Events

Feb 18 - Mar 3, 2024

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  Smart Grids Communications: Protocols and Cybersecurity

  Suhail Shaik, Electrical Engineering Department, King Fahd University of Petroleum & Minerals

  Feb 25, 12:00 - 13:00

  B9 L2 H2 H2

  smart grids communication protocols ICT

  The conventional power system is transforming into a smart grid through the integration of information and communication technologies (ICT). The incorporation of advanced ICT in the smart grid enhances its control and operational efficiency.

Feb 18 - Feb 25, 2024

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  Rising Stars in AI Symposium 2024

  KAUST

  Feb 19, 08:00 - Feb 21, 17:00

  B19 L3

  Following the resounding success of our previous Annual "Rising Stars in AI" Symposia, including the 2022 and 2023 editions, the AI Initiative at KAUST (King Abdullah University of Science and Technology), located on the scenic Red Sea coast, is thrilled to announce the third installment of this Symposium, scheduled for February 19th to 21st, 2024.

Feb 11 - Feb 25, 2024

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  Point-of-care system: instrumentation and data processing

  Jose Ilton De Oliveira Filho, Postdoctoral Research Fellow, Electrical and Computer Engineering

  Feb 18, 12:00 - 13:00

  B9 L2 H2

  Point of Care devices healthcare innovation

  Point-of-care (PoC) devices refer to portable and affordable diagnosing systems, mostly used in the field of healthcare. PoCs have garnered interest, particularly for detecting diseases that require multiple diagnostic tests and in resource-limited areas.

Feb 11 - Feb 18, 2024

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  Fuzzy clustering of circular time series based on a new distance with applications to wind data

  Ángel López Oriona, Postdoctoral Research Fellow, Statistics

  Feb 15, 12:00 - 13:00

  B9 L2 H2 H2

  Time series clustering is an essential machine learning task with applications in many disciplines. While the majority of the methods focus on time series taking values on the real line, very few works consider time series defined on the unit circle, although the latter objects frequently arise in many applications. In this talk, the problem of clustering circular time series is discussed.
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  Local flex markets from theory to practice: the UK landscape and international experiences

  Jason Avramidis, Director of Innovation and International Flexibility Markets for OakTree Power, UK

  Feb 13, 12:00 - 13:00

  B1 L4 R4214

  Until very recently, distribution-led local flexibility markets were exclusively an academic endeavor, with few practical applications, mostly limited to small-scale innovation projects. However, with European regulation finally catching up with the realities of modern distribution networks, local flexibility markets are slowly becoming a reality - new ones popping up across the continent, or some even becoming a BAU option in the most advanced countries.

Feb 4 - Feb 18, 2024

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  Model hierarchies in semiclassical semi-relativistic quantum models: From Dirac-Maxwell to Euler-Poisson

  Professor Norbert J Mauser, Mathematics, University of Vienna

  Feb 11, 16:00 - 17:00

  B1 L3 R3119

  The Pauli-Poisswell equation models fast-moving charges in semiclassical semi-relativistic quantum dynamics. It is at the center of a hierarchy of models from the Dirac-Maxwell equation to the Euler-Poisson equation that is linked by asymptotic analysis of small parameters such as the Planck constant or inverse speed of light. We discuss the models and their application in plasma and accelerator physics as well as the many mathematical problems they pose
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  Data, AI and Cybersecurity: Synergies and Interconnection

  Marco Mellia, Department of Control and Computer Engineering, Politecnico di Torino, Italy

  Feb 11, 12:00 - 13:00

  B9 L2 H2 H2

  Deep learning cybersecurity artificial intelligence

  This Dean's Distinguished Lecture is part of the ECE Graduate Seminar. Modern Artificial Intelligence (AI) technologies, led by deep learning, have gained unprecedented momentum over the past decade.

Feb 4 - Feb 11, 2024

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  Dependence and Causality in Functional Brain Networks

  Hernando Ombao, Professor, Statistics

  Feb 8, 12:00 - 13:10

  B9 L2 H2 H2

  Brain activity over the entire network is complex. A full understanding of brain activity requires careful study of its multi-scale spatial-temporal organization. Motivated by these challenges, we will explore some characterizations of dependence between components of a multivariate time series and then apply these to the study of brain functional connectivity.
• 

  Matrix-free Monolithic Multigrid Methods for Stokes and Generalized Stokes Problems

  Prof. Ulrich Langer, Institute of Numerical Mathematics, Johannes Kepler University, Linz

  Feb 7, 16:00 - 17:00

  B2 L5 R5209

  stokes equation

  We consider the widely used continuous $Q_{k+1}-Q_k$ quadrilateral or hexahedral Taylor-Hood elements for the finite element discretization of the Stokes and generalized Stokes systems in two and three spatial dimensions.
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  Fast Solution Methods for Wave Propagation Problems: From Classical Domain Decomposition Solvers to Learning

  Prof. Dr. Victorita Dolean, Mathematics and Computer Science, Scientific Computing, TU Eindhoven

  Feb 6, 16:00 - 17:00

  B2 L5 R5220

  wave propagation numerical methods

  Wave propagation and scattering problems are of huge importance in many applications in science and engineering - e.g., in seismic and medical imaging and more generally in acoustics and electromagnetics.
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  Diffusion with Heterogeneous Persistence and Permeability

  Prof. Yong-Jung Kim, KAIST, Korea

  Feb 6, 14:00 - 15:30

  B2 L5 R5209

  A subtle difference in a diffusion model can lead to an opposite conclusion. We need to understand how each component involved in the diffusion phenomenon contributes to the diffusion model. In this talk, we will discuss how nonconstant persistence and permeability play a role in the diffusion phenomenon.
• 

  Harnessing Liquid Metal for Next-Generation Soft Sensors, Actuators, and Reconfigurable Systems

  Wedyan Babatain, Postdoc, MIT

  Feb 6, 10:30 - 11:30

  B9 L4 R4225

  Liquid metal(LM)-based electronics have the potential to shape the future of intelligent systems, soft robotics, and wearable technologies by leveraging their sensing, actuation, and computational capabilities. This talk will discuss methods to harness the unique properties of liquid metal for applications in wearable sensors, soft actuators, and reconfigurable electronic platforms.
• 

  Recent advances in doubly nonlinear equations

  Professor Vincenzo Vespri, of Mathematics Department at the University of Florence, Italy

  Feb 5, 16:00 - 17:00

  B1 L3 R3119

  The term doubly nonlinear refers to the fact that the diffusion part depends nonlinearly both on the gradient and the solution itself. Such equations describe several physical phenomena and were introduced by Lions and Kalashnikov. These equations have an intrinsic mathematical interest because they represent a natural bridge between the more natural generalizations of the heat equation: the p-Laplacian and the porous medium equation.
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  Towards Transparency of IoT Device Presence

  Gene Tsudik, Distinguished Professor of Computer Science, the University of California, Irvine (UCI)

  Feb 5, 11:30 - 12:30

  B9 L2 H2 H2

  cybersecurity IoT

  As many types of IoT devices worm their way into numerous settings and many aspects of our daily lives, awareness of their presence and functionality becomes a source of major concern. Hidden IoT devices can snoop (via sensing) on nearby unsuspecting users, and impact the environment where unaware users are present, via actuation.

Jan 28 - Feb 11, 2024

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  Trainable Decompositions: Addressing Device Heterogeneity

  Prof. Samuel Horvath, Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)

  Feb 4, 15:00 - 16:00

  Buliding 4 L5 R5220

  In the first part of the talk, we introduce Ordered Dropout, a mechanism that achieves an ordered, nested representation of knowledge in deep neural networks (DNNs).
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  Damage-free pixel definition technology for future microLED display

  Zhiyuan Liu, Ph.D. Student, Electrical and Computer Engineering

  Feb 4, 12:00 - 13:00

  B9 L2 H2

  Micro-LEDs Selective thermal oxidation(STO) device performance

  Recently, InGaN-based blue, green, and red (RGB) micro-LEDs have garnered significant attention and interest due to their exceptional features such as high contrast, intense brightness, excellent energy efficiency, and long device lifetimes, positioning them as strong contenders as the next-generation display technology.

Jan 28 - Feb 4, 2024

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  Think globally, act locally: from domain decomposition to nonlinear model order reduction

  Prof. Charbel Farhat

  Jan 30, 14:00 - 15:00

  KAUST Auditorium R2030

  Abstract The Finite Element Tearing and Interconnecting (FETI) methodology is a family of domain decomposition (DD)-based iterative methods for the fast solution on massively parallel processors of large-scale systems of equations arising from finite element (FE) spatial approximations. Developed in its basic form in 1991, it has been extended and refined during 18 years to enable ever faster and more accurate analyses of a broad range of engineering and pathfinder systems such as re-entry vehicles, modern aircraft, advanced Formula 1 cars, aircraft carriers, underwater systems, electronic
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  The Role of Microgrids in Enhancing Power System Resilience against Natural Disasters

  ​​Nikos D. Hatziargyriou, Professor Emeritus, National Technical University of Athens (NTUA)

  Jan 30, 12:00 - 13:00

  Auditorium between B4 and 5

  Power system resilience is defined as the ability of power grids to anticipate, withstand, adapt and recover from high-impact, low-probability (HILP) events. There are long-term and short-term measures that system operators can apply to enhance resilience. Long-term measures include infrastructure hardening and resilient planning, while short-term operational measures are applied in the pre-event, during-event and post-event phases. Microgrids (MGs) can effectively enhance resilience for both transmission and distribution systems due to their ability to operate in a controlled, coordinated way when connected to the primary power grid and in islanded mode. In this presentation, MG-based operational measures for resilience enhancement will be presented, including MG-based resilient operational planning, the systematic formation of MGs after natural disasters hit the system and the role of MGs in power system restoration.
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  Developing, Synthesizing, and Automating Domain-Specific Accelerators

  Jian Weng, Assistant Professor, Computer Science

  Jan 29, 11:30 - 12:30

  B9 L2 H2

  Domain-Specific Accelerators

  In reaction to the waning benefit of transistor scaling and the increasing demands on computing power, specialized accelerators have drawn significant attention from both academics and industry because of their orders-of-magnitude performance improvement and energy efficiency.

Jan 21 - Feb 4, 2024

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  The KAUST Research Conference on Divide, Conquer and Combine Methods in Large-scale Simulation and Analytics (DD28)

  CEMSE Division with financial support from the Office of Research Funding and Services (RFS)

  Jan 28, 14:00 - Feb 1, 12:00

  B20

  To help celebrate the arrival of phase 1 of Shaheen3, an HPE-Cray supercomputer ranked #20 globally as of the November 2023 Top500 list, we are pleased to announce the upcoming KAUST Research Conference on Divide, Conquer and Combine Methods in Large-scale Simulation and Analytics, a.k.a. the 28th International Conference on Domain Decomposition Methods ( DD28) from January 28 to February 1, 2024, at King Abdullah University of Science and Technology (KAUST), Saudi Arabia.
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  Wideband mm-Wave Integrated Circuits and Phased-Array Systems for Multi-Standard Communication

  Abdulrahman Alhamed, Electrical Engineering, King Saud University

  Jan 28, 12:00 - 13:00

  B9 L2 LH 2325

  Phased arrays design Telecommunications Wireless Technology

  The rapid growth in mobile users and high-bandwidth applications is creating unprecedented challenges and opportunities in telecommunications. As we address the need for higher data rates, the mm-Wave 5G bands have been expanded to accommodate this demand.

Jan 21 - Jan 28, 2024

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  On space-time models: models and applications

  Elias Teixeira Krainski, Postdoctoral Research Fellow, Statistics

  Jan 25, 12:00 - 13:00

  B9 L2 H2 H2

  Partial differential equations are a mathematical tool widely used to model phenomena in several different fields. A stochastic partial differential equation (SPDE) introduces random forcing to take the nature of real-world observations.
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  A Posteriori Error Estimation and Adaptivity for Elliptic Interface Problems

  Prof. Zhiming Chen, Academy of mathematics and Systems Science, Chinese Academy of Sciences

  Jan 24, 14:30 - 16:00

  B4 L5 R5220

  adaptive methods linear elliptic equations

  In this short course, we will introduce some elements in deriving the hp a posteriori error estimate for a high-order unfitted finite element method for elliptic interface problems. The key ingredient is an hp domain inverse estimate, which allows us to prove a sharp lower bound of the hp a posteriori error estimator.
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  Arbitrarily High-order Finite Element Methods for Arbitrarily Shaped Domains with Automatic Mesh Generation

  Prof. Zhiming Chen, Academy of Mathematics and Systems Science, Chinese Academy of Sciences

  Jan 23, 16:00 - 17:00

  B2 L5 R5220

  High-order FEM adaptive methods

  Coffee time: 15:30–16:00. We consider high-order unfitted finite element methods on Cartesian meshes with hanging nodes for elliptic interface problems, which release the work of body-fitted mesh generation and allow us to design adaptive finite element methods for solving curved geometric singularities.
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  Scalable demand response of decentralised assets: A perspective on reinforcement learning as a control paradigm

  Prof. Bert Claessens, Ghent University, Belgium

  Jan 22, 13:00 - 14:00

  B3 L5 R5209

  In the last decade reinforcement learning has demonstrated tremendous progress in terms of being a model-free control paradigm for decision making in complex systems with uncertainty and partial observability, thus making it a candidate technology for demand response with a promise of true scalability.
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  Decision Trees for Fault Diagnosis in Circuits and Switching Networks

  Mikhail Moshkov, Professor, Applied Mathematics and Computational Sciences

  Jan 22, 11:30 - 12:30

  B9 L2 H2325

  decision trees switching networks

  We study theoretical problems of fault diagnosis in circuits and switching networks, which are among the most fundamental models for computing Boolean functions.

Jan 14 - Jan 28, 2024

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  The fourth wave: ultrawide bandgap semiconductors

  Xiaohang Li, Associate Professor, Electrical and Computer Engineering

  Jan 21, 12:00 - 13:00

  B9 L2 LH 2325

  Ultrawide bandgap (UWBG) semiconductors including AlN, Ga2O3, c-BN, diamond have attracted enormous interests. They offer markedly larger figures of merits for power and RF applications than other known semiconductors.

Dec 31 - Jan 14, 2023

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  Leading the world to 5G and beyond: A prototyping perspective

  Dr Amira Alloum

  Jan 7, 13:30 - 14:30

  B1 L3 R3119

  The talk will introduce the 5G advanced standard vision for vertical industries and relate it to the latest prototyping effort released by the Qualcomm Research teams.

Dec 10 - Dec 24, 2023

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  Efficient Machine Learning across Hardware, Software, and Algorithms

  Prof. Mohamed Abdelfattah, Electrical and Computer Engineering Department at Cornell University

  Dec 17, 14:00 - 15:30

  B2 L5 R5209

  Efficient machine learning Hardware software algorithms

  Deep neural networks (DNNs) are revolutionizing computing, necessitating an integrated approach across the computing stack to optimize efficiency. In this talk, I will explore the frontier of DNN optimization, spanning algorithms, software, and hardware. We'll start with hardware-aware neural architecture search, demonstrating how tailoring DNN architectures to specific hardware can drastically enhance performance.

Dec 10 - Dec 17, 2023

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  Refined Vehicle Perception: An Innovative Framework for Robust Pedestrian Intent Prediction in Challenging Environments

  Khalid Elgazzar, Professor, Engineering and Applied Science, Ontario Tech University

  Dec 14, 10:00 - 11:00

  B1 L3 R3119

  In this talk, I will present an innovative framework we developed to address these limitations and accurately predict pedestrian crossing intentions. At the core of the framework, we implement an image enhancement pipeline to enable the detection and rectification of various defects that may arise during unfavorable weather conditions. Following this, we employ a transformer-based network with a self-attention mechanism to predict the crossing intentions of pedestrians. This pipeline enhances the model's robustness and accuracy in classification tasks. We assessed our framework using the famous JAAD dataset. Performance metrics indicate that our model achieves state-of-the-art results while ensuring significantly low inference times.
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  From Academia to Management Consulting and Startups

  Dr. Gareth Guvanasen, Director of AI and Data Analytics Division, Partner at Terra Digital Ventures

  Dec 11, 15:00 - 16:00

  B3 L5 R5209

  In my lecture, I will share personal insights on transitioning from academia to management consulting and creating startups. I will discuss how to assess if a career in management consulting suits your goals and skills, and provide practical advice on interviewing successfully with consulting firms.

Dec 3 - Dec 17, 2023

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  Resistance is Futile: Balancing Opportunities and Security Challenges of Federated Learning

  Prof. Ahmad-Reza Sadeghi, Distinguished Professor of Computer Science, the Technical University of Darmstadt, Germany.

  Dec 10, 12:00 - 13:00

  B4 L5 R5220

  artificial intelligence Federated learning

  The rapid growth of Artificial Intelligence (AI) and Deep Learning mirrors an infectious phenomenon. While AI systems promise diverse applications and benefits, they bear substantial security and privacy risks. Indeed, AI represents a goldmine for the security and privacy research domain.

Dec 3 - Dec 10, 2023

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  Multilevel Monte Carlo for a class of Partially Observed Processes in Neuroscience

  Dec 7, 12:00 - 13:00

  B9 L2 H2

  In this talk, we consider Bayesian parameter inference associated to a class of partially observed stochastic differential equations (SDE) driven by jump processes. Such type of models can be routinely found in applications, of which we focus on the case of neuroscience.
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  A Brief History of Artificial Intelligence: Its Past and Its Future

  Dr. Jeffrey M. Bradshaw, Institute for Human and Machine Cognition (IHMC), Florida, USA

  Dec 6, 14:00 - 15:00

  B1 L4 R4102

  Over the past decades, Jeff has been lucky enough to follow some of these developments from a front-row seat. He will share selected perspectives on current and past research including the various pendulum swings over the years between extremes, such as expertise-based knowledge engineering vs. data-centric machine learning, autonomous vs. mixed-initiative systems, publicly available chatbot capabilities vs. personalized, policy-governed multi-agent systems. In this talk, I will show what past research in AI has to teach us about the future.
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  Nonlinear energy stability for phase-field models: Numerics and analysis

  Prof. Tao Tang

  Dec 5, 16:00 - 17:00

  B5 L5 R5209

  phase-field models

  Coffee Time: 15:30 - 16:00. The phase-field model, a powerful modeling tool for dealing with interface problems, has been widely used in various fields such as computational physics, computational biology, materials engineering, and even image processing. The dissipation of free energy is an important and fundamental property of the phase-field model.
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  Error Estimates for Deep Learning Methods in Fluid Dynamics

  Professor, Suleyman Ulusoy, School of Arts and Sciences, American University of Ras Al Khaimah

  Dec 5, 14:30 - 15:30

  B1 L4 R4214

  We provide error estimates and stability analysis of deep learning techniques for certain partial differential equations including the incompressible Navier-Stokes equations. In particular, we obtain explicit error estimates (in suitable norms) for the solution computed by optimizing a loss function in a Deep Neural Network approximation of the solution, with a fixed complexity. This is a joint work with A. Biswas and J. Tian.
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  Gradient Estimates for weak solutions of Elliptic PDE's - Seminar

  Giuseppe Di Fazio, Professor, Mathematics and Computer Sciences, University of Catania, Italy

  Dec 5, 13:00 - 14:00

  B1 L4 R4214

  Let us consider an elliptic equation of second order in variational form i.e. div(A(x)∇u) = divf in a bounded domain Ω ⊂ Rn where the function f belongs to some suitable function space.
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  RC3 Advisory Board Distinguished Lectures Workshop

  RC3 Advisory Board

  Dec 5, 08:30 - 12:30

  B5 L5 R5220

  cybersecurity resilience Computer science

  Machine learning (ML) has witnessed remarkable advancements in recent years, demonstrating its effectiveness in a wide array of applications, including intrusion detection systems (IDS). However, when operating in adversarial environments, ML-based systems are susceptible to a range of attacks.
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  Nonlinear stability of splitting methods for Cahn-Hilliard equations

  Prof. Tao Tang's personal website

  Dec 4, 15:30 - 17:00

  B3 L5 R5220

  nonlinear stability splitting methods Cahn-Hilliard equations

  Splitting methods have been shown to a useful tool in solving phase field equations. However, rigorous nonlinear stability analysis has not been available. In this short course, we will discuss some recent development in this direction.

Nov 26 - Dec 10, 2023

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  Splitting methods: merits and pitfalls

  Prof. Alexander Ostermann

  Dec 3, 16:00 - 17:00

  B2 L5 R5220

  splitting methods numerical integration computational efficiency pitfalls

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

  Prof. Marcin Baszynski

  Dec 3, 12:00 - 13:00

  B9 L2 H2

  power electronics

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

Nov 26 - Dec 3, 2023

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

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

  Nov 30, 15:30 - 16:30

  B5 L5 R5209

  ICT cyber-physical systems

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

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

  Nov 30, 14:00 - 15:00

  B2 L5 R5209

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

  Nov 30, 12:00 - 13:00

  B9 L2 H2

  Many problems in applied geometry amount to the solution of a typically nonlinear partial differential equation. We will discuss why it may not be a good idea to discretize the equation, but to take the viewpoint of discrete differential geometry and discretize the theory.
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  Broadband Wireless Communication Using Free-space Optics and Radio Frequency

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

  Nov 29, 16:30 - 18:30

  B1 L2 R2202

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

  Prof. Jiping Zhang

  Nov 29, 15:00 - 16:00

  B3 L5 R5220

  symmetry groups symmetric polynomials monstrous moonshine

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

  Prof. Efim Zelmanov

  Nov 29, 14:00 - 15:00

  B3 L5 R5220

  Structures Galois

  We will give an overview of the development of Abstract Algebra from Galois to our time. The talk will be accessible to general audience with basic mathematical background.
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  Numerical approximation of PDEs on complex geometries: fluid-structure interaction problems and virtual element methods

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

  Nov 28, 16:30 - 18:30

  KAUST

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

  Diogo Gomes, Program Chair, Applied Mathematics and Computational Sciences

  Nov 27, 11:30 - 12:30

  B9 L2 H2 H2

  minimization Gradient flows Monte Carlo Monte Carlo Methodology

  We develop a derivative-free global minimization algorithm that is based on a gradient flow of a relaxed functional. We combine relaxation ideas, Monte Carlo methods, and resampling techniques with advanced error estimates. Compared with well-established algorithms, the proposed algorithm has a high success rate in a broad class of functions, including convex, non-convex, and non-smooth functions, while keeping the number of evaluations of the objective function small.
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  KAUST Research Conference on 4th 6G Summit: Super Connect the Connected - Connect the Unconnected

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

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

  B18 L4 Fellowship Hall

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