Topics

<> Statistical computing (2) <> statistical methods (2)

Modeling and Inference for Multivariate Time Series, with Applications to Integer-Valued Processes and Nonstationary Extreme Data

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B4 L5 R5220

This Ph.D. research focuses on proposing new statistical methods for two types of time series data: integer-valued data and multivariate nonstationary extreme data. For the former, the researcher proposes a novel approach to building an integer-valued autoregressive (INAR) model that offers the flexibility to specify both marginal and innovation distributions, leading to several new INAR processes. For the latter, the researcher proposes new extreme value theory methods for analyzing multivariate nonstationary extreme data, specifically EEG recordings from patients with epilepsy. Two extreme-value methods, Conex-Connect and Club Exco, are proposed to study alterations in the brain network during extreme events such as epileptic seizures.

Sarah Alghamdi

Ph.D. Student, Computer Science
Sarah Alghamdi is a Ph.D. candidate in the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Robert Hoehndorf. Research Interests Sarah's research interests include applications of artificial intelligence and using statistical methods to genomics and healthcare. Professional Profile Program Committee for the International Conference of Biomedical Ontology (ICBO 2022) Program Committee for the International Society of Molecular Biology (ISMB 2022) - Bio-Ontology track 2018-2021: Teaching Assistant positions: CS
<> stochastic gradient descent (2) <> stochastic partial differential equations (2) <> stokes equation (2) <> structural design (2) <> STSDS (2) <> Student Internship Programs (2)

Saudi Summer Internship 2019 - E-Poster Competition

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Campus Library

We invite all members of the community to visit the first ever E-poster competition at KAUST for the SSI. The Saudi Summer Internship (SSI) is currently in it’s 7th year. This year CEMSE welcomes over 40 undergraduate students from Saudi Arabia to KAUST. With 25 interns being female, and 12 universities represented, 2019 is the largest and most diverse cohort of the SSI that the division has welcomed since it’s inception. All students have an excellent academic record in their home institution in areas related to Computer Science, Electrical Engineering and Mathematics. The students undertake a 12 week research program, supplemented with graduate skills and academic courses and are mentored by faculty and researchers in the CEMSE Division.

Mashail Alwadi

Mashail Alwadi is the Student Internship Specialist at the Computer, Elecrtical and Mathematical Sciences (CEMSE) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Mashail earned her Bachelor's Degree in Management Information Systems from Yanbu University College (YUC) in Yanbu Industrial City. She graduated with First Class Honors in 2013. Education Profile B. S. in Management Information Systems, Yanbu University College, 2013
<> Student Support (2) <> Subsurface (2)

Dark Vision: A Sensory Eye into Subsurface Wellbore Casings

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KAUST

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.

Managing subsurface uncertainties in reservoir simulations: Applications to compositional flow and geothermal extraction

Prof. Hussein Hoteit, Energy Resources and Petroleum Engineering, KAUST

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B2 L5 R5220

Reservoir simulation is an essential tool in reservoir engineering, enabling effective management and optimization of reservoirs. Despite minimal changes in the fundamental sciences since the development of reservoir simulators, advancements in computational power and linear solvers have significantly improved the technology. However, the reliability and ability to improve decision quality of reservoir models remain debatable.
<> supercomputers (2) <> Symbolic Computation (2) <> Telecommunications (2) <> telescope (2) <> The Internet of Bodies (2) <> thermoelectric appliances (2) <> Thermoelectric materials (2) <> thermoelectric power harvesters (2) <> thin film deposition (2) <> threat intelligence (2) <> Thz rectennas (2) <> Time Series Analysis (2) <> TinyML (2) <> Tissue Engineering (2) <> Trajectory optimization (2) <> transport equation (2) <> transportation networks (2) <> Trustworthy AI (2) <> TSS (2)

Promoters identification and analysis

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B1 L2 R2202

Promoter is a key region that is involved in differential transcription regulation of protein-coding and RNA genes. The gene-specific architecture of promoter sequences makes it extremely difficult to devise the general strategy for their computational identification.

Novel computational methods for promoter identification and analysis

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B2 L5 R5209

In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.
<> Turbulence (2)

On some nonlinear elliptic/parabolic systems arising in mechanics and turbulence

Prof. Luigi Carlo Berselli

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B2 L5 R5220

I consider the vector counterpart of the classical p-Laplace and p-heat equations which are some of the building blocks for the mathematical description of non-linear plasticity, non-Newtonian fluids, and turbulent eddy viscosity models. I will discuss results of “natural regularity” and their role in the study of the well-posedness of the nonlinear pdes as well as in the theory of convergence for space-time discretisation methods. In particular, I will present the “A-approximation" method which generalises results by Necas and which reduces the problem to a family of linear ones. Coffee Time: 15:30 - 16:00

Steven Dufour

Steven Dufour is a Former Visiting ​Associate Professor from École Polytechnique de Montréal, at Professor Raul F. Tempone's Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Steven's research activities revolve around the development of numerical methodologies for the modeling of free surface flows that can be found in various industrial applications. The main challenge associated with the numerical modeling of multifluid flows is to accurately locate the interfaces between each fluid. More complex flows, such as the flow of
<> UAV communications (2) <> ultrasound ranging (2) <> ultraviolet wavelengths (2) <> Underwater acoustic and optical communication (2) <> underwater acoustics (2) <> underwater sensor (2) <> University of Oxford (2)

Aggregation-Diffusion and Kinetic PDEs for collective behavior: applications in the sciences

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B1 L3 R3119

In this seminar, I will present a survey of micro, meso and macroscopic models where repulsion and attraction effects are included through pairwise potentials. I will discuss their interesting mathematical features and applications in mathematical biology and engineering. Qualitative properties of local minimizers of the interaction energies are crucial in order to understand these complex behaviors. I will showcase the breadth of possible applications with three different phenomena in applications: segregation, phase transitions, and consensus.

Simon Maher

Simon Maher is currently an assistant professor of sensors and analytical instrumentation in the Department of Electrical Engineering & Electronics at the University of Liverpool, U.K. Maher graduated from KAUST in 2010 with a master’s degree in electrical engineering. After KAUST, he went on to complete his Ph.D. from the University of Liverpool in 2013. Maher has held positions at the University of Oxford, AMOLF, Ohio State University and Tata Steel. He was a co-founder and director of the U.K. charity Caring Alone, receiving a Community Impact Award from the Prince of Wales for services to
<> University of Pennsylvania (2)

Quantum Inspired Photonics

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B1 L2 R4214

Quantum mechanics and photonics share mathematical equivalence. By carefully exploiting the interplay between optical index, gain and loss in the complex dielectric permittivity plane, optics has become an ideal platform to explore some exotic quantum concepts, such as topological physics and parity-time (PT) symmetry. Instead of counteracting optical losses at micro and nano scales in integrated photonics, we started from an opposite viewpoint and developed a new paradigm of positively and strategically manipulating optical losses by the quantum-inspired photonics concept enrich fundamental optical physics and realized novel photonic synthetic matters with unique optical functionalities. In this seminar, I will present our recent efforts on engineering the complex optical potentials at an exceptional point (i.e. PT symmetry transition point). Based on the exceptional point-induced unidirectionality, we harness optical losses to enable unique microlaser functionalities, in particular, an orbital angular momentum (OAM) microlaser that structures and twists the lasing radiation at the microscale, which is expected to address the growing demand for information capacity. Additionally, I will discuss non-Hermitian topological photonics where optical non-Hermiticity and topological physics are coupled.

Light Matter Interactions in Layered Materials: from Trivial to Topological Band Structures

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B1 L2 R4214

Strongly confined electrical, optical and thermal excitations drastically modify material’s properties and break local symmetries that can enable precisely tunable novel responses and new functionalities. We will discuss the effect of engineered plasmonic lattice on light matter interactions in 2D excitonic crystals to produce novel responses such as enhanced and tunable emission, Fano resonances and strong exciton-plasmon polaritons, which can be precisely controlled by geometry and applied fields to produce novel device concepts. Our recent work on collective polaritonic modes and the formation of a complete polaritonic bandgap in few-layered excitonic semiconductors coupled to plasmons will also be presented.
<> Unmanned aerial vehicles UAVs enabled wireless networks (2) <> urban modeling (2) <> user authentication (2)

Practical Cryptographic Framework to Manage Security and Privacy for IoT Endpoint devices

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B1 L4 R4214

In this talk, the speaker will provide a high-level introduction to his recent research on IoT endpoint security. Firstly, he will introduce requirements followed by a discussion on cryptographic algorithm implementation. He will mainly focus on an overview of efficient cryptography for IoT endpoints and system privacy issues. Then he will discuss security management approaches, positives, negatives and challenges to resolve, linking to the endpoint device security section with regards to realistic device needs/capabilities.

Dictionary Attacks on Biometrics

Prof. Nasir Memon, Vice Dean for Academics and Student Affairs and Professor of Computer Science and Engineering at the New York University Tandon School of Engineering

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B9 L2 H2

Contrary to the prevailing belief, we show that user authentication based on biometrics is vulnerable to dictionary attacks. We show the problem is particularly significant for partial prints used in smartphones and increasingly adopted for authentication tasks ranging from unlocking the devices screen up to payment authorization. We also show that speaker verification systems are also vulnerable to dictionary attacks. We then discuss ways to mitigate such attacks.
<> variant prioritization (2)

Semantic Prioritization of Novel Causative Genomic Variants in Mendelian and Oligogenic Diseases

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B9 R4223

Abstract Recent advances in Next Generation Sequencing (NGS) technologies have facilitated the generation of massive amounts of genomic data which in turn is bringing the promise that personalized medicine will soon become widely available. As a result, there is an increasing pressure to develop computational tools to analyze and interpret genomic data. In this dissertation, we present a systematic approach for interrogating patients' genomes to identify candidate causal genomic variants of Mendelian and oligogenic diseases. To achieve that, we leverage the use of biomedical data available

Imane Boudellioua

Imane Boudellioua obtained her Ph.D. degree in Computer Science under the supervision of Professor Robert Hoehndorf at the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST). Imene has a Master's degree in Computer Science from KAUST. During Master's her thesis supervisor was Professor Basem Shihada. Thesis title: " A Vehicular Guidance Wireless Sensor Actuator Network." Research Interests Imane Boudellioua's research interests include the application of machine learning and data mining algorithms for functional annotation of various biological
<> vertical-cavity surface emitting laser (2) <> Virtual Element Method (2)

Parallel multilevel solvers for virtual element discretizations of saddle point problems

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B1 L3 R3119

In this seminar, we will present our work on Virtual Element Method (VEM) approximations. The Virtual Element Method is a recent numerical technique for solving partial differential equations on computational grids constituted by polygonal or polyhedral elements of very general shape. This work aims to develop effective linear solvers for general order VEM approximations of three-dimensional scalar elliptic equations in mixed form and Stokes equations. To this end, we consider block algebraic multigrid preconditioners and balancing domain decomposition by constraints (BDDC) preconditioners. The latter allows us to use conjugate gradient iterations, albeit the algebraic linear systems arising from the discretization of the differential problems are indefinite, ill-conditioned, and of saddle point nature.

Virtual Element Approximation of Eigenvalue Problems

Prof. Francesca Gardini, Università di Pavia

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B1 L3 R3119

We will discuss the solution of eigenvalue problems associated with partial differential equations (PDE)s that can be written in the generalised form Ax = λMx, where the matrices A and/or M may depend on a scalar parameter. Parameter dependent matrices occur frequently when stabilised formulations are used for the numerical approximation of PDEs. With the help of classical numerical examples we will show that the presence of one (or both) parameters can produce unexpected results.
<> Visual Art (2) <> vlc (2) <> Water Desalination and Reuse (2) <> water resources monitoring (2)

Coal product used to create green clean water

1 min read ·
Compressed blocks of pulverized coal can be used as the basis of sunlight-powered off-grid water purification. The technology is already being progressed by commercial partners toward pilot-scale production of drinking water. Dark-colored materials that strongly soak up sunlight to drive seawater desalination are a long-standing research interest of KAUST's Andrea Fratalocchi. While reading about the economic challenges of ending coal’s use for power generation, Fratalocchi was struck by a novel possible use for coal. “The two ideas clicked together: why don’t we use coal for a new economy in

Matthew McCabe

Research Interests Prof. McCabe’s research focuses on issues related to water and food security, climate change impacts, precision agriculture, water resources monitoring and modeling, and the novel use of technologies for enhanced Earth system observation. The research undertaken in his group combines models and observations to answer questions on the distribution, variability and exchanges of water at local, regional and global scales, as well as the interactions with vegetation. CubeSats, unmanned aerial vehicles (UAVs) and in-situ monitoring techniques are all employed to monitor
<> water waves (2) <> waves (2) <> wearable devices (2)

Liquid Metal-Based Inertial Sensors for Motion Monitoring and Human Machine Interfaces

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B2 B3 A0215

In this dissertation, the development of novel practical resistive and capacitive-type inertial sensors using liquid metal as a functional proof mass material is presented. Utilizing the unique electromechanical properties of liquid metal, the novel inertial sensor design confines a graphene-coated liquid metal droplet inside tubular and 3D architectures, enabling motion sensing in single and multiple directions. Combining the graphene-coated liquid metal droplet with printed sensing elements offers a robust fatigue-free alternative material for rigid, proof mass-based accelerometers. Resistive and capacitive sensing mechanisms were both developed, characterized, and evaluated. Emerging rapid fabrication technologies such as direct laser writing and 3D printing were mainly adopted, offering a scalable fabrication strategy independent of advanced microfabrication facilities. The developed inertial sensor was integrated with a programmable system on a chip (PSoC) to function as a stand-alone system and demonstrate its application for real-time- monitoring of human health/ physical activity and for soft human-machine interfaces. The developed inertial sensor architecture and materials in this work offer a new paradigm for manufacturing these widely used sensors that have the potential to complement the performance of their silicon counterparts and extend their applications.

Wedyan Babatain

Wedyan Babatain is a doctoral candidate of MMH Labs in the Electrical Engineering program at KAUST. She has an interdisciplinary background obtaining her bachelor's degree in Biomedical Engineering from the University of Delaware, USA, in 2017, and her master's degree in Electrical Engineering from King Abdullah University of Science and Technology (KAUST), KSA, in 2019. Her research interests include sensors, actuators, microfluidics, and flexible and soft electronics for healthcare and environmental applications. She was a finalist at the 2022 SXSW Innovation Awards and has presented her
<> wearable technology (2) <> wearables (2) <> wind (2)

A Novel HVDC Architecture for Offshore Wind Farm Applications

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

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KAUST

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

Modeling where the wind blows

1 min read ·
A new statistical technique could be used to more accurately locate global wind resources.
<> wind energy (2) <> Wireless communication theory (2) <> wireless connectivity (2) <> wireless network (2) <> Wireless sensors (2) <> xstat research highlights (2) <> 2D materials characterization (1) <> 3D bioprinting (1) <> 3D design (1) <> 3D electrodes (1) <> 3D fabrication (1) <> 3D high-speed printing (1) <> 3D microstructures (1) <> 3D printed denatl brace (1) <> 3D printed localization system (1) <> 3D Shape Manipulation (1) <> 3D shapes (1) <> 3D understanding (1) <> 5G enabling technologies (1) <> 5G/6G (1) <> 6G On-chip reconfigurable intelligent surface (1) <> 6G On-chip reconfigurable transmitarray and phased array (1) <> academic convocation (1) <> Academic Operations (1) <> accidental faults (1) <> account protection (1) <> account sharing (1) <> Acoustic Absorption (1) <> acoustic noise (1) <> acoustic pulses (1) <> acoustic signals (1) <> Action Recognition (1) <> Action Recognition Challenge (1) <> Action understanding (1) <> Active Distribution Network (1) <> Adaptive modeling (1) <> Adaptive modulation and coding (1) <> ADC (1) <> Additive Schwarz methods (1) <> Adobe Creative Suite (1) <> advanced materials (1) <> Advanced Perception (1) <> aerodynamic simulations (1) <> aerospace information systems (1) <> Affective AI (1) <> Agent Management (1)