST

  nonlinear dynamics linear matrix inequalities Lyapunov methods

  Abstract In this lecture we will address the problem of observer design for nonlinear systems. It is mainly devoted to Linear Matrix Inequality (LMI) based methods and their use to improve observer design for a large class of nonlinear systems. A second part of this course will be dedicated to simple but useful contributions to high-gain observer design, where some techniques to improve performances of the standard high gain observer will be presented. Before tackling the problem of observer design, basic notions on stability by using direct and indirect Lyapunov methods will be thoroughly

Jun 13 - Jun 19, 2021

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  Learning over Graphs

  Ali H. Sayed, Dean of Engineering, EPFL Switzerland

  Jun 15, 16:30 - 17:45

  KAUST

  This talk explains how agents over a graph can learn from dispersed information and solve inference tasks of varying degrees of complexity through localized processing. The presentation also shows how information or misinformation is diffused over graphs, how beliefs are formed, and how the graph topology helps resist or enable manipulation. Examples will be considered in the context of social learning, teamwork, distributed optimization, and adversarial behavior.

Jun 6 - Jun 12, 2021

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  Research on Ultrawide Bandgap Semiconductors

  Xiaohang Li, Associate Professor, Electrical and Computer Engineering

  Jun 8, 15:00 - 16:30

  KAUST

  Wide bandgap (WBG) semiconductors including GaN have demonstrated great success in lighting, display, electrification, and 5G communication due to superior properties and decades of R&D. Lately, the III-nitride and III-oxide ultrawide bandgap (UWBG) semiconductors with bandgap larger than GaN have attracted increasing attentions. They are regarded as the 4th wave of the inorganic semiconductors after the consequential Si, III-V, and WBG semiconductors. Because the UWBG along with other properties could enable electronics and photonics to operate with significantly greater power and frequency capability and at much shorter far−deep UV wavelengths, crucial for sustainability and health of the human society. Besides, they could be employed for the revolutionary quantum information science as the host and photonic platform. This seminar would cover the latest research by the Advanced Semiconductor Lab. It includes multi-disciplinary studies of growth, materials, physics, and devices of the UWBG semiconductors.

May 30 - Jun 5, 2021

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  Part 2B | PDE Backstepping Boundary Control of Parabolic PDEs

  Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

  Jun 2, 17:00 - 18:30

  KAUST

  Partial Differential Equations Lyapunov methods linear parabolic PDEs parabolic-hyperbolic PDE

  Partial Differential Equations (PDEs) are often used to model various complex physical systems. Representative engineering applications such as heat exchangers, transmission lines, oil wells, road traffic, multiphase flow, melting phenomena, supply chains, collective dynamics, and even chemical processes governing the state of charge of Lithium-ion battery, extrusion, reactors to mention a few. This course will explore the boundary control of a class of parabolic PDE via the well-known backstepping method.
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  Part 2A | PDE Backstepping Boundary Control of Parabolic PDEs

  Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

  Jun 2, 15:00 - 16:30

  KAUST

  Partial Differential Equations Lyapunov methods linear parabolic PDEs parabolic-hyperbolic PDE

  Abstract Partial Differential Equations (PDEs) are often used to model various complex physical systems. Representative engineering applications such as heat exchangers, transmission lines, oil wells, road traffic, multiphase flow, melting phenomena, supply chains, collective dynamics, and even chemical processes governing the state of charge of Lithium-ion battery, extrusion, reactors to mention a few. Generally, key aspects of these processes operating mode are driven by convection phenomena with a spatiotemporal dynamic that cannot be approximated straightforwardly using a finite
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  Part 1B | PDE Backstepping Boundary Control of Parabolic PDEs

  Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

  Jun 1, 17:00 - 18:30

  KAUST

  Partial Differential Equations Lyapunov methods linear parabolic PDEs parabolic-hyperbolic PDE

  PDE Backstepping Boundary Control of Parabolic PDEs Partial Differential Equations (PDEs) are often used to model various complex physical systems. Representative engineering applications such as heat exchangers, transmission lines, oil wells, road traffic, multiphase flow, melting phenomena, supply chains, collective dynamics, and even chemical processes governing the state of charge of Lithium-ion battery, extrusion, reactors to mention a few. This course will explore the boundary control of a class of parabolic PDE via the well-known backstepping method.
• 

  Part 1A | PDE Backstepping Boundary Control of Parabolic PDEs

  Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

  Jun 1, 15:00 - 16:30

  KAUST

  Partial Differential Equations Lyapunov methods linear parabolic PDEs parabolic-hyperbolic PDE

  Partial Differential Equations (PDEs) are often used to model various complex physical systems. Representative engineering applications such as heat exchangers, transmission lines, oil wells, road traffic, multiphase flow, melting phenomena, supply chains, collective dynamics, and even chemical processes governing the state of charge of Lithium-ion battery, extrusion, reactors to mention a few. This course will explore the boundary control of a class of parabolic PDE via the well-known backstepping method.

May 23 - May 29, 2021

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  Computational Wavefront Sensing: Theory, Practice, and Applications

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

  May 26, 18:00 - 19:30

  KAUST

  Wavefront sensing is a fundamental problem in applied optics. Wavefront sensors that work in a deterministic manner are of particular interest. Initialized with a unified theory for classical wavefront sensors, this dissertation discusses relevant properties of wavefront sensor designs. Based on which, a new wavefront sensor, termed Coded Wavefront Sensor, is proposed to leverage the advantages of the analysis, especially the lateral wavefront resolution. A prototype was built to demonstrate this new wavefront sensor.
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  Towards 6G Wireless Communication Networks: Vision, Enabling Technologies, and New Paradigm Shifts

  H. Vincent Poor, Michael Henry Strater University Professor, Princeton University

  May 25, 15:30 - 16:30

  KAUST

  Fifth generation (5G) wireless communication networks are being deployed worldwide and more capabilities are in the process of being standardized, such as massive connectivity, ultra-reliability, and low latency. However, 5G will not meet all requirements of the future, and sixth generation (6G) wireless networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, greater intelligence and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architectures, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. One vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication networks. Multiple spectra will be exploited to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the very large datasets generated by heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of AI-related technologies. And, fourth, network security will have to be strengthened when developing 6G networks. This talk will review recent advances and future trends in these four aspects.

May 2 - May 8, 2021

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  Advances in Microelectromechanical Digital Circuit Design: Low Power Computation, Sensing and Beyond

  Hossein Fariborzi, Adjunct Professor (former), Electrical and Computer Engineering

  May 2, 12:00 - 13:00

  KAUST

  Microelectromechanical Digital Circuit design Low Power computation Sensing

  Electromechanical switches were the core elements of the very first digital computers in early 20th century. While these switches were later replaced by the smaller, faster and more reliable "transistor" technology, they found a new life following the development of nanofabrication tools and Micro-electromechannical Systems (MEMS). In this seminar we will explore the most recent advances in the field of MEMS-based digital circuit and sensor design. We also examine the application of MEMS switches and resonators in building the most important blocks of a digital system, namely adders, multipliers, data converters, sequential and combinational complex logic, and discuss the future of this technology in the beyond-CMOS era.

Apr 25 - May 1, 2021

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  Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 2B

  Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

  Apr 27, 14:00 - 15:30

  KAUST

  wastewater treatment adaptive linearizing control dynamical modeling

  There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
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  Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 2A

  Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

  Apr 27, 10:30 - 12:00

  KAUST

  wastewater treatment adaptive linearizing control dynamical modeling

  There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
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  Applied Complexity: Ultra-flat AI materials for different applications

  Andrea Fratalocchi, Professor, Electrical and Computer Engineering

  Apr 25, 12:00 - 13:00

  KAUST

  We review our recent results on artificial-intelligent designed ultra-flat materials that embeds "physical" neural networks for different application in biomedical imaging, optics, displays, and structural color generation.

Apr 18 - Apr 24, 2021

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  Introduction to hybrid dynamical systems: Part 2B

  Prof. Mohamed Djemai, University Polytechnique Hauts-de-France

  Apr 22, 14:00 - 15:30

  KAUST

  Dynamical Systems Modelization Time Scale Approach

  This research is motivated not only because the control of some systems is implemented through the combination of continuous control laws with discrete switching logic but also because a wide range of physical and engineering systems exhibit hybrid behavior. Among the problems to be addressed, those of stabilization and observation are particularly important in order to always improve the efficiency of systems in terms of performance, lifetime and efficiency.
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  Introduction to hybrid dynamical systems: Part 2A

  Prof. Mohamed Djemai, University Polytechnique Hauts-de-France

  Apr 22, 10:30 - 12:00

  KAUST

  Dynamical Systems Modelization Time Scale Approach

  In recent years, new theoretical tools have been developed to describe complex systems more precisely, such as hybrid dynamical systems (HDS). Many works ranging from modelling to stabilisation, or control and observation have focused on the study of this class of systems. This research is motivated not only because the control of some systems is implemented through the combination of continuous control laws with discrete switching logic but also because a wide range of physical and engineering systems exhibit hybrid behavior. Among the problems to be addressed, those of stabilization and observation are particularly important in order to always improve the efficiency of systems in terms of performance, lifetime and efficiency.
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  Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 1B

  Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

  Apr 20, 14:00 - 15:30

  KAUST

  wastewater treatment adaptive linearizing control dynamical modeling

  There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
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  Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 1A

  Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

  Apr 20, 10:30 - 12:00

  KAUST

  wastewater treatment adaptive linearizing control dynamical modeling

  The objective of this course is to give an introduction and cover recent aspects of dynamical modeling, monitoring and control of wastewater treatment processes. There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
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  KL Divergence Regularized Learning Model for Multi-Agent Decision Making

  Shinkyu Park, Assistant Professor, Electrical and Computer Engineering

  Apr 18, 12:00 - 13:00

  KAUST

  The large population game framework has been widely adopted in biology, economics, and engineering fields to model and analyze strategic interactions among decision-making agents. In this framework, a population of agents select strategies of interaction with one another and repeatedly revise their strategy choices using revisions defined by a decision-making model. While many of existing works in the literature focus on designing decision-making models that ensure convergence of the agents’ strategy revision to Nash equilibrium, a still open challenge is to establish the convergence when the agents’ strategy revision is subject to time delay. Such scenarios include multi-agent decision problems in which there is delay in propagation of traffic congestion in congestion games, communication between the electric power utility and demand response agents in demand response games, and information transmission between agents in network games. In this seminar, I’ll introduce our recent work on designing a new decision-making model called the Kullback-Leibler (KL) divergence regularized learning. We will discuss how the new model enables a large population of agents to learn and self-organize to an effective strategy profile in population games subject to time delay and implication of the new model in engineering applications.

Apr 11 - Apr 17, 2021

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  Introduction to hybrid dynamical systems: Part 1B

  Prof. Mohamed Djemai, University Polytechnique Hauts-de-France

  Apr 15, 14:00 - 15:30

  KAUST

  Dynamical Systems Modelization Time Scale Approach

  This research is motivated not only because the control of some systems is implemented through the combination of continuous control laws with discrete switching logic but also because a wide range of physical and engineering systems exhibit hybrid behavior. Among the problems to be addressed, those of stabilization and observation are particularly important in order to always improve the efficiency of systems in terms of performance, lifetime and efficiency.
• 

  Introduction to hybrid dynamical systems: Part 1A

  Prof. Mohamed Djemai, University Polytechnique Hauts-de-France

  Apr 15, 10:30 - 12:00

  KAUST

  Dynamical Systems Modelization Time Scale Approach

  In recent years, new theoretical tools have been developed to describe complex systems more precisely, such as hybrid dynamical systems (HDS). Many works ranging from modelling to stabilisation, or control and observation have focused on the study of this class of systems.
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  Pointing and Trajectory Tracking Control for Optical Wireless Communication

  Ibrahima N’Doye, Research Scientist, Electrical and Computer Engineering (ECE), CEMSE, KAUST

  Apr 11, 12:00 - 13:00

  KAUST

  Pointing Trajectory tracking control Optical wireless communication

  In this talk, I will present our recent works on reducing the beam pointing error for improved free-space optical communication (FSO) link performance. Specifically, I will discuss a robust control strategy that reduces the beam alignment error under controlled weak turbulence conditions for FSO systems. Then, I will discuss localization and tracking control of a mobile target ship with an autonomous underwater vehicle (AUV) in underwater environment. The framework is designed using a hybrid acoustic-optical underwater communication to drive the AUV to the maximum achievable data rate angle. The acoustic link is used for non-line-of-sight localization, and the optical link is for line-of-sight transmission. I will conclude the talk by providing recent results on estimating the alignment angle through a novel estimation-based reference trajectory control algorithm for an LED-based optical communication model.

Apr 4 - Apr 10, 2021

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  Discriminant Analysis and Support Vector Regression in High Dimensions: Sharp Performance Analysis and Optimal Designs

  Houssem Sifaou, Ph.D., Electrical and Computer Engineering

  Apr 8, 11:00 - 13:00

  KAUST

  Machine learning is emerging as a powerful tool to data science and is being applied in almost all subjects. In many applications, the number of features is comparable or even larger than the number of samples, and both grow large. This setting is usually named the high-dimensional regime. In this regime, new challenges and questions arise when it comes to the application of machine learning. In this work, we conduct a high-dimensional performance analysis of some popular classification and regression techniques. In a first part, discriminant analysis classifiers are considered. A major challenge towards the use of these classifiers in practice is that they depend on the inverse of covariance matrices that need to be estimated from training data. Several estimators for the inverse of the covariance matrices can be used. The most common ones are estimators based on the regularization approach. The main advantage of such estimators is their resilience to the sampling noise, making them suitable to high-dimensional settings. In this thesis, we propose new estimators that are shown to yield better performance.
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  Blue LED material beyond Blue for Micro-LED Displays

  Kazuhiro Ohkawa, Professor (former), Electrical and Computer Engineering

  Apr 4, 12:00 - 13:00

  KAUST

  LED material Displays

  Energy is an indispensable part of our lives. We are challenging energy-saving novel light emitters and clean-energy generation systems at Energy Conversion Devices and Materials (ECO Devices) Laboratory at KAUST. The former is based on MOCVD technology, material science, and device technology. The latter is the nitride photocatalyst invented by Ohkawa. The development of highly-efficient InGaN-based blue LEDs was the topic of the 2014 Nobel Prize in Physics. InGaN-based green LEDs were realized after improving the quality of higher-In-content InGaN. The three primary colors in light are RGB. The current red LEDs are based on InGaP as the active region. If we realize red LEDs by InGaN, we can fabricate the monolithic RGB LEDs in a wafer. Such RGB integration will be a breakthrough for micro-LED displays that are the next generation after the OLED displays. In this seminar, the science of MOCVD, the growth of high-In-content InGaN, and the state-of-the-art InGaN-based red LEDs will be introduced.

Mar 28 - Apr 3, 2021

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  Wireless Magnetic Sensors to Empower the Next Technological Revolution

  Abdullah Almansouri, PhD Student, Electrical and Computer Engineering, KAUST

  Apr 1, 16:00 - 17:00

  KAUST

  The next technological revolution, Industry 4.0, is envisioned as a digitally connected ecosystem where machines and gadgets are driven by artificial intelligence. By 2025, more than 75 billion devices are projected to serve this revolution. Many of which are to be integrated into the fabrics of everyday life in the form of smart wireless sensors. Still, two major challenges should be addressed to realize truly wireless and wearable sensors. First, the sensors should be flexible and stretchable, allowing for comfortable wearing. Second, the electronics should scavenge the energy it requires entirely from the environment, thus, eliminating the need for batteries, which are bulky, create ecological problems, etc. By addressing these two challenges, this dissertation paves the way for truly wearable sensors.
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  Transient Analysis of Electromagnetic and Acoustic Scattering using Second-kind Surface Integral Equations

  Rui Chen, PhD Student, Electrical and Computer Engineering, KAUST

  Mar 31, 16:00 - 18:00

  KAUST

  Time-domain methods are preferred over their frequency-domain counterparts for solving acoustic and electromagnetic scattering problems since they can produce wide-band data from a single simulation. Among the time-domain methods, time-domain surface integral equation solvers have recently found widespread use because they offer several benefits over differential equation solvers. This dissertation develops several second-kind surface integral equation solvers for analyzing transient acoustic scattering from rigid and penetrable objects and transient electromagnetic scattering from perfect electrically conducting and dielectric objects. For acoustically rigid, perfect electrically conducting, and dielectric scatterers, fully explicit marching-on-in-time schemes are developed for solving time domain Kirchhoff, magnetic field, and scalar potential integral equations, respectively.
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  Towards Robust and Accurate Navigation: Theory, Applications, and Future Directions

  Tareq Al-Naffouri, Professor, Electrical and Computer Engineering

  Mar 28, 12:00 - 13:00

  KAUST

  Towards Robust Navigation theory Applications Future Directions

  Navigation is an essential requirement for many applications (commercial, retail, military, scientific, ...etc) and in a variety of environments (in-doors, outdoors, space, underwater, and even underground). In this talk, I will overview some of my group's work in localization and navigation focusing on indoor and satellite positioning. The talk will demonstrate how the structure or constraints of the problem can help achieve very accurate localization (e.g. millimeter level indoors) that is robust to Doppler, multipath, and shadowing. The talk will also touch upon various related applications that the group is pursuing in smart health and smart cities. The talk will end with future directions for localization in extreme environments and in the TeraHertz spectrum where localization, environment sensing, and communication converge.

Mar 21 - Mar 27, 2021

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  Advancing Visual Intelligence via Neural System Design

  Hengshuang Zhao, Postdoctoral Fellow, Oxford University

  Mar 21, 12:00 - 13:00

  KAUST

  Visual Intelligence Neural System design

  Building intelligent visual systems is essential for the next generation of artificial intelligence systems. It is a fundamental tool for many disciplines and beneficial to various potential applications such as autonomous driving, robotics, surveillance, augmented reality, to name a few. An accurate and efficient intelligent visual system has a deep understanding of the scene, objects, and humans. It can automatically understand the surrounding scenes. In general, 2D images and 3D point clouds are the two most common data representations in our daily life. Designing powerful image understanding and point cloud processing systems are two pillars of visual intelligence, enabling the artificial intelligence systems to understand and interact with the current status of the environment automatically. In this talk, I will first present our efforts in designing modern neural systems for 2D image understanding, including high-accuracy and high-efficiency semantic parsing structures, and unified panoptic parsing architecture. Then, we go one step further to design neural systems for processing complex 3D scenes, including semantic-level and instance-level understanding. Further, we show our latest works for unified 2D-3D reasoning frameworks, which are fully based on self-attention mechanisms. In the end, the challenges, up-to-date progress, and promising future directions for building advanced intelligent visual systems will be discussed.

Mar 14 - Mar 20, 2021

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  mm-Sized Wireless Implantable Medical Devices Toward Clinical Diagnostics and Therapeutics

  Pyungwoo Yeon, Postdoctoral Fellow, Electrical Engineering, Stanford University

  Mar 14, 16:00 - 17:00

  KAUST

  Implantable and wearable technologies are rapidly emerging and showing great promise in various medical therapeutics and diagnostics. These advances from health monitoring to therapeutic applications reorganize many aspects of daily life. Since the invention of the first implantable cardiac pacemaker for patients with arrhythmia in 1958, many implantable medical devices (IMDs) such as implantable cardioverter defibrillators (ICDs) and implantable deep brain stimulators (iDBSs) have been developed and have treated millions of patients. These IMDs eventually need wireless powering and communication for 1) eliminating transcutaneous power/data interconnects that elevate the risk of infection and 2) removing bulky batteries to avoid the risk of repeated surgical intervention. They also need small form factors and soft materials to mitigate tissue fibrosis due to foreign body responses. In this talk, I will introduce a new wireless neural interfacing tool within a cubic millimeter that can potentially record large scale neuronal ensembles over large brain area. The discussion will be focused on its building pieces across a wide range of science and engineering disciplines toward translating those into a complete clinically viable IMD. Also, I will present my recent research on RF-to-ultrasound power relay for powering deep mm-scale implants across air/tissue or tissue/skull media, and an all-soft and wireless pressure sensor tags that aim to address the issues of surgical complexity, tethering effect, and foreign body response. Finally, I will conclude the talk by presenting my future research plans toward clinically viable wireless medical diagnostics and therapeutics.

Mar 7 - Mar 13, 2021

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  Generation of Orbital Angular Momentum (OAM) Modes with Spiral Phase Plate Integrated Laser Source

  Edgars Stegenburgs, Ph.D. Student, Electrical and Computer Engineering

  Mar 10, 12:00 - 14:00

  KAUST

  The objective of this work is to develop a near-infrared laser device capable of emitting orbital angular momentum (OAM) light. The prototyped device must be suitable for compact, energy-saving optical communication applications. Integrated OAM lasers would revolutionize high capacity data transmission over any telecommunication network environment as OAM light can be guided and transmitted through kilometers of optical fibers as well as propagated in free space and underwater.
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  Materials and Devices for Printed Flexible Electronics

  Derya Baran, Assistant Professor, Material Science and Engineering, PSE, KAUST

  Mar 7, 12:00 - 13:00

  KAUST

  flexible electronics Flexible electronic devices

  The need for big data that the internet of things (IoT) has created in recent years has turned the focus on integrating the human body in the quest to understand it better, and in turn use such information for detection and prevention of harmful conditions. Applications in which continuous and uninterrupted operation is required, or where the use of external power sources may be challenging demands the use of self-powered autonomous systems. Organic photovoltaic devices are flexible, lightweight, and soft, capable of interacting with the human body and its mechanical demands. Their processability from solutions permits their adaptation to versatile fabrication techniques such as spin coating, roll-to-roll coating and inkjet printing, with benefits including low material usage and freedom of design. In this talk, I will present how organic photovoltaics can be utilized in printed electronics as energy harvesting devices and go through the historical progress of organic/hybrid photovoltaics as well as the main activities that are ongoing in my research lab ‘Omegalab’.

Feb 28 - Mar 6, 2021

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  The fourth wave: ultrawide bandgap compound semiconductors for photonics and electronics

  Xiaohang Li, Assistant Professor, Electrical and Computer Engineering

  Feb 28, 12:00 - 13:00

  KAUST

  The fourth wave semiconductors photonics electronics

  Wide bandgap (WBG) compound semiconductors including GaN have shown enormous success in solid-state lighting, display, and electrification in recent decades due to superior properties such as direct bandgap, high electron mobility, and large breakdown field. They have been changing the world by elevating living standards and addressing grand challenges such as global warming. The pioneering researchers have been recognized by numerous accolades including the Nobel Prize and most recently, the Queen Elizabeth Prize. Lately, the III-nitride and III-oxide ultrawide bandgap (UWBG) compound semiconductors with bandgap larger than 3.4 eV have attracted increasing attentions: they have been regarded as the 4th wave/generation after the consequential Si, III-V, and WBG semiconductors. Because the UWBG along with other properties could enable electronics and photonics to operate with significantly greater power and frequency capability and at much shorter far−deep UV wavelengths, respectively, both crucial for human society. Besides, they could be employed for the revolutionary quantum information science as the host and photonic platform. However, extensive multi-disciplinary studies of growth, materials, physics, and devices are essential to unearth the potentials due to the infancy. This seminar would cover the latest research on those aspects. It includes growth of state-of-the-art materials, discovery of unique material properties, and development of a widely adopted device physics framework for photonics and electronics especially short and long wavelength photonic devices.

Feb 21 - Feb 27, 2021

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  High-Dimensional Analysis of Regularized Convex Optimization Problems with Application to Massive MIMO Wireless Communication Systems

  Ayed M. Alrashdi, Ph.D. Student (former), Electrical and Computer Engineering

  Feb 21, 17:00 - 18:00

  KAUST

  In this thesis, we focus on precisely analyzing the high dimensional error performance of such regularized convex optimization problems under the presence of different impairments (such as uncertainties and/or correlations) in the measurement matrix, which has independent Gaussian entries. The precise nature of our analysis allows performance comparison between different types of these estimators and enables us to optimally tune the involved hyperparameters. In particular, we study the performance of some of the most popular cases in linear inverse problems, such as the Least Squares (LS), Regularized Least Squares (RLS), LASSO, Elastic Net, and their box-constrained variants.
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  Smart Meter Data-Driven Load Forecasting and Price Design in the Retail Market

  Dr. Yi Wang, Postdoctoral Researcher, Power Systems Laboratory, ETH Zurich

  Feb 21, 12:00 - 13:00

  KAUST

  Smart Meter Data-Driven Load forecasting Price design Retail Market

  The widespread popularity of smart meters enables an immense amount of fine-grained smart meter data to be collected. Meanwhile, the deregulation of the power industry, particularly on the delivery side, has continuously been moving forward worldwide. Electricity retailer is one of the main participants in the retail market. This presentation will discuss how an electricity retailer can increase the competitiveness in the retail market by making full use of the fine-grained smart meter data. Since load forecasting is fundamental for various businesses of the retailer, the first part of this presentation will study how to enhance the performance of aggregated load forecasting using the fine-grained smart meter data. Designing customizing prices is an effective way to promote consumer interactions and increase customer stickiness for retailers. The second part of this presentation will introduce a novel data-driven approach for incentive-compatible customizing time-of-use (ToU) price design so that the benefits of both the retailer and consumers can be gained.

Feb 7 - Feb 13, 2021

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  Visible Light Communications Technology and Machine Learning - 2021-02-12

  Dr. Paul Anthony Haigh, Newcastle University, United Kingdom and Dr. Bo Tan, Tampere University, Finland

  Feb 12, 16:00 - 17:15

  KAUST

  vlc

  In this webinar we will give an overview of several key technologies related to our special issues in Frontiers of Communications and Networks; (1) visible light communications (VLC) and (2) applications of machine learning in optical and wireless communication systems.
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  Ariadne: Building safe autonomy with unproven algorithms

  Eric Feron, Professor, Electrical and Computer Engineering

  Feb 7, 12:00 - 13:00

  KAUST

  Ariadne safe autonomy unproven algorithms

  With the advent of increasingly intelligent algorithms, robots are capable of planning and performing increasingly challenging and creative tasks. Safety, however, remains an essential requirement on robotic behaviors. It is also a property that is hard or impossible to prove for virtually all intelligent algorithms of practical value. Ariadne is a model-based paradigm that enables the safe operation of many robotic systems, even though the algorithms involved with the operation may not be verifiable. Ariadne, or "plan B" engineering, will be illustrated in various current Robotics contexts derived from Ariadne's own Greek mythology, railroad systems, nuclear energy production, air transportation, and others.