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<> engineering (3) <> fiber optics (3)

Color-Converting Luminescent Devices for High-Speed Optical Wireless Communication

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B3 L5 R5209

This dissertation advances optical communication systems by exploring and integrating novel luminescent materials, including MOFs, perovskite nanosheets and quantum dots, and organic fluorophores, to enhance speed, efficiency, and versatility in applications ranging from high-speed visible-light communication and ultraviolet free-space communication to underwater wireless optical communication and optical amplification.

Yue Wang

Ph.D. Candidate (former), Electrical and Computer Engineering
Yue Wang's research focuses on semiconductor optoelectronics, high-speed color-converting luminescent devices, and optical wireless communication.

Juan Manuel Marin Mosquera

Ph.D. Candidate (former), Electrical and Computer Engineering
Early stage researcher focused on laying the foundations for the emerging field of Integrated Sensing and Communications (ISAC). His work aims to incorporate smart sensing solutions leveraging machine learning-aided Distributed Fiber Optic Sensing (DFOS) into the next generation of fiber-based telecommunication networks, as well as their integration into the realm of the Internet of Things (IoT).
<> Finance (3)

The role of applied mathematics in finance

1 min read ·
“Sometimes there’s a strange dichotomy between applied mathematics and pure mathematics,” said Professor Raul Tempone, a founding KAUST faculty member and principal investigator of the University's Stochastic Numerics Research Group. “People think that applied math is simply the application of theory.” The argument is that applied math is just classified by its ends in the sense that one is trying to solve a real problem. Tempone argues that this doesn’t mean that new theories don’t need to be created. It also does not mean that the kinds of problems are less challenging than the ones faced in

Liliana Rivera

Liliana Rivera is the center manager for the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST).

Hamimah Supian

Hamimah Supian joined KAUST in August 2009 as one of the founding members of the university. She was the Business Manager for the Computational Bioscience Research Center (CBRC) before assuming the Senior Business Manager position for CEMSE in January 2014. Hamimah oversees the financial, administration and operation of the division. She had well over 25 years of experiences in finance and administration from diverse industries prior to joining KAUST.
<> Flexible and Disposable Wireless Sensors (3)

High Specificity Microwave Wearable Biosensors for Remote Health Monitoring

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B2/3 L0 R0215

This dissertation investigates an alternative route based on electromagnetic (EM) sensing to realize passive, label-free, and cost-effective wearable biosensors, addressing key limitations of existing technologies.

Fully Printed, Flexible and Disposable Wireless Sensors for Internet of Things Applications

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B9 L2 R2322

With the advent of wearable devices and internet of things (IoT), there is a new focus on sensing systems which can be bent so that they can be worn or mounted on non-planar objects.
HeadShot-Firas

Firas Fatani

Firas Fatani is an electrical engineer and researcher specializing in wireless sensing technologies, flexible electronics, and intelligent systems. His work focuses on advancing the design and integration of low-cost, battery-free, and printed microwave devices for health, environmental, and industrial monitoring applications. He is particularly interested in bridging electromagnetic design, material science, and data intelligence to develop innovative sensing platforms that enable smarter and more connected systems.
<> fluid-structure interactions (3)

Theory and Implementation of Novel Numerical Methods for Multiphysics Interface Problems

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B2/B3 L0 R0215

This thesis develops and analyzes Finite Element Methods (FEM) for multiphysics interface problems using the Fictitious Domain with Distributed Lagrange Multiplier (FD-DLM) framework. It introduces new families of stable mixed methods with discontinuous Lagrange multiplier spaces, studies both a priori and a posteriori error estimates, and designs multigrid preconditioners. Theoretical results are supported by numerical experiments.

Rolf Krause

Professor Rolf Krause is an experienced researcher and educator specializing in designing and analyzing algorithms to solve complex problems in scientific computing and machine learning.

Najwa Alshehri

Professional Interests Beyond academic and research pursuits, Najwa is deeply committed to mentoring and empowering female students to pursue careers in science and research. At KAUST, she engaged in initiatives that cultivate talent in mathematics, AI, and deep learning. Additionally, she placed significant emphasis on developing her leadership and entrepreneurial skills through specialized programs and certifications along with other trainings in Key Performance Indicators (KPI), Total Quality Management (TQM), and strategic planning.
<> flux-corrected transport (3)

Locally Discrete Maximum Principle DG finite element method for the transport equation

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B1 L4 R4214

In this talk we propose a Flux Corrected Transport (FCT)-like stabilization suitable for high-order Discontinuous Galerkin (DG) finite element discretizations. As a model problem we consider the multi-dimensional transport equation. The method guarantees that the solution satisfies a local Discrete Maximum Principle (DMP). A solution is said to satisfy a DMP locally if any degree of freedom is bounded with respect to the solution at the previous time step in some defined neighborhood.

Algebraic flux correction for finite element discretizations of hyperbolic conservation laws

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B1 L4 R4214

In this talk, we review some recent advances in the analysis and design of algebraic flux correction (AFC) schemes for hyperbolic problems. In contrast to most variational stabilization techniques, AFC approaches modify the standard Galerkin discretization in a way which provably guarantees the validity of discrete maximum principles for scalar conservation laws and invariant domain preservation for hyperbolic systems. The corresponding inequality constraints are enforced by adding diffusive fluxes, and bound-preserving antidiffusive corrections are performed to obtain nonlinear high-order approximations. After introducing the AFC methodology and the underlying theoretical framework in the context of continuous piecewise-linear finite element discretizations, we present some of the limiting techniques that we use in high-resolution AFC schemes. This presentation is based on joint work with Dr. Manuel Quezada de Luna (KAUST) and other collaborators.

Manuel Quezada De Luna

Research Scientist, Numerical Mathematics
Dr. Suleyman Ulusoy earned both his Ph.D in Mathematics in 2007 and his Master of Science in Applied Mathematics in 2003 from Georgia Institute of Technology in Atlanta, Georgia, USA. He earned both of his Bachelor’s degrees in Mathematics and Mathematics Education from the Middle East Technical University in Ankara, Turkey in 2000. He did postdocs in University of Oslo and University of Maryland. He is currently a faculty member in American University of Ras Al Khaimah.
<> food security (3) <> forecasting (3)

Statistical Analysis of Multi-day Solar Irradiance using a Threshold Time Series model

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B9 H2 R2325

Abstract The analysis of solar irradiance has important applications in predicting solar energy production from solar power plants. Although the sun provides every day more energy than we need, the variability caused by environmental conditions affects electricity production. Most of the existing statistical models to forecast solar irradiance are linear and highly depend on normality assumptions. However, solar irradiance shows strong non-linearity and is only measured during the day time. Thus, we propose a new multi-day threshold autoregressive (TAR) model to quantify the variability of the

Smart Meter Data-Driven Load Forecasting and Price Design in the Retail Market

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KAUST

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.

Cristian Felipe Jiménez Varón

Ph.D. Student, Statistics
Cristian Felipe Jiménez Varón is a Ph.D. candidate in the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Cristian obtained a master's degree in applied mathematics from the Universidad Nacional de Colombia Sede Manizales (UNAL), Colombia. He also holds dual bachelor's degrees in industrial engineering and chemical engineering from UNAL. Research Interests Cristian's research interests include the analysis of large volumes of data, statistical modeling and environmental statistics.
<> Fractional calculus (3)

Lilia Ghaffour

Research Interests Lilia Ghaffour is a Ph.D. candidate in the Division of Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) at KAUST. She has a master degree in Applied Mathematics from the University of Mostaganem (Mathematics and Computer Science), Algeria. She joined the Ph.D. degree program in Appl. Math. and Computational Sc. at King Abdullah University of Science and Technology (KAUST) in fall 2016. She is interested in the study of control and inverse problem for fractional partial differential equations. Education Profile August 2016: PhD candidate in the Division

Aslihan Kartci

Postdoctoral Research Fellow, Electrical and Computer Engineering
Education and Early Career Dr. Aslihan Kartci received her Ph.D. degree in Electronics from the Brno University of Technology, the Czech Republic in 2019 and M.S. degree from Yildiz Technical University, Turkey, in 2015. She was with the Research and Development Center of Komax Wire, Turkey from 2012 to 2014, engaged in software development of production planning systems, server management, project management for functional test machines. She was awarded with “Travel Grant” from IEEE flagship conference on Circuits and Systems, namely ISCAS 2015. She was „Congress Publicity Chair” of the

Asem Al Alwan

Asem Alalwan is a Ph.D. candidate in the Estimation, Modeling, and Analysis group (EMAN) supervised by Prof. Meriem Laleg at King Abdullah University of Science and Technology (KAUST).​ Asem has graduated with a bachelor degree in Electrical Engineering from King Fahad University of Petroleum and Minerals KFUPM) in 2014. He joined KAUST in 2014 and earned his Master degree in 2016.​ Research Interests Asem's research is focused in the area of control and design of Free-space optical (FSO) communication systems. FSO has emerged as a viable technology that offers a large capacity usage (data
<> Functional (3)

Waves Functional Materials - 2020-11-15

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KAUST

Wave functional materials are artificial materials that can control wave propagation as wish. In this talk, I will give a brief review on the progress of wave functional materials and reveal the secret behind the engineering of these materials to achieve desired properties. In particular, I will focus on our contributions on metamaterials and metasurfaces. I will introduce the development of effective medium, a powerful tool in modeling wave functional materials, followed by some illustrative examples demonstrating the intriguing properties, such as redirection, emission rate enhancement, wave steering and cloaking.

Functional Differential Equations in Models of Collective Behavior - Graduate Seminar

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B9 L2 R2322

The talk will give an overview of recent results for models of collective behavior governed by functional differential equations. It will focus on models of interacting agents with applications in biology (flocking, swarming), social sciences (opinion formation) and engineering (swarm robotics), where latency (delay) plays a significant role.

Functional Differential Equations in Models of Collective Behavior - Colloquium

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B4 L5 R5220

I will give an overview of recent results for models of collective behavior governed by functional differential equations. The talk will focus on models of interacting agents with applications in biology (flocking, swarming), social sciences (opinion formation) and engineering (swarm robotics), where latency (delay) plays a significant role. I will explain that there are two main sources of delay - inter-agent communications and information processing
<> Functional data (3)

Classification of Functional Data by Detecting the Discrepancy of Second Moment Structure of Scaled functions

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KAUST

This talk presents a new classification method for functional data. We consider the case where different groups of functions have similar means so that it is difficult to classify them based on only the mean function. To overcome this limitation, we propose the second moment based functional classifier (SMFC). Here, we demonstrate that the new method is sensitive to divergence in the second moment structure and thus produces lower rate of misclassification compared to other competitor methods. Our method uses the Hilbert-Schmidt norm to measure the divergence of second moment structure. One important innovation of our classification procedure lies in the dimension reduction step. The method data-adaptively discovers the basis functions that best capture the discrepancy between the second moment structures of the groups, rather than uses the functional principal component of each individual group, and good performance can be achieved as unnecessary variability is removed so that the classification accuracy is improved. Consistency properties of the classification procedure and the relevant estimators are established. Simulation study and real data analysis on phoneme and rat brain activity trajectories empirically validate the superiority of the proposed method.

Zhuo Qu

Ph.D. Student, Statistics
Zhuo Qu is a PhD candidate in statistics, under Prof. Marc Genton. Zhuo likes to use statistics methods to interpret the data in the applications and find the new possibility of exploring the new statistics model. Being eager to learn and experience the uncertainty in the research and life, she also like chatting, swimming and piano. Her goal is to be a spare-time pianist among professional statisticians. Education and Early Career King Abdullah University of Science and Technology, Thuwal, January 2019 - December 2022, PhD in Statistics King Abdullah University of Science and Technology

Jonatan A. González

Postdoctoral Research Fellow, Statistics
Jonatan's research interests lie between spatial statistics and coding, emphasising point processes, epidemiology, infectious disease modelling and, generally, application-focused methods. He has a bachelor's degree and a master's background in mathematics. He completed his PhD in spatial and spatio-temporal point processes at the University Jaume I. Jonatan's research projects include techniques for dealing with point patterns: replicated observations, spatio-temporal analysis, graphical methods, hypothesis testing, experimental design and local characteristics. In addition to the core
<> Gallium oxide (3) <> generalized Sobolev inequalities (3)

Professor Peter Markowich Has Been Awarded The "John Von Neumann Visiting Chair" At The Technical University Of Munich

1 min read ·
Professor Peter Markowich has been awarded the "John Von Neumann Visiting Chair" at the Technical University of Munich. The John von Neumann Visiting Professorship allows outstanding scientists to spend a semester at the TUM Center for Mathematics.

Professor Markowich elected to the European Academy of Sciences and Arts

1 min read ·
KAUST Distinguished Professor of Applied Mathematics and Computational Science Dr. Peter Markowich has been named a member of the European Academy of Sciences and Arts (EASA). He will officially be inducted as a member at the organization's annual inauguration ceremony in early 2023.

Peter Markowich

Al-Khawarzmi Distinguished Professor, Applied Mathematics and Computational Science
A distinguished professor of applied mathematics and computational science, Dr. Markowich is the author of over 200 publications in leading international journals and circa 14,000 citations.
<> generative adversarial network (3)

Stylistic and spatial disentanglement in GANs

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KAUST

This dissertation tackles the problem of entanglement in Generative Adversarial Networks (GANs). The key insight is that disentanglement in GANs can be improved by differentiating between the content, and the operations performed on that content. For example, the identity of a generated face can be thought of as the content, while the lighting conditions can be thought of as the operations.

Yazeed Alharbi

Yazeed Alharbi is a Ph.D. candidate under the supervision of Prof. Peter Wonka at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career In 2015, Yazeed obtained his bachelor degree from Purdue University in the computer graphics and visualization track, with a minor in philosophy. In 2018, he received his master degree from King Abdullah University of Science and Technology (KAUST). He mainly learned about computer vision and the process of publication in that field. Research Interest Currently, Alharbi research is focused

Cheng Zheng

Cheng Zheng is a Software Engineer Consultant working with Professor Bernard Ghanem in the Image and Video Understanding Lab (IVUL) in the Visual Computing Center at King Abdullah University of Science and Technology (KAUST). Education and Early Career Cheng Zheng received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications (BUPT), China, in 2009. He received his Master's degree from the University of Chinese Academy of Sciences (UCAS), China, In 2012. Before joining KAUST, in 2012, he worked as a software engineer at NetEase Games in China. In
<> genome sequencing (3) <> geometric computing (3)

5-axis flank CNC machining of free-form surfaces using custom-shaped tools

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B4 L5 R5209

In this talk, I will discuss our recent advances in approximation of free-form surfaces by motions of curvature varying tools in the context of 5-axis flank CNC machining. In particular, I will discuss path-planning strategies using fixed tools, or custom-shaped ones, and on an example of spiral bevel gears will demonstrate even more efficient variant of flank machining, called double-flank.

Daoming Liu

Postdoctoral Research Fellow, Computer Science
Daoming Liu is a Postdoctoral Research Fellow working with Professor Helmut Pottmann at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career Daoming Liu obtained his Ph.D. degree from the University of Chinese Academy of Sciences (UCAS). During his Ph.D., he spent one year at TUDelft as a visiting doctoral student. Before joining VCC/KAUST, he worked at ShanghaiTech University as a Research Assistant Professor. Research Interest Daoming Liu’s research was focused on physical simulation, geometric computing and their

Cheng Wang

Ph.D. Student, Computer Science
Cheng Wang received his PhD in the Computer Science Program under the supervision of Professor Helmut Pottmann at the Visual Computing Center (VCC). He is now an Assistant Professor at the University of East Anglia in the United Kingdom Education and Early Career Cheng received his Bachelor's Degree in Automation from Tsinghua University, China in 2016. He joined KAUST to continue his studies and received his Master's Degree in Computer Science in 2018. Research Interest Cheng is mainly interested in Computer Graphics, Geometric Computing, and Machine Learning. Education Profile M.S., Computer
<> Georgia Tech (3)

Implantable and Wearable Microelectronic Devices to Improve Quality of Life for People with Disabilities

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B3 L5 R5209

Implantable medical devices (IMD) and neuroprostheses are finding applications in new therapies thanks to advancements in microelectronics, sensors, RF communications, and medicine, which have resulted in embedding more functions in IMDs that occupy smaller spaces down to millimeters and consume less power, while offering therapies for more complex diseases and disabilities. I will address the latest developments in key building blocks for state-of-the-art IMDs.

Introduction to High Performance Computational Chemistry with an Application of Hierarchical Matrices

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B2 B3 A0215

This talk begins with an introduction to quantum chemistry for HPC researchers. We discuss the main computational kernels, how their performance is limited by various bottlenecks, and algorithms and implementations that improve performance. One particular kernel is the calculation of the Coulomb matrix. Whereas the fast multipole method (FMM) can be used to rapidly compute the Coulomb potential for sets of point charges, continuous variants of FMM were developed in the 1990s for sets of charge distributions that arise in quantum chemistry.

Hommood Alrowais

Hommood Alrowais is a Ph.D. student based in the department of electrical and computer engineering at the Georgia Institute of Technology (Georgia Tech) in Atlanta, Georgia, U.S. Alrowais graduated from KAUST in 2010 as part of the University's first graduating class with a master's degree in electrical engineering. His current research is focused on bio-inspired sensors. "The sensor I am developing is based on the semicircular canal in the inner ear. This tiny organ is responsible for sensing angular rotation in three axes, and it also stabilizes gaze and allows for a smoother reading
<> GPU (3)

Use Mathematics and get a SPARQL Query Engine (almost) for Free! It’s MAGiQ!

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B9 L2 H1 R2322

Existing RDF engines are designed for specific hardware architectures; porting to a different architecture (e.g., GPUs) entails enormous implementation effort. We explore sparse matrix algebra as an alternative for designing a portable, scalable and efficient RDF engine.

Device accelerated solvers for PDEs. Current status and future perspectives

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B5 L5 R5220

In the next months, KAUST expects to place into service Shaheen-3, a supercomputer with a GPU partition whose planned 1 Exaflop/s HPL AI capability would rank it in the Top 6 globally if delivered today.

BORG team win at the KAUST-NVIDIA GPU Hackathon 2022

1 min read ·
Congratulations to Senay Kafkas, Maxat Kulmanov and Fernando Zhapa Camacho of the Bio-Ontology Research Group (BORG) on winning at the KAUST-NVIDIA GPU Hackathon 2022. The 8th edition of the Hackathon on Accelerating Scientific Applications using Graphical Processing Units (GPUs) was held at King Abdullah University of Science and Technology (KAUST), twelve teams of students and researchers enjoyed the opportunity to accelerate their codes in GPU’s under the guidance of expert mentors of NVIDIA, Codee, KAUST Supercomputing Lab (KSL) and KAUST core labs.
<> Hand Gestures Recognition (3)

Stochastic Optimization in Target Positioning and Location-based Applications

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KAUST

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.

Mohammed Hussain AlSharif

Postdoctoral Research Fellow, California Institute of Technology (Caltech)
Dr. Mohammed AlSharif is a Postdoctoral Fellow at the California Institute of Technology (Caltech) and a recipient of the KAUST Ibn Rushd Fellowship. His research bridges Riemannian geometry, statistical estimation, and learning for autonomous systems, with applications to high-accuracy pose estimation and robotics.

Hui Chen

Ph.D. Student (former), Electrical and Computer Engineering
Ph.D. degree Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST) ,Currently a Ph.D. student working on localization & tracking and gesture recognition.
<> haps (3)

Bang Huang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Bang Huang works as a postdoctoral fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Bang Huang received the M.S. degree (with honors) in electrical engineering and Ph.D degree in information and communication engineering from the School of Information and Communication Engineering (SICE), University of Electronic Science and Technology of China (UESTC), Chengdu, China, in

Xiaowei Pang

Postdoctoral Research Fellow, Electrical and Computer Engineering
Xiaowei Pang is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Xiaowei Pang received her B.S. degree in Telecommunication Engineering from Northwestern Polytechnical University, Xi'an, China, in 2018, and her Ph.D. degree in Information and Communication Engineering from Dalian University of Technology, Dalian, China, in 2024. From 2021 to 2022
H

Hussein Al-Shatri

I chose KAUST because of its reputation for excellence in research and its recent emphasis on applied research. With my extensive background in both academic research and industrial development, I am excited to contribute my experience and ambition. My goal is to foster new ideas and develop innovative prototypes in the field of wireless communications, which will undoubtedly enhance people's lives.
<> health (3) <> health surveillance (3) <> Heterogeneous networks (3)

Wireless Network Intelligence @ the Edge

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B1 L3 R3119

In just a few years, breakthroughs in machine learning (ML) and particularly deep learning have transformed every aspects of our lives from face recognition, medical diagnosis, and natural language processing. This progress has been fueled mainly by the availability of more data and more computing power. However, the current premise in classical ML is based on a single node in a centralized and remote data center with full access to a global dataset and a massive amount of storage and computing, sifting through this data for inference.

Rachad Atat

Rachad Atat was a CTL lab member and graduated from KAUST. Then, he joined the KTH Royal Institute of Technology (KTH) as a PhD student. Selected Publications Book Chapters: M. Z. Shakir, R. Atat, and M. -S. Alouini, "Interference suppression capabilities of smart cognitive-femto networks (SCFN),” Chapter in Self-Organization and Green Applications in Cognitive Radio Networks, Al-Dulaimi, A., Cosmas, J., and Mohammed, A. (Eds), IGI Global, 2012. M.S. Thesis: R. Atat, "Cooperative Content Distribution over Wireless Networks for Delay and Energy Efficiency," King Abdullah University of Science

Laila Hesham Afify

Postdoctoral Research Fellow (former), Electrical and Computer Engineering
Postdoctoral Research Fellow Electrical and Computer Engineering (KAUST), Assistant Professor, School of Engineering and Applied Sciences, Nile University, Egypt
<> Higher Education (3)
Rana Aleryani CEMSE KAUST

Rana Aleryani

Rana has a background in the education and IT sectors. She has a Bachelor degree in computer science and a Master's degree in Business Administration. Before joining KAUST as a Graduate Program Coordinator for the Electrical Engineering Program in March 2018, Rana worked as Account Manager at Oracle Corporation, Jeddah and Dubai. Prior to that, she worked in the Education sector in different capacities.

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
KAUST-CEMSE-Administrative Staff-Graphic Designer-Marta Hentunen

Marta Hentunen

Higher Education Professional working in university setting for nearly 15 years. Joined KAUST in August 2014 and worked as a graphic designer in the Presidents Office, at KAUST Marketing and Communication Office, and since September 2017 for CEMSE Division. Detail-oriented and results-driven Graphic Designer producing high-quality graphics, illustrations and layouts for websites, social media, and print. I've been working with scientific disciplines, efficiently expressing complex data and ideas through deliverables like scientific posters and presentations, infographics, animations, and other
<> Homogenization (3) <> Hyperbolic PDEs (3)

On Strong Stability of Runge-Kutta Methods

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B1 L4 R4214

Runge-Kutta methods are classical and widespread techniques in the numerical solution of ordinary differential equations (ODEs). Considering partial differential equations, spatial semidiscretisations can be used to obtain systems of ODEs that are solved subsequently, resulting in fully discrete schemes. However, certain stability investigations of high-order methods for hyperbolic conservation laws are often conducted only for the semidiscrete versions.

Unveiling the potential of energy/entropy stable numerical methods for hyperbolic/mixed hyperbolic-parabolic PDEs

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B9 L2 H1

Abstract The demand for increasingly multidisciplinary reliable simulations, for both analysis and design optimization purposes, requires transformational advances in individual components of future PDEs solvers. At the algorithmic level, hardware compatibility and efficiency are of paramount importance in determining viability on future hardware. However, equally important (if not more so) is provable algorithmic robustness which becomes progressively more challenging to achieve as problem size and physics complexity increase. We show that rigorously designed adaptive semi- and fully-discrete

Xiaokai Huo

Postdoctoral Research Fellow, Applied Mathematics and Computational Science
Short Bio Xiaokai Huo received a bachelor degree in Mathematics from Tsinghua University, China in 2012 and a Ph.D degree in Mathematics from Tsinghua University China, 2017. He was a Postdoctoral fellow in the Applied PDE group at KAUST in the period October 2017 - October 2020. In October 2020 he joined the Institute of Analysis and Scientific Computing, Vienna University of Technology as a Postdoctoral Fellow. Xiaokai Huo's research interests lie in the area of Hyperbolic PDEs, Fluid Mechanics and Non-equilibrium Thermodynamics. Education Profile Ph. D. Mathematics, Tsinghua University
<> ICT (3) <> Imaging (3) <> industrial control systems (3)

Cybersecurity of Industrial Control Systems - Challenges and Research Directions

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B9 L2 H2 H2.

This Distinguished Lecture is part of the CS Graduate Seminars. Abstract Industrial Control Systems play an important role in monitoring, controlling, and automating critical infrastructure such as water, gas, oil, and electricity. Recent years have seen a number of high-profile cyber attacks on such infrastructure, exemplified by Triton, Colonial Pipeline, and the Ukrainian Power Grid attacks. This naturally begs the question: how should we manage cyber security risks in such infrastructure on which the day-to-day functioning of our society relies? What are the complexities of managing

Ioannis (Yannis) Zografopoulos

Ioannis Zografopoulos received his Ph.D. at the Computer, Electrical, and Mathematical Sciences and Engineering Division (CEMSE) of King Abdullah University of Science and Technology (KAUST) in 2023. Prior, he graduated with a B.Eng. and M.Eng. degrees in Computer, Communications, and Network Engineering, and an M.Sc. degree in Electrical and Computer Engineering from the University of Thessaly, Volos, Greece, in 2014 and 2015, respectively. His research interests include cyber-physical systems security, with an emphasis on embedded systems for industrial, distributed energy, and power grid
<> Information Technology (3)

KAUST Ph.D. candidate wins first place at IEEE SSD’21 PhD Students Contest

1 min read ·
KAUST Ph.D. candidate Mohamed Abdelwaheb Bahloul recently won first place at the IEEE International Multi-Conference on Systems, Signals and Devices 2021 (SSD’21) PhD Students Contest. The contest provided a showcase for students’ original work related to electrical engineering and information technology.

Professor Elnozahy Elected as Fellow of the National Academy of Inventors

1 min read ·
KAUST Professor of Computer Science Elmootazbellah Elnozahy has been elected to the rank of National Academy of Inventors (NAI) Fellow. NAI fellows are selected based on the number and significance of patents they are co-inventors; the patents must also have stemmed from a university-based research program.

Naseer Aijaz

Naseer Aijaz is a founding member of KAUST and he joined the university in July 2009. Prior to joining KAUST, Naseer worked as an Office Manager for the Provost and President Office at the Alfaisal University in Riyadh, Saudi Arabia. He has a Masters Degree in Operations Management, a Bachelor Degree in International Business, a spectrum of training certifications in project management, SAP ERP, Enterprise Data Warehouse (EDW), Business Intelligence, Power BI, and Diploma in Network-Centered Computing. As the Data Analytics Specialist, Naseer is responsible to work with financial and non
<> Information theory (3)

Mohamed A. Gaafar

Mohamed A. Gaafar was a CTL lab member and graduated from KAUST. Then, he joined the Technical University of Berlin as a PhD student. Selected Publications Selected Conferences 1. M. Gaafar, O. Amin, W. Abediseid, and M.-S. Alouini, “Sharing the licensed spectrum of full-duplex systems using improper Gaussian signaling,” in Proc. IEEE Global Commun. Conf. (GLOBCOM), San Diego, USA, Dec. 2015, pp. 1–6. 
 2. M. Gaafar, M. G. Khafagy, O. Amin, and M.-S. Alouini, “Improper Gaussian signaling in full-duplex relay channels with residual self-interference,” in Proc. IEEE Int. Conf. Commun. (ICC)

Anas Chaaban

Postdoctoral Research Fellow, Communication Theory Lab
Anas Chaaban was a Postdoctoral Research Fellow in CTL(Communication Theory Lab), KAUST. He now is an assistant professor in University of British Columbia (UBC), British Columbia , Canada Selected Publications Ph.D. Thesis A. Chaaban, “Relaying for Interference Management,” Faculty of Electrical Engineering and Information Technology, Ruhr-University of Bochum, Bochum, Germany, July 2013. M.S. Thesis A. Chaaban, “Some Aspects of Adaptive Decoding of Concatenated Codes,” Institute of Telecommunications and Applied Information Theory, University of Ulm, Ulm, Germany, June 2009. Journal

Abdullah Al-Nafisah

Master student at the Information Science Lab (ISL), in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST).
<> inkjet printing (3)

Sumeyra Agambayev

Sumeyra Agambayev worked as a Researcher at Integrated Microwaves Packaging Antennas & Circuit Technology (IMPACT) Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Sumeyra's research interests included BioSensors, Microfluidics, ​Inkjet printing.

Bauyrzhan Krykpayev

Bauyrzhan Krykpayev obtained his Master's degree in Electrical Engineering under the supervision of Professor Atif Shamim at Integrated Microwaves Packaging Antennas & Circuit Technology (IMPACT) Research Group at King Abdullah University of Science and Technology (KAUST). Master's Thesis Title: A WiFi Tracking Device Printed Directly on Textile for Wearable Electronics Applications. Research Interests Baur's research interests included RFID and Inkjet printing. Education Profile ​B.Sc. Electrical Engineering(cum laude), USC, USA, 2011​. M.SC. in Electrical Engineering from King Abdullah

Adnan Ahmad Khan

Adnan Ahmad Khan obtained his Master's degree in Electrical Engineering under the supervision of Professor Atif Shamim at Integrated Microwaves Packaging Antennas & Circuit Technology (IMPACT) Research Group at King Abdullah University of Science and Technology (KAUST). Currently, Adnan is working as a Control Systems Engineer at Saudi Aramco, Saudi Arabia. Research Interests Adnan's research interests included Rectennas, Energy Harvesting using RF Energy and Inkjet printing of Electronics. Education Profile B.Eng. 2011, Electrical and Electronic Engineering, Nanyang Technological University
<> INLA (3)

Raphaël Huser’s article among the top downloaded articles in Springer’s Environmental Sciences Journals

1 min read ·
Luigi Lombardo, Thomas Opitz, and Raphaël Huser’s article “Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster”, published in the scientific journal Stochastic Environmental Research and Risk Assessment (SERRA), in July 2018, is among the top downloaded articles in Springer’s Environmental Sciences Journals for the year 2018. Huser is an Assistant Professor of statistics in the CEMSE division and principal investigator of the Extreme Statistics (extSTAT) Research Group at KAUST.

Jonatan A. González

Postdoctoral Research Fellow, Statistics
Jonatan's research interests lie between spatial statistics and coding, emphasising point processes, epidemiology, infectious disease modelling and, generally, application-focused methods. He has a bachelor's degree and a master's background in mathematics. He completed his PhD in spatial and spatio-temporal point processes at the University Jaume I. Jonatan's research projects include techniques for dealing with point patterns: replicated observations, spatio-temporal analysis, graphical methods, hypothesis testing, experimental design and local characteristics. In addition to the core

Daniela Castro-Camilo

Postdoctoral Research Fellow, Statistics
Dr. Daniela Castro-Camilo was a postdoctoral fellow in the Extreme Statistics Research Group of Prof. Raphaël Huser from November, 2015, to May, 2019, doing research on the theory and applications of multivariate and spatial extremes. After her postdoc at KAUST, Daniela moved to the University of Glasgow, United Kingdom, where she embraced an academic career by becoming a Lecturer (equivalent to Assistant Professor in the UK) of Statistics. See her personal webpage. Education and early career Daniela Castro-Camilo received her Ph.D. from Pontificia Universidad Católica de Chile in August 2015
<> Integrated Photonics technology (3)

Mutibah Alanazi

Mutibah’s research focuses on quantum optics, optoelectronics, and nanophononics, with an emphasis on developing scalable quantum optical technologies. During her PhD at the University of Oxford, she explored quantum coherent emission, polariton condensation, and photon bunching in low-dimensional systems. She has extensive expertise in advanced laser systems, cryogenic techniques, microcavity systems, and material modeling, contributing to several notable publications in the field of condensed matter physics. Research interests Mutibah's research focuses on developing cavity-coupled spin

Integrated Photonic Devices for Sensing and Telecom Applications

Prof. Hugo E. Hernandez Figueroa, University of Campinas (UNICAMP)

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B3 L5 R5209

This talk will be focused on Integrated Photonics technology, which demands strong and robust confinement of light in order to attain the maximum possible integration of photonics devices on a single chip. Keeping this in mind, three applications based on LEMAC’s recent developments will be presented in this talk.

Toward scalable and high performance on-chip light source for integrated silicon photonics

Chen Shang, Postoctoral Researcher Fellow, University of California Santa Barbara

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B9 L2 R2322

Monolithic integration of quantum dot (QD) gain materials onto Si photonic platforms via direct epitaxial growth is considered as the ultimate solution for on-chip light sources.
<> intelligent reflecting surfaces (3)

Gyan Deep Verma

Postdoctoral Research Fellow, Electrical and Computer Engineering
Gyan Deep verma works as a postdoctoral fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Gyan Deep Verma received his B.Tech. degree in Electronics Engineering from Harcourt Butler Technological Institute, Kanpur, Uttar Pradesh, India, in 2015, and his M.Tech. degree in Communication Systems Engineering from the Indian Institute of Technology (IIT) Patna, Bihar, India, in

Waqas Aman

Visiting Student (former), Electrical and Computer Engineering
Remote Internship at King Abdullah University of Science and Technology (KAUST).

Alice Faisal

Visiting Student (former), Electrical and Computer Engineering
Visiting Student at King Abdullah University of Science and Technology (KAUST), chair of IEEE women in engineering affinity group at Effat University student branch.
<> International Supercomputing Conference (3) <> internet of things security (3)

BBDS: A Privacy-preserving Blockchain-Based Data Sharing System

Prof. Jin Li, Computer Science, Guangzhou University

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B1 L4 R4214

Abstract Nowadays, the devices in the Internet of Things have been widely used. These devices generate a huge amount of sensitive data, which are susceptible to cyber attacks. In this talk, we introduce an efficient blockchain based approach with several computational models of physically unclonable functions (denoted by PUF model). The presented protocol aims to guarantee the authentication of the devices with fast verification process. Furthermore, the combination of Blockchain and PUF motivates us to propose an efficient protocol that guarantees data provenance and data integrity in IoT

Maha Al-Aslani

Ph.D. Student, Computer Science
Maha Al-Aslani is a Ph.D. student under the supervision of Prof. Basem Shihada at the Networking Research Lab (NETLAB) in King Abdullah University of Science and Technology (KAUST). Maha received her bachelor's degree in Information Technology from King Abdulaziz University (KAU), and a master's degree in Computer Science from King Abdullah University of Science and Technology (KAUST) Saudi Arabia. Thesis title: Securing Internet of Things. Master's Thesis title: " Green Frame Aggregation Scheme for IEEE 802.11n Networks ". Education Profile M.Sc., Computer Science, KAUST, Saudi Arabia, 2015

Ioannis (Yannis) Zografopoulos

Ioannis Zografopoulos received his Ph.D. at the Computer, Electrical, and Mathematical Sciences and Engineering Division (CEMSE) of King Abdullah University of Science and Technology (KAUST) in 2023. Prior, he graduated with a B.Eng. and M.Eng. degrees in Computer, Communications, and Network Engineering, and an M.Sc. degree in Electrical and Computer Engineering from the University of Thessaly, Volos, Greece, in 2014 and 2015, respectively. His research interests include cyber-physical systems security, with an emphasis on embedded systems for industrial, distributed energy, and power grid
<> intrusion detection (3) <> intrusion tolerance (3) <> inverse scattering (3)

Efficient and Accurate Numerical Techniques for Sparse Electromagnetic Imaging

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KAUST

In this thesis, efficient solutions are sought out to fundamental problems in Electromagnetic (EM) imaging that determines the shape, location, and material properties of an (unknown) object of interest in an investigation domain from the scattered field measured away from it. The solution of an EM inverse scattering problem inherently poses two main challenges: (i) non-linearity, since the scattered field is a non-linear function of the material properties and (ii) ill-posedness, since the integral operator has a smoothing effect and the number of measurements is finite in dimension and they are contaminated with noise. The non-linearity is tackled incorporating a multitude of techniques (ranging from Born approximation (linear), inexact Newton (linearized) to complete non-linear iterative Landweber schemes) that can account for weak to strong scattering problems. The ill-posedness of the EM inverse scattering problem is circumvented by formulating the above methods into a minimization problem with a sparsity constraint, which assumes that the dimension of the unknown object relative to the investigation domain is much smaller. Numerical experiments, which are carried out using synthetically generated measurements, show that the images recovered by these sparsity-regularized methods are sharper and more accurate than those produced by existing methods. The methods developed in this work have potential application areas ranging from oil/gas reservoir engineering to biological imaging where sparse domains naturally exist.

Sadeed Bin Sayed

Sadeed Bin Sayed is a Ph.D. candidate in Electrical engineering at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Hakan Bagci. He received his B.Tech. degree in electronics and communication engineering from the National Institute of Technology Calicut, Calicut, India, in 2004, and the M.Tech. degree in communications engineering from the Indian Institute of Technology Delhi, New Delhi, India, in 2007. From July 2007 to May 2008, he worked as a Member with Technical Staff Digibee Microsystems, Bangalore, India. In May 2008, he joined as an

Ali Imran Sandhu

Education Ph.D. Student, Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, 2010-present M.S., Communication Engineering, Chalmers University of Technology Sweden, Sweden, 2008-2010 B.S., Electronics Engineering, Comsats University Islamabad, Pakistan, 2003-2007 Professional Appointments Research Engineer, European Project FLEXWIN, University of Calabria, Italy, September 2011 Lecturer, Electrical Engineering Department, Comsats University Islamabad (CUI), Lahore, Pakistan, October 2007 Research Interests Computational
<> KAUST (3)

Nanomaterials and Nanostructure Based Energy Efficient Edge and Fluidic Computing for Internet of Things Applications

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B9 L2 H1

In this talk, I will address these questions with a focus on smart and multifunctional nanomaterial-based memory devices than can sense different physical qualities of the environment (Memsors) in addition to pressure-driven microfluidic logic gates which can process and analyze non-electronic media in an attempt to explore, enable and empower a wider range of IoT applications.

Aerospace Systems Research at KAUST, an uplifting experience

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KAUST

Aerospace Engineering is the source of much dreaming and worrying in most people's imagination. As such, it constitutes a marvelous support for the development and application of numerous disciplines, chief among them are aerodynamics, structures, flight and orbital mechanics. With time however, information technologies are progressively becoming the costliest activity within the aerospace engineering systems design phase. Indeed, they stand as the core elements of avionics systems, airline operations, air traffic control, spacecraft engineering, and planetary exploration, among others. Such subjects have been bringing much joy and teaching many lessons to your speaker for the past 30 years and will keep doing so, hopefully, for the next three decades.

Solving the grandest of challenges

1 min read ·
Around the world, scientists, researchers and engineers seek to develop sustainable alternatives to the burning of fossil fuels. Some explore the kinetic energy of wind, gravity or water. Others capture excited electrons using photosensitive materials. William Tang, a principal research physicist at the Princeton Plasma Physics Laboratory at Princeton University, wants to power the world using the chemical reaction that stars run on—nuclear fusion—and he believes deep learning is a key.
<> KFUPM (3)

Alumni Focus: Albara Alauhali

1 min read ·
KAUST alumnus Albara Bin Mousaed Alauhali is currently the executive advisor and director of strategic projects at the National Identity Enhancement Program, a program aimed at achieving Saudi Vision 2030.

Imran Shafique Ansari

Imran Ansari graduated from KAUST in March 2015 with a Ph.D. in electrical engineering and joined Texas A & M at Qatar, Doha, Qatar, as a PDRA Postdoc Research Fellow after graduation, then British University in Oman, Muscat, Oman, as Assistant Professor, and then in August 2018 the University of Glasgow, Scotland, UK. He describes himself as an optical wireless communications enthusiast who works towards enhancing current wireless connectivity to provide more secure means of wireless information transfer. "For wireless information transfer—in which I have been involved recently—to have a

Albara Alauhali

M.S. Student, Computer Science
KAUST alumnus Albara Bin Mousaed Alauhali is currently the executive advisor and director of strategic projects at the National Identity Enhancement Program, a program aimed at achieving Saudi Vision 2030. Alauhali graduated from KAUST in December 2011 with a master's degree in computer science with a specialization in theoretical computing and algorithms. He received his undergraduate degree with first-class honors in computer science from King Fahd University of Petroleum and Minerals. After beginning his career in cyber security, Alauhali then moved on to become enrichment program
<> knowledge discovery (3)

AI4GH Seminar Series | Predicting Protein Function and Phenotype Associations

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B2 R5220

The amount of available protein sequences is rapidly increasing, mainly as a consequence of the development and application of high ​throughput sequencing technologies in the life sciences.

CEMSE Big Data Open Day shows off fascinating discoveries

1 min read ·
The fifth-anniversary event marked CEMSE's biggest successes and featured 20 KAUST discoveries, with more than 1,000 visitors from the community attending the event."Big data has many applications: to understand medicine better; to manage food supplies, and to connect objects. Data is at the center of everything," said Dean Mootaz Elnozahy of the University's Computer, Electrical, Mathematical Science and Engineering (CEMSE) Division at the CEMSE Big Data Open Day held on December 4, 2016.

New Book "Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining" of Professor Moshkov and His Former Students is Published by Springer

1 min read ·
A new book - "Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining" by Hassan AbouEisha, Talha Amin, Igor Chikalov, Shahid Hussain, and Mikhail Moshkov - was recently published by Springer.
<> knowledge representation (3)

Knowledge-based methods in life sciences

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B9 L2 H2 R2325

In my research I aim to understand how formalized knowledge bases can be used to systematically structure and integrate biological knowledge, and how to utilize these formalized knowledge bases as background knowledge to improve scientific discovery in biology and biomedicine. To achieve these aims, I develop methods for representing, integrating, and analyzing data and knowledge with the specific aim to make the combination of data and formalized knowledge accessible to data analytics and machine learning in bioinformatics. Biomedicine, and life sciences in general, are an ideal domain for knowledge-driven data analysis methods due to the large number of formal knowledge bases that have been developed to capture the broad, diverse, and heterogeneous data and knowledge.

Robert Hoehndorf

Associate Professor, Computer Science
Robert Hoehndorf is an Associate Professor of Computer Science at KAUST. His research focuses on bioinformatics, knowledge representation and reasoning, Semantic Web technologies, and neuro-symbolic methods.

Olga Mashkova

Ph.D. Student, Computer Science
PhD student in Computer Science. Research interests: machine learning, bioinformatics, mathematics, knowledge representation and reasoning, deep learning, algorithms.
<> Large Language Models (3) <> large-scale computing (3) <> large-scale simulation (3)

Interactive High-Quality Visualization of Large-Scale Particle Data

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B2 L5 R5209

Large-scale particle data sets, such as those computed in molecular dynamics (MD) simulations, are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry.

IXPUG Middle East Conference 2018 at KAUST

1 min read ·
KAUST will host the first Middle East meeting of the Intel eXtreme Performance Users Group (IXPUG), 22-25 April 2018. Alan Gara, Intel Fellow, will give the keynote address. Alex Heinecke (Intel), Adrian Tate (Cray), Vincent Etienne (Aramco), and Taisuke Boke (Tsukuba University) will give invited talks.

Hakan Bagci

Professor Bagci is a highly accomplished researcher in the field of computational electromagnetics (CEM). His research focuses on the theoretical and applied aspects of CEM.
<> laser physics (3)

Light management in non-Hermitian media

Dr. Waqas Ahmed, Electrical Engineering, King Abdullah University of Science and Technology

-

KAUST

Structured media provide the momentum compensation for the scattering of waves. It is well-known that nano-scale modulations of the refractive index may lead to a temporal and spatial control over light propagation. Yet, also engineering the gain and loss profile uncovers analogous shaping effects. However, only the interplay between both the refractive index and gain and loss modulations introduces unidirectionality in light management. Thus, non-Hermitian optics has become one of the most fertile grounds in optics. A generalized Hilbert transform allows tailoring the two quadratures of the complex permittivity to design periodic or disordered non-Hermitian media, holding either global or local unidirectionality following arbitrary vector fields to tailor the flow of light. The method allows restricting the permittivity within realistic values rendering it suitable for applications.

Waqas Waseem Ahmed

Postdoctoral Research Fellow, Applied Mathematics and Computational Science
Erasmus Mundus Joint Doctorate in Photonics Engineering, Universitat Politècnica de Catalunya (Spain), Universita degli Studi di Firenze (Italy), Karlsruhe Institute of Technology (Germany), Université Paul Cèzanne Aix Marseille III (France).(2018) MS in Electrical Engineering, King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. (2014) BS in Electronic Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), Pakistan. (2009) Research Interests Non-Hermitian Photonics, Nonlinear Optics, Machine Learning, Laser Physics.

Martins Bruvelis

Senior Information Technology Specialist, Computer, Electrical and Mathematical Sciences and Engineering
Martins is a Tier 3 IT Specialist with a background in quantum engineering and data science. He leverages analytical, multidisciplinary, and data-driven approaches to drive innovation and efficiency within the IT infrastructure. He excels at full-stack development, identifying complex problems' root causes and developing impactful long-term solutions within a broad area of competence.
<> Laser-scribed graphene (3)
Mario Soto

Mario Soto Martinez

Ph.D. Student, Bioengineering

Multifunctional Flexible Laser-Scribed Graphene Sensors for Resilient and Sustainable Electronics

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KAUST

This dissertation introduces flexible, lightweight, and robust Laser-Scribed Graphene (LSG) sensor solutions for detecting various physical parameters, such as strain, flow, deflection, force, pressure, temperature, conductivity, and magnetic field. Multifunctionality was obtained by exploiting the direct laser scribing process combined with the flexible nature of polyimide and the piezoresistivity of porous graphene. The outstanding properties of LSG, such as low cytotoxicity, biocompatibility, corrosion resistance, and ability to function under extreme pressure and temperature conditions, allowed targeting diverse emerging applications.

Altynay Kaidarova

​Altynay has pursued an academic career in Electrical Engineering in different countries, such as Kazakhstan, Singapore, the United Kingdom, and Saudi Arabia. She considers herself a citizen of the world upholding scientific achievements, passion, inspiration, diversity, integrity, and openness. In 2010 the student attained Bolashak International Scholarship which was awarded to high-performing students from Kazakhstan. She has then successfully completed the foundation at Nanyang Technological University in Singapore and obtained a first honor degree in Electronics and Communication
<> LiDAR (3) <> low power digital circuit (3)

CEMSE New Faculty: Ahmed Eltawil, Professor, Electrical Engineering

1 min read ·
Professor of Electrical Engineering, Ahmed Eltawil, recently joined the KAUST CEMSE Division from the University of California (UCI), Irvine, where he had worked for 14 years prior. At UCI, Eltawil worked in the Department of Electrical Engineering and Computer Science and was also the founder and director of the university’s Wireless Systems and Circuits Laboratory. As an expert in system integration for wireless systems, he joins KAUST with an established pedigree of university-industry collaboration, and he continues to act as an advisor in the development of wireless systems for leading international companies.

Ahmed Eltawil

Professor Eltawil is an expert in advanced wireless communications and energy-efficient computing architectures, with a particular focus on low-power mobile systems, machine-learning platforms, sensor and body area networks. His work bridges academic research and industry, translating innovative ideas into impactful technologies and successful startups.

Abdullah Alshehri

My research focuses on designing efficient interfaces between the analog and digital domains through the development of low-power, high-performance CMOS interface circuits. The interface circuit encompasses key components such as amplifiers, filters, comparators, analog-to-digital converters (ADCs), each of which must be carefully optimized to meet the specific requirements of the target application. By addressing the challenges in analog-digital interfacing, this work aims to contribute to the advancement of integrated circuits and systems that can seamlessly connect real-world analog signals to their digital counterparts, with potential applications in sensor interfaces, data acquisition systems, and mixed-signal electronics. The research involves circuit design, simulation, integration, and experimental evaluation to create novel interface circuit topologies and techniques that improve power efficiency, speed, and overall performance.
<> Machine learning applications for wireless communication systems (3)

Mohamed Amine Lahmeri

Mohamed-Amine Lahmeri is an MS/Ph.D. student in the Communication Theory Lab (CTL) under the supervision of Professor Mohamed-Slim Alouini at King Abdullah University of Science and Technology (KAUST). Education and Early Career Mohamed-Amine Lahmeri joined the best engineering school in Tunisia, "Ecole Polytechnique de Tunisie (EPT)", in 2019 after being ranked among the top 2% at the Tunisian national contest for entrance to engineering schools. During his graduation project, he joined KAUST as a visiting student and got enrolled in the Visiting Student Research Program (VSRP) that is

Asmaa Abdallah

Abdullah Adil Albakry

Senior Associate Consultant, Bain & Company
Education and early career: I graduated with my bachelor’s degree in Electrical and Computer engineering with a mathematics minor from North Carolina State University (NCSU) in the United States. Now, I am a MS/PhD student at KAUST supervised by Dr. Ahmed Eltawil. Research Interest: Machine Learning and Communication Education Profile B.Sc., Electrical and Computer Engineering, North Carolina State University, United States, 2020.
<> machine learning for wireless communication (3) <> Market (3)

Smart Meter Data-Driven Load Forecasting and Price Design in the Retail Market

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KAUST

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.

Entrepreneurship Explored

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B9 L2 H2 H2

Entrepreneurs continue to be the driver for economic development and innovation. Some startups invent brand new markets while other manage to enter markets crowded by existing large companies. In this seminar we will explore making critical early decisions starting from chaos and creating an exciting new business. We will gain insights on the value of learning by doing, prototyping, discussing tradeoffs between analysis, experimentation and scale. We will also review courses offered by KAUST Entrepreneurship Center.

Critical Phenomena in Financial Markets and Social Networks

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B9 L2 R2322

Analogies between financial markets and critical phenomena have long been observed empirically. So far, no convincing theory has emerged that can explain these empirical observations. Here, we take a step towards such a theory by modeling financial markets as a lattice gas.
<> Mathematical Biology (3)
Analysis and PDEs Workshop-2025

Workshop on Analysis and PDEs

-

B3, L5, R5220

Join us for the Workshop on PDEs to explore advances, challenges and methods in the analysis and computation of partial differential equations.

Katerina Nik

Professor Nik studies partial differential equations that describe phenomena in biological growth processes, fluid dynamics, and mechanical engineering.

On Nonlocal Keller-Segel Type Equations

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B1 L3 R3119

In the first part of the talk we investigate a Keller-Segel model with quorum sensing and a fractional diffusion operator. This model describes the collective cell movement due to chemical sensing with flux limitation for high cell densities and with anomalous media represented by a nonlinear, degenerate fractional diffusion operator. The purpose here is to introduce and prove the existence of a properly defined entropy solution. In the second part of the talk we will analyze an equation that is gradient flow of a functional related to Hardy-Littlewood-Sobolev inequality in whole Euclidean space of higher dimensions.
<> MCMC (3) <> Mechatronics (3) <> memristor (3) <> Metric graphs (3)

Gaussian Random Fields on Metric Graphs

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B9 B2 L2325

This talk presents a comprehensive mathematical and statistical theory, along with user-friendly software, for modeling data with Gaussian random fields on metric graphs by developing valid covariance functions based on network distance.

Statistical Models and Methods Based on Stochastic Partial Differential Equations

-
This talk presents an overview of our research on statistical methods using stochastic partial differential equations (SPDEs), focusing on non-Gaussian random fields and fractional-order SPDEs, and theory for random fields and statistical analysis on metric graphs, highlighting theoretical contributions, software development, and applications relevant to KAUST RDI pillars.

Vaibhav Mehandiratta

Postdoctoral Research Fellow (former), Statistics
Vaibhav Mehandiratta was a Postdoctoral Research Fellow in the CEMSE Division, Statistics Program, at the King Abdullah University of Science and Technology (KAUST), supervised by Prof. David Bolin. He received his Ph.D. in Mathematics from the Indian Institute of Technology Delhi in November 2022 and joined KAUST as a Postdoctoral Fellow in January 2023. He held this position until September 2024. He is currently an Assistant Professor in the Department of Mathematics at BITS Pilani, K K Birla Goa Campus, India.
<> micro and nanofabrication (3)

Meet KAUST prospective student: Carlos Augusto Zan Malaguti

1 min read ·
Carlos Augusto Zan Malaguti, 23, from Brazil, obtained his bachelor’s degree in electronics and telecommunications engineering from Sao Paulo State University (UNESP). Carlos will join KAUST in the fall of 2020 as an M.S./Ph.D. candidate in the KAUST Sensors Lab under the supervision of Professor Khaled Nabil Salama.

Xiong Dun

Postdoctoral Research Fellow, Electrical and Computer Engineering
Xiong Dun was a Postdoctoral Research Fellow in the Computational Imaging Group (VCCIMAGING) working with Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Dr. Dun obtained his bachelor degree in Electronic Science and Technology from Harbin Institute of Technology in Harbin, China in 2007. After that in 2010, he received his master degree in Optical Engineering from Tianjin Jinhang Institute of Technology and Physics in Tianjin, China. He has a doctoral in Optical Engineering from Beijing Institute of Technology in Beijing

Qiang Fu

Research Scientist, Computer Science
Qiang Fu is a Research Scientist in the Computational Imaging Group (VCCIMAGING) working with Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Qiang Fu obtained his bachelor degree in Manufacturing and Design Automation of Machinery from University of Science and Technology of China in 2007. He has a Ph. D. in Optical Engineering from University of Chinese Academy of Sciences (2012). In 2012, Qiang joined the Academy of Opto-Electronics at Chinese Academy of Sciences as an Assistant Research Fellow. After 2 years
<> Micro-LEDs (3) <> MIMO and Passive radar (3)

Dr. Basem Shihada and Dr. Sajid Ahmed promoted to Senior Member of IEEE

1 min read ·
Dr. Basem Shihada and Dr. Sajid Ahmed have been elevated to the rank of Senior Member of IEEE. This is considered a significant honor since only 8% of nearly 400,000 IEEE members are Senior Members because of their superior professional achievements.

Seifallah Jardak

Introduction Seifallah Jardak, Ph.D. alumni of King Abdullah University of Science and Technology (KAUST) class 2018, is currently holding a research engineer position at Toshiba Telecommunications Research Laboratory (TRL), Bristol, UK. Education and Early Career Seifallah Jardak obtained his Diplôme d’Ingénieur from Ecole Polytechnique de Tunisie, in Tunisia in 2012. Afterward, he joined King Abdullah University of Science and Technology (KAUST) to pursue his Master and Ph.D. degrees in Electrical Engineering supervised by Prof. Sajid Ahmed and Prof. Mohamed-Slim Alouini. During his graduate

Sajid Ahmed

Senior Research Scientist, Electrical and Computer Engineering
Current position I am a Research Scientist at KAUST. The broad area of my research is array signal processing with application to radar and communication. My current research focuses on finding low complexity innovative solutions and development of state-of-the-art technologies, for autonomous vehicles and biomedical problems. Why did you choose KAUST? I was very much inspired by the worthy endeavor of making KAUST a new “House of Wisdom” in the region, and I wanted to be a part of it. KAUST is a model institution for the advancement of scientific research. How is KAUST helping you fulfill
<> MIMO-radar waveform design (3)

Dr. Basem Shihada and Dr. Sajid Ahmed promoted to Senior Member of IEEE

1 min read ·
Dr. Basem Shihada and Dr. Sajid Ahmed have been elevated to the rank of Senior Member of IEEE. This is considered a significant honor since only 8% of nearly 400,000 IEEE members are Senior Members because of their superior professional achievements.

Sajid Ahmed

Senior Research Scientist, Electrical and Computer Engineering
Current position I am a Research Scientist at KAUST. The broad area of my research is array signal processing with application to radar and communication. My current research focuses on finding low complexity innovative solutions and development of state-of-the-art technologies, for autonomous vehicles and biomedical problems. Why did you choose KAUST? I was very much inspired by the worthy endeavor of making KAUST a new “House of Wisdom” in the region, and I wanted to be a part of it. KAUST is a model institution for the advancement of scientific research. How is KAUST helping you fulfill

Karim Saifullin

Karim Saifullin is a PhD student at the CLT group at KAUST, focusing on research in Joint Radar and Sensing, Wireless Communications, and the application of Quantum Computing to radar and signal processing. He obtained his specialist degree from BMSTU and has accrued approximately 3.5 years of experience in diverse organizations within the field of wireless communications. In addition to his research, he serves as a teacher and teaching assistant across multiple courses.
<> mixed finite elements (3)

Theory and Implementation of Novel Numerical Methods for Multiphysics Interface Problems

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B2/B3 L0 R0215

This thesis develops and analyzes Finite Element Methods (FEM) for multiphysics interface problems using the Fictitious Domain with Distributed Lagrange Multiplier (FD-DLM) framework. It introduces new families of stable mixed methods with discontinuous Lagrange multiplier spaces, studies both a priori and a posteriori error estimates, and designs multigrid preconditioners. Theoretical results are supported by numerical experiments.

Najwa Alshehri

Professional Interests Beyond academic and research pursuits, Najwa is deeply committed to mentoring and empowering female students to pursue careers in science and research. At KAUST, she engaged in initiatives that cultivate talent in mathematics, AI, and deep learning. Additionally, she placed significant emphasis on developing her leadership and entrepreneurial skills through specialized programs and certifications along with other trainings in Key Performance Indicators (KPI), Total Quality Management (TQM), and strategic planning.

Daniele Boffi

Professor Boffi is a leading international expert in mixed finite elements and the approximation of eigenvalue problems arising from partial differential equations.
<> mmWave/Terahertz communications (3)

Wafa Hedhly

Wafa Hedhly is an MS/Ph.D. student in the Communication Theory Lab (CTL) under the supervision of Professor Mohamed-Slim Alouini at King Abdullah University of Science and Technology (KAUST). Education and Early Career Wafa obtained her Engineering Degree in Telecommunication from the Higher School of Communication of Tunis (Sup’Com) in 2017. In spring 2017, she was a visiting student in KAUST for 4 months working on her graduation project. Research Interest Wafa is focusing on resource allocation in future Terahertz networks. Education Profile Ph.D. in Kind Abdullah University of Science and

Srujana Kagita

Selected Publications ​S.Kagita,A.Basu,S.K.Koul , "Electrically Tunable Ferrite Bandpass Filter in X-Band With Wide Tunability," in IEEE Transactions Magnetics, vol. 55, no. 7, pp. 1-4, July 2019. S.Kagita,A.Basu,S.K.Koul," Characterization of LTCC based ferrite tape and its application to electrically tunable phase shifter and notch filter," IEEE.Transactions in Magnetics , vol.53 , issue 1, 2017. S.Kagita,A.Basu,S.K.Koul,"Modeling of LTCC-Ferrite Tunable Inductors and Development of an L -Band Phase Shifter," IEEE.Trans.Magn,vol.51, no.10, pp.1-9, Oct. 2015. Education Profile ​​PhD , Topic

Shuaishuai Guo

Postdoctoral Research Fellow, Electrical and Computer Engineering
Shuaishuai Guo is a Postdoctoral Fellow with Computer, Electrical and Mathematical Science and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alumni in the Communication Theory Laboratory. Education and Early Career Shuaishuai Guo received the B.E and Ph.D. degrees in communication and information systems from the School of Information Science and Engineering, Shandong University, Jinan, China, in 2011 and 2017, respectively. During 2016-2017, he visited the University of Tennessee at Chattanooga (UTC) as a visiting scholar
<> mobile computing (3)

Sensor-less Energy-free Sensing: The Future of Ubiquitous Context-Awareness for the IoT

Moustafa Youssef, The American University in Cairo, Egypt

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B1 L3 R3119

Many IoT devices are expected to be limited in capability and run with minimal power sources/limited batteries. To extend their lifetime, and autonomy, and reduce the cost of deployment, we introduce the concepts of sensor-less and energy-free sensing, where we sense the environment without using any external sensors while consuming minimal or no energy.

Kamran Jamshaid

Postdoctoral Research Fellow, Networking Research Lab
Kamran Jamshaid was a Postdoctoral Research Fellow at Networking Research Lab (NETLAB) in King Abdullah University of Science and Technology (KAUST), working with Professor Basem Shihada in his research group. Research Interests Kamran's research interests included computer networks, wireless data networks, distributed systems, and pervasive and mobile computing. Selected Publications A. Showail, A. Elrasad, A. Meer, A. Daghistani, K. Jamshaid, and B. Shihada, "iFrag: Dynamic Partial Packet Recovery for Sensor Systems", ACM Journal of Wireless Networks, Vol. 20, No. 4, pp. 1-18, 2014. [ PDF] I

Essam Mansour

Postdoctoral Research Fellow, ‌InfoCloud
Essam Mansour was a Postdoctoral Research Fellow at InfoCloud Research Group (CLOUD) at King Abdullah University of Science and Technology (KAUST), worked with Professor Panagiotis Kalnis. He contributed to research activities of the KAUST InfoCloud Research Group including leading a research project aiming at developing an elastic database system for processing very large strings based on the cloud infrastructure. This system is to support scientific data management, as a data-intensive application. Prior to joining KAUST, Essam was a Research Associate at the School of Information Technology
<> Model Predictive Control (3)

Model Predictive Control Systems for Industrial Applications

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B3 L5 R5209

Model Predictive Control (MPC) is an d advanced control strategy widely used in the process industries and beyond. Therefore, industry is interested in the developments of MPC formulations that can enhance safety, reliability, and economic profitability of chemical processes. Motivated by these considerations, the first part of this talk focuses on the development of methods for integrating process operational safety and process economics within model predictive control system designs.

Economic Model Predictive Control Strategies for Nonlinear Systems

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KAUST

The first part of this talk provides a brief introduction of the EMPC (motivation, challenges, and solutions). The second part of this talk proposes a regret-based robust EMPC paradigm for nonlinear systems subject to unknown but bounded disturbance. The main motivation of the proposed work is the possible improvement of the economic performance when one considers the regret function as the objective function for the robust EMPC algorithm instead of the worst cost. The third part of this talk introduces an integrated framework that combines a Neural Network (NN) algorithm with an MPC scheme that can guarantee closed-loop stability in the presence of deception cyberattacks (e.g., min-max cyberattack). Both discrete-time and continuous-time nonlinear systems will be utilized throughout the talk to demonstrate the applicability and effectiveness of the proposed control methods. Finally, future research directions will be presented at the end of the talk.

Xingang Guo

Xingang is an MS /Ph . D . student in Electrical Engineering department within CEMSE division at King Abdullah University of Science and Technology. He also hold s a B.Sc. from Northeastern University. His research interests are in the area of estimation and optimal control of nonlinear differential algebraic equations and nonlinear dynamical systems with applications in both membrane distillation desalination and wastewater treatment plants. My research activities are mainly around optimal controller design. For example, a fractional order PID (FOPID) controller was designed for a laser beam
<> MOFs (3)

Lining MOF pockets to detect noxious gases

1 min read ·
A porous material with tailor-made pockets stitched into its structure is a promising material for sensing noxious gases. A thin film of the material, coated onto an electrode, formed an electronic sensor that could detect traces of sulfur dioxide gas. The sensor is a significant step toward real-world devices that can sniff out dangerous gases in real air. Although several lab-based analytical instruments can detect traces of a specific gas in the air, these instruments are typically large, expensive, power-hungry machines. There is still a need for small, inexpensive, energy-efficient

MOFs can sense and sort troublesome gases

1 min read ·
Fluorinated metal-organic frameworks make excellent materials for selective sensing and removal of toxic gases.

Realization of an Ultrasensitive and Highly Selective OFET NO2 Sensor: The Synergistic Combination of PDVT-10 Polymer and Porphyrin–MOF

1 min read ·
Saravanan Yuvaraja, et al., "Realization of an Ultrasensitive and Highly Selective OFET NO2 Sensor: The Synergistic Combination of PDVT-10 Polymer and Porphyrin–MOF." ACS Applied Materials & Interfaces 12 (16), 2020, 18748. Organic field-effect transistors (OFETs) are emerging as competitive candidates for gas sensing applications due to the ease of their fabrication process combined with the ability to readily fine-tune the properties of organic semiconductors. Nevertheless, some key challenges remain to be addressed, such as material degradation, low sensitivity, and poor selectivity toward
<> molecular evolution (3)

Kosuke Goto

Research Interests ​Development of bioinformatics tools and databases for molecular evolution, population genetics, metagenomics. Professional Profile ​2015-present: Technical Specialist, KAUST, Thuwal, Saudi Arabia Education Profile ​M.Sc., Applied Biological Science, Tokyo University of Science, Chiba, Japan, 1993 B.Sc., Physics, Tokyo University of Science, Tokyo, Japan, 1991

Hiroyuki Kuwahara

Hiroyuki Kuwahara got his Ph.D. degree in Computer Science from the University of Utah in 2008. He was then a junior researcher at Microsoft Research - Trento during 2007 and 2009. During 2009 and 2012, he was a Ray and Stephanie Lane Fellow at the School of Computer Science at Carnegie Mellon University. Since 2012, he joined the SFB group as a Research Scientist. Research Interests ​Hiroyuki's area of research is broadly in computational systems and synthetic biology. His main research focus is on the theoretical understanding of how various uncertainties contribute to the relation between

Hajime Ohyanagi

Research Interests ​My original question in biology is the Origin and History of Eukaryotes. I also love to understand the possibility of Genomic Breeding in the imminent global food security issue. To these ends, currently, I aim to determine the biological significance in big data of marine and crop genomics, by the means of diverse bioinformatics methodologies. Professional Profile 2015-present: Technical Specialist, KAUST, Thuwal, Saudi Arabia 2015-present: Visiting Research Scientist, National Agriculture and Food Research Organization, Tsukuba, Japan 2013-present: Visiting Research
<> monte carlo algorithms (3)

Overcoming the curse of dimensionality: from nonlinear Monte Carlo to deep learning

Arnulf Jentzen, Professor, Applied Mathematics Münster: Institute for Analysis and Numerics, University of Münster

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KAUST

In this talk we prove that suitable deep neural network approximations do indeed overcome the curse of dimensionality in the case of a general class of semilinear parabolic PDEs and we thereby prove, for the first time, that a general semilinear parabolic PDE can be solved approximatively without the curse of dimensionality.

Meet KAUST prospective student: Miguel Ángel Álvarez Ballesteros

1 min read ·
Miguel Ángel Álvarez Ballesteros is a physics graduate from the Universidad Industrial de Santander, Bucaramanga, Colombia. Miguel will join KAUST this fall as a M.S./Ph.D. candidate and member of the KAUST Computational Probability research group under the supervision of Professor Ajay Jasra.

Hamza M. Ruzayqat

Research Scientist, Omar Knio Research Group
Dr. Hamza Ruzayqat is a Research Scientist at KAUST, specializing in Monte Carlo algorithms, data assimilation, and uncertainty quantification, with a background that includes a PhD in Mathematics from the University of Tennessee-Knoxville and various teaching and research positions.
<> Monte carlo methods (3)

Learning for Visual Data Synthesis and Analysis

Dr. Timo Ropinski, Professor, Visual Computing, Ulm University, Germany

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B9 L2 H1 R2322

Abstract In this talk, I will present our recent advances in deep learning to synthesize and analyze visual data, such as images, volumes, and point clouds. The presented approaches are loosely aligned along the classical computer graphics rendering pipeline, whereby both structured and unstructured data are handled. I will first present concepts for learning in object space, i.e., directly on the data to be rendered. To realize different visual tasks, such as normal estimation and segmentation, I will discuss how Monte Carlo integration can be used to realize convolutions on point cloud data

Coupled Sampling Methods for Filtering

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KAUST

This thesis focuses on the use of multilevel Monte Carlo methods to achieve optimal error versus cost performance for statistical computations in hidden Markov models as well as for unbiased estimation under four cases: nonlinear filtering, unbiased filtering, unbiased estimation of hessian, continuous linear Gaussian filtering.

Miguel Angel Alvarez Ballesteros

Miguel Angel Alvarez Ballesteros is a M.S./Ph.D. candidate in the KAUSTStochastic Numerics research group under the supervision of Professor Raul Tempone. Before joining KAUST, Miguel obtained a bachelor's degree in physics from the Universidad Industrial de Santander, Bucaramanga, Colombia. Research Interests Miguel's research interests include Monte Carlo methods, Bayesian Statistics, Particle filtering and Machine learning. Education Profile Bachelor's degree in Physics from the Universidad Industrial de Santander (UIS), Bucaramanga, Colombia, in 2019. Publications Álvarez, M., Orjuela
<> Multi-Agent Decision Making (3)

Multi-Robot Task Allocation Games in Dynamically Changing Environments with Application to Trash Collection

Shinkyu Park, Assistant Professor, Electrical and Computer Engineering, KAUST

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KAUST

Featured Sessions
For more information please visit the website

Principles and Algorithms for Multi-Agent Decision Making

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B9 L2 R2322 H1

A multi-agent system consists of individual agents sharing information and coordinating for collective decision making. The study of multi-agent decision making has important implications in conceiving networked engineering systems - a team of mobile robots or a fleet of drones - that can effectively coordinate to carry out assigned missions. Modeling such system as feedback interconnections of many smaller units allows us to examine its long-term behavior using analytical tools from feedback control theory, such as Lyapunov stability and bifurcation analysis. In this presentation, we discuss how such tools can be used to predict asymptotic behavior of the agents' decision making process and also to design computational models of the decision making process.

Lucas Câmara Dantas Bezerra

PhD candidate working on cooperation in multi-agent systems through Multi-Agent Reinforcement Learning (MARL). He is affiliated with the Distributed Systems and Autonomy (DSA) group, under supervision of Professor Shinkyu Park.
<> Multi-face flows (3)

Mini Course Part 2-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

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B1 L3 R3119

In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation

Mini Course Part 3-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

-

B1 L3 R3119

In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation

Mini Course Part 1-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

-

B1 L3 R3119

In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation
<> Multi-robot Systems (3) <> multi-scale 3D visualization (3)

Modeling and Automated Storytelling of Mesoscale Molecular Models

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KAUST

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

Making the invisible, visible

1 min read ·
As bioscience and medicine progress, we are now able to live with diseases, which were once a death sentence. And we are rapidly discovering new interactions at the microscopic level that give us insight into the engines of life. However, as research gets more complicated, the layperson gets left further and further behind. Even those who trust the work of scientists can feel overwhelmed when attempting to read the latest research.

Ivan Viola

Professor, Computer Science
Professor Viola’s expertise lies in scientific visualization and visual computing. His research focuses on multiscale visualization and modeling of complex biological systems, ranging from cellular organisms to atomistic-level details.
<> Multiphysics Simulation (3)

Multiphysics Simulation of Semiconductor Optoelectronic Devices

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KAUST

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.

Multi-physics Simulation of Plasmonic Photoconductive Devices and Antennas

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B9 L2 R2322 H1

Terahertz (THz) frequency electromagnetic fields have numerous applications ranging from wireless communications to imaging systems and nondestructive testing, to material characterization. One of the main obstacles in the way of widespread industrial use of THz technologies is the difficulty of implementing compact and frequency-stable THz sources that can operate at room temperatures. Among a variety of possible options, photoconductive devices (PCDs) satisfy these conditions. Indeed, they have become one of the most promising candidates for THz source generation since recent advances in fabrication techniques, such as metasurface integration and nanostructured surface inclusions have significantly increased their optical-to-THz conversion efficiency and made them polarization insensitive.

Rolf Krause

Professor Rolf Krause is an experienced researcher and educator specializing in designing and analyzing algorithms to solve complex problems in scientific computing and machine learning.
<> multivariate analysis (3) <> Nanogenerators (3)

An origami 'slinky' that harvests incidental energy

1 min read ·
Lightweight and low-cost device uses friction inside paper-based coils to transform mechanical motion into electricity.

Yuvaraj Sivalingam

Yuvaraj Sivalingam is a Research Scientist at the Sensors Lab, Computer, Electrical, and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia. Education and Early Career He received his M.Sc. in Physics in 2007 from Madurai Kamaraj University, India and in 2009 he received his M.Tech. in Sensor System Technology from VIT University (India), with a project entitled “Studies on the development of compositions for hydrogen sensing applications and their relevant instrumentation’. In 2008-2009 during his M.Tech.

Latifah Al Maghrabi

Latifah Al-Maghrabi is pursuing a master's degree in Electrical Engineering in the electrophysics track at King Abdullah University of Science and Technology (KAUST). Currently, the questions that guide Latifah's journey of investigation revolve around exploring novel lower dimensional materials for integration with group-III-nitride-based optoelectronic devices at the Photonics Laboratory at KAUST. By understanding the physics at the device level, she hopes to be able to enhance optoelectronics used for light and energy generation. In May 2018, Latifah graduated with a B.S. in Electrical
<> nanoscale (3)

Tsunami On Demand: The Power To Harness Catastrophic Events

1 min read ·
A new study published today on Nature Physics features a nano-optical chip that makes possible generating and controlling nanoscale rogue waves. The innovative chip was developed by an international team of physicists, led by Andrea Fratalocchi from King Abdullah University of Science and Technology (KAUST), in Saudi Arabia, and is expected to have significant applications for energy research and environmental safety.

Optical chips harness the power of rogue waves

1 min read ·
A microchip designed to generate and control rogue waves of light on the nano-scale has many potential applications.An optical chip to create and harness the power of nanoscale rogue waves of light could ultimately lead to better prediction systems for weather events and natural disasters by improving researchers’ understanding of the mechanisms that underpin chaotic wave events. Natural catastrophic events are inherently unpredictable, stemming from high-energy, chaotic systems that are difficult to understand or emulate. Andrea Fratalocchi, and his team from KAUST, in collaboration with

A firefly's flash inspires new nanolaser light

1 min read ·
Synchronized emissions from innovative on-chip lasers create possibilities for inexpensive artificial neural networks.
<> nanoscience (3) <> Nanyang Technological University (3)

Convolutional Neural Networks on Graphs

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B9 H2

In the past years, deep learning methods have achieved unprecedented performance on a broad range of problems in various fields from computer vision to speech recognition. So far research has mainly focused on developing deep learning methods for grid-structured data, while many important applications have to deal with graph-structured data.

Day 2 - Deep learning and the latest algorithms in artificial intelligence

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B4 B5 A0215

The ML Hub offers a 2-day short course on deep learning and the latest algorithms in artificial intelligence. The course will be given by Professor Xavier Bresson from the Nanyang Technological University (NTU) in Singapore, who is a leading researcher in the field of deep learning. The course will include the theory of deep learning techniques as well as practical exercises. Prerequisite knowledge: Basic knowledge of linear algebra (e.g. matrix multiplication) and script programming (e.g. Python, Matlab, R) are needed. The coding will be done in Python. Note, that this course has limited seating and filling registration form does not guarantee acceptance. If you are selected, you will receive a confirmation e-mail.

Day 1 - Deep learning and the latest algorithms in artificial intelligence

-

B4 B5 A0215

The ML Hub offers a 2-day short course on deep learning and the latest algorithms in artificial intelligence. The course will be given by Professor Xavier Bresson from the Nanyang Technological University (NTU) in Singapore, who is a leading researcher in the field of deep learning. The course will include the theory of deep learning techniques as well as practical exercises. Prerequisite knowledge: Basic knowledge of linear algebra (e.g. matrix multiplication) and script programming (e.g. Python, Matlab, R) are needed. The coding will be done in Python. Note, that this course has limited seating and filling registration form does not guarantee acceptance. If you are selected, you will receive a confirmation e-mail.
<> networking (3)

Paving the Way for Next Generation Wireless Networks

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B9 L2 H1 R2322

In this talk, I will introduce several ongoing projects at the networking lab in KAUST. I will start by highlighting our research profile along with our mission. Then, I will walk you through our projects and contributions in the domains of the internet of things, visible light communication, underwater communication, and future 6G networks. I will focus on the challenges facing each project, highlight our solution methodology, and discuss some performance evaluation results. I will focus on our work on Aqua-Fi, which aims at bringing the Internet into the underwater environment. I will also focus on our recent project on the communication via breath.

Elisa Chiapponi

I am currently a PhD student in Digital Security enrolled in the Sorbonne Université. I work on my research project at EURECOM and Amadeus, under the supervision of prof. Marc Dacier at KAUST My areas of interest include Network and Web security. My thesis focuses on the analysis and mitigation of the new generation of botnets, in particular the ones performing web scraping. My goal is to find practical means to defeat them. The starting point of my project is understanding the ecosystem of scraping bots. This consists of identifying the actors behind this business and their motivations

Amr El-Rasad

Amr El-Rasad obtained his Ph.D. degree in Computer Science under the supervision of Professor Basem Shihada at King Abdullah University of Science and Technology (KAUST). Prior to KAUST, he was also an assistant lecturer for the Faculty of Engineering, Alexandria University, Egypt. He received his BSc in electrical engineering and MSc in engineering mathematics from Alexandria University, Egypt, in 2004 and 2010, respectively. Currently, Amr is working as a Post-Doctorate Fellow at Trinity College Dublin, University of Dublin, Ireland. Research Interest Amr's research interests included
<> networks (3) <> Neuro-Symbolic AI (3) <> nonlinear (3)

Overcoming the curse of dimensionality: from nonlinear Monte Carlo to deep learning

Arnulf Jentzen, Professor, Applied Mathematics Münster: Institute for Analysis and Numerics, University of Münster

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KAUST

In this talk we prove that suitable deep neural network approximations do indeed overcome the curse of dimensionality in the case of a general class of semilinear parabolic PDEs and we thereby prove, for the first time, that a general semilinear parabolic PDE can be solved approximatively without the curse of dimensionality.

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

Maria Sara Nour SADOUN

Visiting Student (former), Information Science Lab
Research internship in King Abdullah University of Science and Technology within EMANG as a Visiting Student on the topic of Epileptic Seizure Detection using Electroencephalography (EEG).
<> nonlinear models (3)

Deterministic particle approximation for nonlinear transport equations

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Building L3 R3119

Approximating the solution to an evolutionary partial differential equation by a set of "moving particles" has several advantages. It validates the use of a continuity equation in an "individuals-based" modeling setting, it provides a link between Lagrangian and Eulerian description, and it defines a "natural" numerical approach to those equations. I will describe recent rigorous results in that context. The main one deals with one-dimensional scalar conservation laws with nonnegative initial data, for which we prove that the a suitably designed "follow-the-leader" particle scheme approximates entropy solutions in the sense of Kruzkov in the many particle limit. Said result represents a new way to solve scalar conservation laws with bounded and integrable initial data. The same method applies to second order traffic flow models, to nonlocal transport equations, and to the Hughes model for pedestrian movements.

A novel design of antenna array developed by KAUST scientists

1 min read ·
At the sensors lab, Prof. K.N. Salama and Prof. A. Shamim led a team of KAUST founding masters students Farhan Abdul Ghaffar and Muhammad Umair Khalid to develop an aperture coupled patch antenna array SoP.
<> Nonlinear Partial Differential Equation (3)

Gravitational Collapse of Self-similar stars

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B1 L4 R4102

The Euler-Poisson equations give the classical model of a self-gravitating star under Newtonian gravity. It is widely expected that, in certain regimes, initially smooth initial data may give rise to blow-up solutions, corresponding to the collapse of a star under its own gravity. In this talk, I will present recent work with Yan Guo, Mahir Hadzic and Juhi Jang that demonstrates the existence of smooth, radially symmetric, self-similar blow-up solutions for this problem. I will also comment on the stability of the obtained solution. At the heart of the analysis is the presence of a sonic point, a singularity in the self-similar model that poses serious analytical challenges in the search for a smooth solution.

Simone Portaro

Simone Portaro is a Ph.D. Student in the Computer, Electrical, Mathematical Sciences and Engineering (CEMSE) department at the Applied Mathematics and Computational Sciences (AMCS) program under the supervision of Professor Peter Markowich at King Abdullah University of Science and Technology. Simone received his B.S. degree in Industrial Engineering from the University of Catania, Italy in 2017. In 2020, he received his M.S. degree in Mathematical Engineering from Politecnico di Torino, Italy. Research interests Nonlinear Partial Differential Equations, Analysis-Modeling of biological network

Shuaikun Wang

Postdoctoral Research Fellow, Applied Mathematics and Computational Science
Short Bio Shuaikun Wang received his bachelor's degree in Mathematics from University of Science and Technology of China in 2012 and a Ph.D degree in Mathematics from City University of Hong Kong in 2016. He was a postdoc in City University of Hong Kong in 2016-2017 and a Postdoctoral Research Fellow in the Applied PDE group at KAUST from September 2017 - December 2020. Currently he is an Associate Professor in the School of Mathematics, Shandong University, Jinan, China. Shuaikun Wang's research interests lie in the area of applied analysis, nonlinear partial differential equations and
<> numerical PDEs (3) <> Numerical simulation and analysis (3)

Training Neural Networks at Any Scale

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B9 L2 R2325

The talk explores a key mathematical ingredient of scaling in tandem with scaling theory: the numerical solution algorithms commonly employed in deep learning, spanning domains from vision to language models.

KAUST Ph.D. student wins Society for Industrial and Applied Mathematics award

1 min read ·
Chiheb Ben Hammouda, a KAUST Ph.D. student in the University's Stochastic Numerics Research Group, recently won the best poster award at the Society for Industrial and Applied Mathematics (SIAM) Conference on Financial Mathematics & Engineering (FM19) held at the University of Toronto from June 4 to 7. His winning poster, titled "Hierarchical adaptive sparse grids and quasi-Monte Carlo for option pricing under the rough Bergomi model," is one of several research projects carried out by Ben Hammouda under the supervision of KAUST Professor Raul Tempone.

Chiheb Ben Hammouda

Chiheb Ben Hammouda is a Ph.D. candidate at Stochastic Numerics Research Group (STOCHNUM) under the supervision of Professor Raul F. Tempone at King Abdullah University of Science and Technology (KAUST). Prior to joining Ph.D., Chiheb obtained a Master's degree in Applied Mathematics and Computational Sciences from KAUST, and a Bachelor's degree in multidisciplinary engineering from Ecole Polytechnique de Tunisie, Tunisia. Research Interests Chiheb's research interests include Stochastic modeling, Numerical simulation and analysis, Quantitative finance in particular option pricing, Stochastic
<> operating systems (3)

Security analysis of Docker-based containerized environments

Operating System (OS) virtualization, also known as container-based virtualization, has gained momentum over the past few years thanks to its lightweight nature and support for agility. However, its compelling features come at the price of a reduced isolation level compared to the traditional host-based virtualization techniques, exposing workloads to various faults, such as container escape. Those faults might be manifested as host OS bugs, container runtime vulnerabilities, and/or poor container deployment choices and profile configuration. The latter aspect is particularly critical as

Monitoring containerized environments for security state error detection

Operating System (OS) virtualization, also known as container-based virtualization, has gained momentum over the past few years thanks to its lightweight nature and support for agility. However, its compelling features come at the price of a reduced isolation level compared to the traditional host-based virtualization techniques, exposing workloads to various threats, such as container escape. In those threats, compromised or rogue containers might exploit existing vulnerabilities or poor container deployment choices to successfully inject security state errors (e.g., breaking out of the

An Overview of Systems Research at TU Munich

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B4 L5 R5209

In this talk, Professor Pramod Bhatotia will give an overview of systems research at TU Munich. He will cover his teaching and ongoing research projects. And will conclude the talk with a brief overview of his ERC project.
<> Optical (3)
optoelectronic device can adapt to light

Artificial neurons enable neuromorphic computing with light

1 min read ·
An adaptive capacitor that can sense and learn through optical stimuli enables learning and recognition tasks.

Pointing and Trajectory Tracking Control for Optical Wireless Communication

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

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KAUST

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.

Sutanu Ghosh

Sutanu Ghosh is a visiting research scholar under the supervision of Prof. Dr. Mohamed-Slim Alouini at the Computer, Electrical, and Mathematical Science and Engineering (CEMSE) Division in King Abdullah University of Science and Technology (KAUST). Education and Early Career Sutanu Ghosh obtained his Master Degree from Jadavpur University, India and Ph.D Degree from Indian Institute of Engineering Science and Technology, India. Research Interest Sutanu Ghosh is focusing his research in the area of Device-to-Device Communication, optical wireless communication, Energy harvesting, Internet-of
<> optical fiber (3) <> parallel numerical algorithms (3)

ISC21 Workshop: Numerical Algorithms and Libraries for Exascale (NAL-X)

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ISC21 KAUST Frankfurt Germany Time CET

Abstract With the hardware technology scaling and the trend on heterogeneous chip design, the existing numerical algorithms and software framework may break down due to load imbalance. There is currently a fundamental mismatch between the underlying hardware architecture with high thread concurrency and the software deployment of numerical libraries, which relies on the traditional bulk synchronous programming model. Numerical software should first squeeze performance out of single node by efficiently running on manycore architectures with processor counts sharing a common memory in the

Heterogeneity in Hardware: Opportunities and Challenges for Software and Applications (SC21 Panel)

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SC21 Saint Louis MO USA

Heterogeneity in Hardware: Opportunities and Challenges for Software and Applications SC21 Panel Time: Tuesday, 16 November 2021, 10:30am - 12pm CST Location: 225-226 (America's Center, St. Louis, MO USA) Abstract With the end of Moore’s Law, the community has witnessed new hardware trends to increase performance. Today, it is not only the traditional x86 and accelerators that are part of computing systems, but also ARM, FPGAs and dedicated processors for DL workloads that equip now pioneering HPC systems. By the end of this decade, we are moving towards an era of extreme scale with “extreme

Hatem Ltaief

Principal Research Scientist, Applied Mathematics and Computational Science
Dr. Hatem Ltaief is a Principal Research Scientist at KAUST. He works on mixed-precision algorithms and performance optimizations to help HPC scientific applications address the exascale challenges. His innovations have been recognized with the ACM Gordon Bell Prize (shared) for Climate Modeling in 2024.
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Seven IVUL members recognized as Outstanding Reviewers by CVPR 2021

1 min read ·
The 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) has granted Outstanding Reviewer awards to seven members of IVUL: Alejandro Pardo, Ali Thabet, Chen Zhao, Mattia Soldan, Mengmeng Xu, Juan C. Pérez, and Silvio Giancola. CVPR, a premier annual computer vision event that will take place virtually from June 19th to June 25th, is the largest computer vision conference in the world, gathering researchers from academia and industry alike. The peer-review process through which the conference determines acceptance of papers relies on expert reviewers from across the world

Israel Jesus Santos Filho

Israel's research is focusing on Pattern Recognition and Digital Signal Processing. He is passionate about the scientific computing ecosystem, with a particular focus on Data Science, Data Engineering, Applied and Computational Mathematics, Pattern Recognition, and Signal Processing.

Abdullah Alharthi

Postdoctoral Research Fellow, Electrical and Computer Engineering
Dr. Abdullah Alharthi's research centers around pattern recognition as a means to tackle a diverse array of new challenges, including how to learn intelligent behavior in complex, dynamic environments. His areas of expertise include cognition, perception, theory of mind, gait, and human-robot interaction. His work delves into both human kinetics and the comprehension and resolution of how humans and robots interact with one another in a dynamic setting. Dr. Alharthi employs Deep Learning techniques to tackle problems related to image, object, and signal recognition and classification
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On the Use of "Conventional" Unconstrained Minimization Solvers for Training Regression Problems in Scientific Machine Learning

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B9 L2 R2325

This talk introduces PETScML, a framework leveraging traditional second-order optimization solvers for use within scientific machine learning, demonstrating improved generalization capabilities over gradient-based methods routinely adopted in deep learning.

Device accelerated solvers for PDEs. Current status and future perspectives

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B5 L5 R5220

In the next months, KAUST expects to place into service Shaheen-3, a supercomputer with a GPU partition whose planned 1 Exaflop/s HPL AI capability would rank it in the Top 6 globally if delivered today.

Lisandro Dalcin

Lisandro Dalcin obtained a degree in Electromechanical Engineering from National Technological University, Concepción del Uruguay, Argentina in 2001 and a PhD degree in Engineering Sciences, Computational Mechanics from National University of the Littoral, Santa Fe, Argentina in 2008. Research Interest Lisandro Dalcin's research interest include ​​Parallel and High Performance Computing, Scientific Software Development, Finite Element Methods and Computational Fluid Dynamics.​ Education Profile ​​PhD in Engineering Sciences, Computational Mechanics, National University of the Littoral, Santa
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Ontology design patterns and methods for integrating phenotype ontologies

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B3 L5 R5209.

Ontologies are widely used in various domains, including biomedical research, to structure information, represent knowledge, and analyze data. Combining ontologies from different domains is crucial for systematic data analysis and comparison of similar domains. This requires ontology composition, integration, and alignment, which involve creating new classes by reusing classes from different domains, aggregating types of ontologies within the same domain, and finding correspondences between ontologies within the same or similar domain.

​PhenomeNET method wins at Ontology matching workshop

1 min read ·
CBRC congratulates Professor Robert Hoehndorf and Postdoctoral Fellow Miguel Angel Rodriguez Garcia for being one of the winners of the Ontology Alignment Evaluation Initiative challenge sponsored by Pistoia Alliance, presented in the Ontology Matching Workshop that is co-located with ISWC 2016 in Kobe, Japan.

How much do model organism phenotypes contribute to the computational identification of human disease genes?

1 min read ·
PhD Student Sarah M Alghamdi from the Bio-Ontology Research Group (BORG) explains how phenotype ontologies help in identifying disease genes through phenotype comparison. Her research was picked as a highlight in the July 2022 issue of Disease Models and Mechanisms Journal.
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InGaN-based light-emitting devices

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B9 L2 H1

III-Nitride-based light-emitting diodes (LEDs) are already commercialized for instance blue and green LEDs. It is very contributed as energy saving light source all over the world. This material is a very attractive material, capable of the emitting range is not only blue light but also UV and visible light. Moreover, application as a power device is also possible, it is one of the materials considered to lead the energy saving society in the future. Visible light LED has a wide range of applications. Visible light LED has a wide range of applications. we expect that there is some application, for instance, μ-LED display, optical communication, plant cultivation, medical treatment, and so on. In the seminar, I will talk about III-Nitride-based visible light emitting devices and introduce recent research with outstanding metalorganic chemical vapor deposition (MOCVD) growth technique.

Dark materials squeeze green fuel from sunlight

1 min read ·
Metallic nanostructures that slow down light dramatically can triple the efficiency of solar-based hydrogen fuel generation.

Daisuke Iida

Senior Research Scientist, Electrical and Computer Engineering
Daisuke Iida is a Senior Research Scientist at Energy Conversion Devices and Materials (ECO Devices) Laboratory in the Division of Computer, Electrical and Mathematical Sciences & Engineering (CEMSE). He holds a Ph.D. in Materials Science and Engineering from Meijo University in 2011. Afterward, he held postdoctoral and visiting researcher positions at Meijo University and Technical University of Denmark. Then, he worked as an assistant professor at Tokyo University of Science from 2014 to 2017. His research interest is III-nitride semiconductors-based optoelectronic devices, especially the
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Power Electronics Applications in Offshore Wind Farms

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

The challenging path to creating fully autonomous and controllable microrobots

Prof. Néstor O. Pérez-Arancibia, Autonomous Microrobotic Systems Laboratory, University of Southern California (USC)

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KAUST

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

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KAUST

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.