Topics

<> Deep generative models (5)

Nanbo Li

Postdoctoral Research Fellow, Computer Science
Nanbo Li is a Postdoctoral Fellow working in Prof. Jürgen Schmidhuber research group at the King Abdullah University of Science and Technology (KAUST) Center of Excellence for Generative AI.

Ahmad Sait

M.S. Student, Computer Science
Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Generative Models for Neural Fields

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B1 L2 R2202

In computer vision, generative AI models are typically built for images, videos, and 3D objects. Recently, there has emerged a paradigm of neural fields, which unifies the representations of such types of data by parametrizing them via neural networks. In this thesis, we develop generative models for images, videos, and 3D scenes which treat the underlying data in such a form and explore the benefits which such a perspective provides.

Victor Escorcia

Research Scientist committed to innovating AI agents to empower creativity and increase productivity. Passionate about developing cutting-edge AI applications involving video understanding and creative storytelling. I have a wide range of research and engineering interests from on-device AI to General AI. Reach out!

Haozhe Liu

Ph.D. Student, Computer Science
Haozhe Liu is a Ph.D. candidate at King Abdullah University of Science and Technology (KAUST), supervised by Prof. Jürgen Schmidhuber.
<> Deep Reinforcement Learning (5)

Multimodal Agents: From Automation toward Open-Ended Self-Improvement

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This thesis presents practical methodologies for building scalable multimodal agents that move from narrow automation toward open-ended self-improvement.

Rising Stars in AI Symposium 2022 at KAUST

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B4 B5 A0215

Rising Stars in AI Symposium 2022 at KAUST The "Rising Stars in AI Symposium" is geared towards young researchers (including PhD students, PostDocs, young faculty) who have recently published promising work at leading venues. There will be dozens of brief in-person presentations about papers recently accepted at major AI conferences such as NeurIPS, CVPR, EMNLP, ACL, ICML, ICLR, etc. All speakers will be encouraged to start with an intro for non-AI experts. To view the complete program and for more event details, please visit the symposium website. Attend the Symposium The symposium will be

Malik Shahid Sultan

Ph.D. Student, Statistics
Malik Shahid Sultan is a Ph.D. student in Bio-Engineering ( Bioinformatics & Machine Learning) at the King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Hernando Ombao in the Biostatistics group. Education and Early Career Malik Shahid Sultan hold BSc. in Industrial Engineering with a Gold Medal from the University of Engineering and Technology Taxila (Pakistan). Malik holds M.Sc. from King Abdullah University of Science and Technology (KAUST) (Saudi Arabia) in Bio-Engineering (Bioinformatics & Machine Learning). During the Fall of 2021

Azimkhon Ostonov

Postdoctoral Research Fellow, Computer Science

Abeer AlAmoudi

<> distributed computing (5)

Jianwei Shi

Postdoctoral Research Fellow, Statistics

Assessing Network Middlebox Impact on End-to-End Protocol Behavior via a Distributed and Reprogrammable Framework

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B5 L5 R5220

This dissertation focuses on the detection and verification of network middleboxes thanks to the creation of a new distributed framework called NoPASARAN.

EF-BV: distributed optimization with compressed communication

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B9 L2 R2322 H1

In the big data era, it is necessary to rely on distributed computing. For distributed optimization and learning tasks, in particular in the modern paradigm of federated learning, specific challenges arise, such as decentralized data storage. Communication between the parallel machines and the orchestrating distant server is necessary but slow. To address this main bottleneck, a natural strategy is to compress the communicated vectors. I will present EF-BV, a new algorithm which converges linearly to an exact solution, with a large class of deterministic or random, biased or unbiased compressors.

Mojtaba Alshams

Ali Charara

Ali Charara obtained both, his MS Degree and PhD Degree from Computer Science at KAUST in 2011 and 2018 respectively. His master thesis supervisor was Alyn Rockwood and his PhD thesis supervisor was David Keyes. Ali's research interests were in High Performance Computing with a focus on parallel computing and algorithms using multicore and manycore Computer Graphics Units. Education Profile MS Degree, Computer Science, KAUST (2011) PhD Degree, Computer Science, KAUST (2018)
<> dynamical modeling (5)

Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 1B

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 1A

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

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

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

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

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

Bacem Ben Nasser

Bacem Ben Nasser is a postdoctoral researcher fellow in the Electrical Engineering department within the CEMSE division. He obtained his Ph.D. degree in Sciences and Technology-Mathematics from the University of Sfax, Faculty of Sciences of Sfax, Tunisia, where he worked in Lyapunov and control theories, nonlinear integral inequalities and time scale calculus. In January 2017, he was affiliated with the University of Kairouan, Tunisia, at the Higher Institute of Applied Sciences and Technology of Kairouan as assistant professor of applied mathematics. Dr. Ben Nasser joined the research group
<> Efficient (5)

Efficient Numerical Methods for Scalable Bayesian Inference

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B9 R2325

This talk will introduce and discuss the computational building blocks of Integrated Nested Laplace Approximations (INLA) and how these are implemented in software libraries such as R-INLA or DALIA.

Accelerating Branch-and-Bound Graph Algorithms with GPUs

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B9 L2 R2325

This talk presents multiple techniques that we have developed to load balance the search tree traversal on GPUs and mitigate the strain on memory capacity and bandwidth.

From Dialects to Peptides: Scalable and Efficient AI for People

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B9 L2 R2325

This talk presents a unified AI framework for decoding complex human and biological signals - spanning African and Arabic dialects to proteomics - by prioritizing rigorous measurement, cultural competence, and computational efficiency to ensure global scalability and accessibility.

Efficient and Accurate Numerical Methods for Transient Electromagnetic Analysis - 2020

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KAUST

Electromagnetic devices and systems are at the heart of technological advances revolutionizing many fields of science and engineering including energy management, biomedical electronics, communications and computing, and even environmental monitoring and civil design. Many of these systems are electrically large, their frequency of operation has a wide dynamic range, their device components are geometrically intricate with dimensions varying by orders of magnitude, and finally their optimal design requires many repetitions of characterizations with different parameters.

Efficient Machine Learning across Hardware, Software, and Algorithms

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B2 L5 R5209

Deep neural networks (DNNs) are revolutionizing computing, necessitating an integrated approach across the computing stack to optimize efficiency. In this talk, I will explore the frontier of DNN optimization, spanning algorithms, software, and hardware. We'll start with hardware-aware neural architecture search, demonstrating how tailoring DNN architectures to specific hardware can drastically enhance performance.
<> Electronic devices (5)

Tutorial: Pathway to Wide and Ultrawide Bandgap Semiconductor Power Electronics - Session 1

Prof. Biplab Sarkar, ECE, Indian Institute of Technology

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B3 L5 R5220

In this talk, Dr. Sarkar will introduce the history and concepts of power semiconductor devices. A special emphasis will be laid on understanding the power semiconductor device-design keeping the applications in perspective. Apart from covering traditional power electronic devices, Dr. Sarkar will also introduce emerging (ultra)wide power semiconductor devices that are expected to occupy a large market share, and their challenges. The core concepts will be thoroughly discussed with the help of examples and interactive discussions.

Tutorial: Pathway to Wide and Ultrawide Bandgap Semiconductor Power Electronics - Session 2

Prof. Biplab Sarkar, ECE, Indian Institute of Technology

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B3 L5 R5220

In this talk, Dr. Sarkar will introduce the history and concepts of power semiconductor devices. A special emphasis will be laid on understanding the power semiconductor device-design keeping the applications in perspective. Apart from covering traditional power electronic devices, Dr. Sarkar will also introduce emerging (ultra)wide power semiconductor devices that are expected to occupy a large market share, and their challenges. The core concepts will be thoroughly discussed with the help of examples and interactive discussions.

KAUST-NSF Research Conference on Electronic Materials, Devices and Systems for A Sustainable Future 2015

1 min read ·
KAUST-NSF Research Conference on Electronic Materials, Devices and Systems for a Sustainable Future will be held at the Engineering Science Hall on Feb 14th.

Rolling out an e-sticker revolution

1 min read ·
High-speed fabrication developed at KAUST can turn out adhesive and flexible electronic devices in any shape imaginable.

Electronics conference gives a positive charge

1 min read ·
Highlighting sustainability and the work of female researchers was a strong focus of the international KAUST-US NSF electronics conference.
<> Estimation (5)

Spatial Self-Confounding: Smoothness-related estimation bias in spatial regression models

1 min read ·
Spatial regression models are widely used to capture the relationship between observations and covariates, employing Gaussian random fields to account for spatial variability not explained by the covariates. A new study by researchers David Bolin and Jonas Wallin addresses a critical yet often overlooked problem in these models: smoothness-related spatial self-confounding. The work examines how misspecified covariates, particularly when there are differences in smoothness between variables, can lead to severe and counter-intuitive biases in the estimation of regression parameters. These

Yasmine Marani

Yasmine is a Ph.D. candidate in Electrical and Computer Engineering under the supervision of Prof. Eric Feron and Prof. Meriem Laleg. She specializes in control theory, robotics, and artificial intelligence. Her research focuses on estimation problems for complex nonlinear systems with application to unmanned aerial vehicles (UAV) in uncertain environments.

Mohamed Abdelwaheb Bahloul

My name is Mohamed Abdelwaheb Bahloul, native from Sfax, Tunisia. I am a Ph.D. candidate in the Computer, Electrical, and Mathematical Sciences and Engineering Division at King Abdullah University of Science and Technology (KAUST). I first came to KAUST, in 2015, as an intern within the Visiting Student Research Program. Impressed with the University, its facilities, and the KAUST lifestyle, I then applied to KAUST as a master's degree student and was accepted to the electrical engineering program, electro-physics track. After graduating with my M.S. in 2017, I began my Ph.D. studies at KAUST

Asma Abdullah Sarouji

Visiting Student (former), Electrical and Computer Engineering
Research intern at King Abdullah University of Science and Technology (KAUST) under the supervision of Prof.Tareq Al-Naffouri on health project that has a significant impact on people’s lives.

Ania Adil

Postdoctoral Research Fellow, Electrical and Computer Engineering
Ania Adil is a Postdoctoral fellow at the KAUST Robotics, Intelligent Systems, and Control Lab (KAUST RISC Lab) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Eric Feron.
<> Finite element methods (5)

Approximation and Optimization for Neural Networks

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In this talk, we consider new connections between the approximation and optimization of neural networks. Instead of relying on excessive over-parametrization to achieve zero training loss, we identify good minima by comparison with established approximation bounds.

Finite element approximation of Stokes equations with non-smooth data

Lucia Gastaldi, Professor Department of Mathematics, University of Brescia

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B1 L4 R4102

Finite element approximation of Stokes equations with non-smooth data

Umberto Zerbinati

Steven Dufour

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

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.
<> forecasting (5)

Yang Xiao

Ph.D. Student, Statistics
Yang Xaio research specializes in the development of advanced spatio-temporal models and Bayesian frameworks.

Time Series Clustering: Pattern Recognition, Forecasting, and Amortized Inference

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B9 R2325

This talk presents innovative time series clustering techniques, highlighting a quantile-based approach for analyzing locally stationary data, a predictive framework for enhanced forecasting, and the use of amortized inference to overcome traditional algorithmic limitations.

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.
<> generative models (5)

KAUST Workshop on Distributed Training in the Era of Large Models

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Auditorium between B4 & 5, L0, R0215

Join leading researchers and innovators to explore how distributed training is reshaping the next generation of large-scale AI models.

Mapping Properties of Neural Networks and Inverse Problems

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B1 L4 R4214

This talk will explore the injectivity and universal approximation properties of neural networks, focusing on one-to-one mappings and the approximation of probability measures using compositions of invertible flow networks and injective layers, with applications in inverse problems, imaging, and generative models.

Xiaoqian Shen

Education Xiaoqian Shen is a Master's student at Vision-CAIR group in Visual Computing Center (VCC), King Abdullah University of Science and Technology (KAUST). • 2018-2022: BSc in Computer Science & Technology Dept. of Computer Science and Technology, Jilin University, China Research Interest • My research mainly focuses on leveraging natural language to facilitate better visual representation in a low-resource setting. Work Experience • Medical relation extraction for Chinese medicine instructions, 2021, Tsinghua University, China • Self-supervised Learning for medical image segmentation

Sherif Abdelkarim

Current Sherif's reserach interests are in application of visual relationship understanding on long tail datasets. Education and Early Career Sherif obtained his bachelor's degree from the German University in Cairo (GUC), Egypt in 2013 in mechatronics engineering. Afterwards he attended MSc program of Intelligent Systems at Aberystwyth University, UK and where he graduated with distinction. Then Sherif worked as machine learning and deep learning engineer for multiple companies on a wide range of applications including customers' behavior clustering, object detection for self driving cars

Ivan Skorokhodov

Ph.D. Student, Computer Science
Ivan Skorokhodov is a Ph.D. candidate in the Computer Science Program under the supervision of Professor Peter Wonka at Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). His research interests include such areas of deep learning as generative models, hypernetworks and neural rendering. Ivan Skorokhodov has obtained his Ph.D degree and graduated in March 2023. Education and Early Career Ivan obtained his bachelor's degree in Management from the Moscow Engineering Physics Institute in 2014. He continued his studies there and received his master's degree
<> genetics (5)

AI speeds up human embryo model research

1 min read ·
Deep-learning tool outperforms human experts at classifying lab-grown embryo-like structures, enabling advances in developmental biology and drug discovery.

New genetic maps expected to improve personalized medicine for underrepresented populations

1 min read ·
New pangenome graphs made using exclusively Saudi and Japanese samples give new genetic insights on these two populations

Genetic Algorithms for Optimization of Machine-learning Models and their Applications in Bioinformatics

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B3 L5 R5209

Abstract ​​​Machine-learning (ML) techniques have been widely applied to solve different problems in biology. However, biological data are large and complex, which often results in extremely intricate ML models. Frequently, these models may have poor performance or may be computationally unfeasible. This study presents a set of novel computational methods and focuses on the application of genetic algorithms (GAs) for the simplification and optimization of ML models and their applications to biological problems. The dissertation addresses the following three challenges. The first challenge is

Honey bee behavior is in the genes

1 min read ·
An integrated set of genetic mechanisms controls whether bees behave as foragers or nurses.

Noisy cells produce bursts of protein

1 min read ·
A new mathematical model explains how random factors affect the production of proteins within the cells.
<> human body communication (5) <> hydrogen energy (5)

CEMSE Welcomes new Professor: Dr. Jr-Hau

1 min read ·
Prof. He joins from National Taiwan University, where he was a tenured associate professor of Electrical Engineering.

Visiting Ph.D. Student Meng-Lin Tsai and Prof Jr-Hau He device the thinnest highly-efficient solar cell

3 min read ·
At King Abdullah University of Science and Technology (KAUST), a team of researchers developed what might be the effective solution to the problem: the thinnest solar cells with lateral geometry offering high optoelectronic performances while reducing production costs of extended photovoltaic architecture. The research was recently published in Advanced Material and reported by Nature Middle East.

Jr-Hau He elected SPIE Fellow

3 min read ·
Jr-Hau He, KAUST associate professor of electrical engineering, has recently been elected as an SPIE Fellow for his achievements in solar cells, photodetectors and semiconductor optics research. SPIE, the international society for optics and photonics, annually recognizes society members who have made significant scientific and technical contributions in the multidisciplinary fields of optics, photonics and imaging, and for their outstanding technical contributions and service to SPIE. He and 72 additional fellows of the society will be promoted later this year.

KAUST Associate Professor Jr-Hau He wins Nano Energy Award 2019

1 min read ·
The Beijing Institute of Nanoenergy and Nanosystems of the Chinese Academy of Sciences recently announced that KAUST Associate Professor Jr-Hau He is one of three selected scholars who will receive the Nano Energy Awards 2019.

Ahmed Rezk

Research Interests Ahmed is an experienced Mechanical Engineer in Mechanical Design, Process Engineering, Prototyping, Simulation, Manufacturing, Testing and commissioning of different industrial projects. His interest is in development of the process engineering technologies practically through building innovated electromechanical setups to be valid for efficient transition from small lab scale to the commercialized industrial field and achieving the system reliability. He is skilled in software such as AutoCAD plant 3D, SolidWorks, Catia, CAD/CAM, ANSYS, HYSYS and MATLAB. Professional
<> imaging apparatus (5)

Prof. Andrea Fratalocchi appointed member of the Editorial Board of Scientific Reports

1 min read ·
Prof. Andrea Fratalocchi has been appointed as a member of the Editorial Board of Scientific Reports.

Prof. Andrea Fratalocchi receives appreciation from Nature Publications as one of its best reviewers

1 min read ·
Prof. Andrea Fratalocchi received a letter of appreciation from the Editor-in-Chief of Nature for serving as a reviewer.

Klemens Katterbauer (PhD in Electrical Engineering) comes 2nd place at the Middle East, North Africa & South Asia SPE Student Paper contest

1 min read ·
Klemens Katterbauer (Ph.D. candidate under supervision Andrea Fratalocchi) comes 2nd place at the Middle East, North Africa & South Asia SPE Student Paper Contest.

Cancer screening advance: single point genetic mutations made visible by new optical chip

3 min read ·
The collaboration of the teams of professors Enzo Di Fabrizio and Andrea Fratalocchi at the King Abdullah University of Science and Technology (KAUST), in Saudi Arabia, has led to the development of a new device that enables the detection of mutations down to a single amino acid.

Andrea Fratalocchi

Professor Fratalocchi is a pioneer in complex systems and sustainable technologies, focused on addressing critical global challenges. His groundbreaking research has led to innovative solutions in areas such as energy harvesting, clean water production and smart materials. As a founder of the ECE program at KAUST and co-founder of Pixeltra, Professor Fratalocchi is a proven leader and entrepreneur, successfully translating his research into real-world impact.
<> Intelligent Transportation Systems (5) <> intrusion detection (5)
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Vehicle Intrusion Resilience Systems in Action

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A modern vehicle is composed of around 100 Electronic Control Unit (ECU) connected via several types of networks. An ECU is an embedded device, similar to a RaspberryPI, running an operating system, e.g., Linux-based or real-time OS, on top of which different software and firmware may run, depending on the application. Due to the imperfection of humans, software can have faults and intrusions, which can lead to catastrophic failures that threatens human lives. A Fault and Intrusion Resilient System (FIRS) is a vehicle middleware that can mask the effect of a failure or intrusion. Contrary to

CybeResil Research Opportunities

Broad Research Topics Robust and Adaptive Fault and Intrusion Tolerance; Ultra-Reliable Micro Trusted Execution Environments; Privacy and Integrity-preserving Data Processing; Next-generation Threat and Intrusion Detection / Prevention Systems; High-confidence Vertical Software Verification. Focused PhD-level Research Opportunities Fault and Intrusion Resilience Systems for Modern Vehicles Modern software-defined vehicles are prone to software faults and intrusions. A modern vehicle is composed of up to hundred commuting units, called Electronic Control Units (ECUs), connected via different

Marc Dacier

Professor, Computer Science
Leveraging 20+ years of international experience, Professor Dacier leads the charge in uncovering internet vulnerabilities and developing robust defenses, building a more secure digital future for all.

Krish Chatterjie

Krish Chatterjie is a Computer Science and Engineering (CSE) undergraduate student at the Vellore Institute of Technology, India. He joined the Secure Next Generation Resilient Systems Lab (SENTRY) as a Visiting Student under the supervision of Professor Charalambos Konstantinou. Chatterjie’s research revolves around Grid Frequency Modulation (GFM) and Intrusion Detection Systems.
<> Large Language Models (5) <> Laser-scribed graphene (5)
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.

Laser scribed graphene: A novel platform for highly sensitive detection of eletroactive biomolecules

1 min read ·
Abdelghani Ghanam, et al., "Laser scribed graphene: A novel platform for highly sensitive detection of eletroactive biomolecules" Biosensors and Bioelectronics, 2020, 112509. Laser-scribed graphene electrodes (LSGEs) have recently shown a potential for the development of electrochemical biosensors thanks to their electronic properties, porous structures, and large surface area that can support the charge transfer. In this paper, the authors present a comparative study of the electrochemical performances of LSGEs with the conventional screen-printed carbon electrodes (SPCEs) toward the

Electrochemical sensors and biosensors using laser-derived graphene: A comprehensive review

1 min read ·
Abdellatif Ait Lahcen, et al., "Electrochemical sensors and biosensors using laser-derived graphene: A comprehensive review." Biosensors and Bioelectronics 168, 2020, 112565. Laser-derived graphene (LDG) technology is gaining attention as a promising material for the development of novel electrochemical sensors and biosensors. Compared to established methods for graphene synthesis, LDG provides many advantages such as cost-effectiveness, fast electron mobility, mask-free, green synthesis, good electrical conductivity, porosity, mechanical stability, and large surface area. This review

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
<> Latent variable models (5)

Pioneering Public Health Frontiers

1 min read ·
It has been an exhilarating week of international scientific exchange for our research group. From May 11th to 15th, 2026, members of our team had the distinct honour of travelling to Fudan University in Shanghai, on the invitation of Professor Dr. Zhijie Zhang. The trip aims to lay the groundwork for a highly impactful, cross-border partnership in public health analytics.

Dr. Haziq Jamil Delivers International Guest Lecture at UIN Mataram

1 min read ·
Our research group continues to expand its global footprint and strengthen international academic ties. Dr. Haziq Jamil, a Research Specialist in the BAYESCOMP team at KAUST, was invited to deliver an online international guest lecture at the Universitas Islam Negeri (UIN) Mataram in Indonesia.

BAYESCOMP Group Secures CRG Funding to Revolutionize Latent Variable Modeling

2 min read ·
The KAUST Bayesian Computational Statistics and Modeling (BAYESCOMP) Research Group is pleased to announce the award of a 2025 Competitive Research Grant (CRG) for the project: "Advancing scalable Bayesian methods for latent variable modelling." The project is funded at USD $900,000 for 36 months, with the research program officially commencing in April 2026.

Haziq Jamil

Research Specialist, Statistics
Haziq Jamil is a Research Specialist at the King Abdullah University of Science and Technology. His research focuses on statistical theory, methods and computation, with a special inclination towards social science applications.

Xiang Ye

Ph.D. Student, Statistics
Xiang Ye is a Ph.D. student In Statistics at the King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Håvard Rue in his research group.
<> machine learning algorithm (5)

Control and Estimation Designs Using Model-Based and Model-Free Approaches for Water Quality Monitoring in Process Systems

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B1 L4 R4214

This dissertation develops and evaluates advanced control and estimation strategies to address complex dynamics and measurement limitations in water-related applications, specifically optimizing fish growth in aquaculture and estimating bacterial concentration in wastewater treatment plants.
Decision Trees Versus Systems of Decision Rules

New book by KAUST Ph.D. students Kerven Durdymyradov, Azimkhon Ostonov and Professor Mikhail Moshkov published by Springer

1 min read ·
New book by Ph.D. students Kerven Durdymyradov, Azimkhon Ostonov, and Professor Mikhail Moshkov explores decision trees and rule systems using rough set theory.

Fahad Aljehani

Designing advanced control algorithms and estimation techniques to optimize water quality systems, specifically aquaculture and wastewater treatment, blending control theory with cutting-edge AI and machine learning to enhance performance, sustainability, and cost-efficiency.

Helping computers to see who we really are

1 min read ·
Algorithms that train computers to automatically detect human activity in videos can improve online searches and real-world surveillance systems.

Yasmine Marani

Yasmine is a Ph.D. candidate in Electrical and Computer Engineering under the supervision of Prof. Eric Feron and Prof. Meriem Laleg. She specializes in control theory, robotics, and artificial intelligence. Her research focuses on estimation problems for complex nonlinear systems with application to unmanned aerial vehicles (UAV) in uncertain environments.
<> mathematical optimization (5)

Rising Stars in AI Symposium 2022 at KAUST

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B4 B5 A0215

Rising Stars in AI Symposium 2022 at KAUST The "Rising Stars in AI Symposium" is geared towards young researchers (including PhD students, PostDocs, young faculty) who have recently published promising work at leading venues. There will be dozens of brief in-person presentations about papers recently accepted at major AI conferences such as NeurIPS, CVPR, EMNLP, ACL, ICML, ICLR, etc. All speakers will be encouraged to start with an intro for non-AI experts. To view the complete program and for more event details, please visit the symposium website. Attend the Symposium The symposium will be

On the resolution of a theoretical question related to the nature of local training in federated learning

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B1 L3 R3119

In this talk, I will explain the problem, its solution, and some subsequent work generalizing, extending and improving the ProxSkip method in various ways. We study distributed optimization methods based on the local training (LT) paradigm - achieving improved communication efficiency by performing richer local gradient-based training on the clients before parameter averaging - which is of key importance in federated learning. Looking back at the progress of the field in the last decade, we identify 5 generations of LT methods: 1) heuristic, 2) homogeneous, 3) sublinear, 4) linear, and 5) accelerated. The 5th generation, initiated by the ProxSkip method of Mishchenko et al (2022) and its analysis, is characterized by the first theoretical confirmation that LT is a communication acceleration mechanism.

Optimization for Deep Learning

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B5 L5 R5209

Abstract The field of optimization for machine learning has undergone significant changes in recent years with deep learning models increasing in scale and fine-tuning taking a more prominent role. In this presentation, I will share a perspective on the direction of changes in the field and highlight interesting research directions. I will provide real-world examples of what practitioners want from optimization methods to train deep networks at scale. I will then present my recent work on adaptive methods, such as Adam and Adagrad, and explain how we can estimate the learning rate for these

Jongho Park

Jongho Park is a Research Scientist at King Abdullah University of Science and Technology (KAUST) where his research focuses on the design and analysis of efficient numerical methods for variational problems.

Ayed M. Alrashdi

Ph.D. Student (former), Electrical and Computer Engineering
Ph.D. degree in electrical and computer engineering from the King Abdullah University of Science and Technology (KAUST) working with Professor Tareq Al-Naffouri in the Information System Lab (ISL),Assistant Professor with the Electrical Engineering Department at University of Ha'il
<> Memory (5)

Mohammed Zidan (EE PhD Candidate) received the best postgraduate poster award at the SIECPS conference

1 min read ·
Mohammed Zidan received the best postgraduate poster award at the second Saudi International Electronics, Communications and Photonics conference, held 27-30 April 2013 in Riyadh, KSA.

Memristor-based memory The sneak paths problem and solutions

1 min read ·
Mohammed A. Zidan, et al., "Memristor-based memory The sneak paths problem and solutions" Microelectronics Journal 44, (2), 2013, 176. Abstract: In this paper, we investigate the read operation of memristor-based memories. We analyze the sneak paths problem and provide a noise margin metric to compare the various solutions proposed in the literature. We also analyze the power consumption associated with these solutions. Moreover, we study the effect of the aspect ratio of the memory array on the sneak paths. Finally, we introduce a new technique for solving the sneak paths problem by gating

Prof. Salama's publications recognized by Elsevier's Top 25 hottest articles list

1 min read ·
Ph.D. student, Mohammed Zidan 's paper on Memristor-based memory: The sneak paths problem and solutions are recognized by ScienceDirect as one of the Top 25 hottest papers.

Mohammed Zidan awarded IEEE Circuits and Systems Society Pre-Doctoral Fellowship

1 min read ·
Mohammed Affan Zidan, sensors lab member and Ph.D. candidate in the Electrical Engineering (EE) Program at the Computer, Electrical, and Mathematical Science and Engineering (CEMSE) Division, received the IEEE Circuits and Systems (CAS) Society Pre-Doctoral Fellowship.

Mohammed Affan Zidan

Mohammed Affan Zidan obtained his Ph.D. Degree in the Electrical Engineering (EE) Program from King Abdullah University of Science and Technology, under the supervision of Prof. Khaled Nabil Salama. Mohammed Zidan earned his M.Sc. in Electronics and Communications Engineering from Faculty of Engineering, Cairo University, Egypt in 2010, where he was ranked first. In 2006, he received his B.Sc. in Electronics and Communications Engineering, Institute of Aviation Engineering and Technology (IAET), Egypt, also ranking first. Before joining KAUST, he worked as a teaching assistant at the German
<> MIMO radars (5)

FMCW Radar Applications for Automotive and Biomedical Applications

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B1 L3 R3119

This dissertation enhances Frequency Modulated Continuous Wave (FMCW) radar effectiveness for automotive forward-looking Synthetic Aperture Radar (SAR) imaging and biomedical vital sign and dehydration monitoring by developing novel methodologies based on advanced signal processing, deep learning, and MIMO radar techniques.

Vijith Varma Kotte

PhD student at the Information System Lab (ISL), in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST).

Taha Bouchoucha

Taha Bouchoucha was a ​MS Thesis Student at King Abdullah University of Science and Technology (KAUST).

José Maria Sosa Gómez

PhD student at KAUST leveraging machine learning and radar systems to enhance patient procedures, under the guidance of Prof. Mohamed-Slim Alouini at the Communication Theory Lab (CTL).

Hussain Ali

Research Engineer, Information Science Lab at King Abdullah University of Science and Technology (KAUST), Research Engineer at Dhahran Techno Valley, KFUPM, Dhahran, Saudi Arabia..
<> ML (5)

KAUST Workshop on Distributed Training in the Era of Large Models

-

Auditorium between B4 & 5, L0, R0215

Join leading researchers and innovators to explore how distributed training is reshaping the next generation of large-scale AI models.

Muhammad Samiullah

Cyber Security, FPGA security, AI/ML security

SIAM CSE21 (VIRTUAL) - Minisymposium on HPC Response to the COVID19 Pandemic

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KAUST

Abstract This minisymposium brings together experts in numerical simulation that have developed HPC software tools toward a better understanding coronavirus and the global COVID19 pandemic. Their recent results highlight the importance of computational science as a guiding tool that helps in uncovering the structure and mechanics of the viral spread as well as drastically reduces the number of candidate treatments that need laborious laboratory testing. From transformative medical advances to drug discovery driven by massively parallel supercomputing, this minisymposium will span a range of

A best-first tree-searching approach for ML decoding in MIMO system

1 min read ·
Chung-An Shen, et al., "A best-first tree-searching approach for ML decoding in MIMO system." In Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010, 3533. In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve close to ML performance while minimizing the number of visited nodes. A detailed outline of the algorithm is given, including the required storage. The effects of

Hamzeh Abu Qamar

MS Student, Electrical, Electronics and Communications Engineering at King Abdullah University of Science and Technology (KAUST).
<> Multigrid (5)
KAUST-CEMSE-The-International-Research-Conference-on-Multi-Grid-and-Multi-Scale-Methods-in-Computational-Science

KAUST International Research Conference on Multi-Grid and Multi-Scale Methods in Computational Science, IMG 2025

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Building 19 and 20

The International Conference on Multigrid and Multiscale Methods in Computational Science (IMG) offers a dynamic forum for researchers to share advances in multigrid, multilevel and multiscale computational techniques, as well as their applications across scientific domains.

Neural Operators: Theory, Architecture, and Applications for PDEs

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B1 L3 R3119

Abstract Neural operator methods provide a novel approach for solving or learning the complex mappings from parameters to solutions arising from intricate physical systems. In this talk, I will cover the foundational aspects of neural operators, encompassing both theoretical frameworks and algorithmic developments, including some well-known neural operator architectures. Additionally, I will share our recent work on applying the neural operator method to multiscale partial differential equations (PDEs). To tackle the challenges of multiscale PDEs, we have developed a neural operator with a

Multigrid Monte Carlo Revisited: Theory and Bayesian Inference

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B1 L3 R3119

Abstract The fast simulation of Gaussian random fields plays a pivotal role in many research areas such as Uncertainty Quantification, data science and spatial statistics. In theory, it is a well understood and solved problem, but in practice the efficiency and performance of traditional sampling procedures degenerates quickly when the random field is discretised on a grid with spatial resolution going to zero. Most existing algorithms, such as Cholesky factorisation samplers, do not scale well on large-scale parallel computers. On the other hand, stationary, iterative approaches such as the

Cell-centered extrapolation cascadic multigrid method for solving diffusion equation with discontinuous coeffcients

Xiaoxin Wu, Central South University, China

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https://meeting.tencent.com/dm/bpUiLe2AlgBC

This seminar is an online interview for a postdoctoral position in KAUST.

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 statistics (5)

Scalable Methods for Multivariate Normal Probability Estimation with Applications in Confidence Region Detection, Transport Phenomena, and Parallel Computing Using RCOMPSs

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B2 R5209

This thesis addresses computing high-dimensional multivariate normal (MVN) probabilities in environmental and geospatial applications by combining high-performance computing, numerical approximation, and transport-based covariance modeling to make several important spatial procedures usable at larger scales.

Modeling Complex Dependence in Multivariate Time Series, with Applications to Brain Signals

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This thesis develops approaches to address issues and limitations associated with multivariate processes generated from unknown complex systems such as brain signals.

A Unified and Computationally Efficient Non-Gaussian Statistical Modeling Framework

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B4 R5209

This thesis develops a linear latent non-Gaussian modeling framework that extends latent Gaussian models to accommodate skewness, heavy tails, and extremes while preserving computational tractability, along with its implementation in the R package ngme2.

Data-driven Anomaly Detection in Industrial Processes

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B9 L2 R2325

This talk presents a model-based anomaly detection framework, along with data-driven process monitoring approaches based on multivariate statistical methods and artificial intelligence techniques.

Maicon J. Karling

Postdoctoral Research Fellow, Statistics
Education B.Sc. in Mathematics (2014) - University of Coimbra, Portugal. B.Ed. in Mathematics (2015) - Unisinos, Brazil. M.Sc. (2017) and Ph.D. (2021) in Mathematics: Probability and Statistics - Federal University of Rio Grande do Sul, Brazil. Research Interests Goodness-of-fit tests, multivariate statistics, skewed distributions, and time series.
<> nanostructures (5)

Multiphysics Simulation of Semiconductor-based Terahertz Devices

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B9 H1

Semiconductor-based terahertz (THz) devices such as photoconductive antennas (PCAs) and photomixers (PMs) are widely studied as promising candidates of THz source generation and signal detection. Recent experimental research has shown that using nanostructures in the design of these devices dramatically enhances their optical-to-THz conversion efficiency, possibly allowing their use in widespread industrial applications. However, the nanostructures also increase the complexity of design and fabrication.

Researchers from Photonics laboratory demonstrates a record bandwidth of 700 nm from novel III/V semiconductor based broadband light emitters

1 min read ·
Researchers from Photonics laboratory demonstrates a record bandwidth of 700 nm from novel III/V semiconductor based broadband light emitters.

KAUST Ph.D. student wins Magnetism as Art Showcase Award

1 min read ·
Jose Efrain Perez, a Ph.D. student based in the University's Sensing, Magnetism and Microsystems Laboratory, won the Magnetism as Art Showcase People's Choice Award at the 62nd Annual Conference on Magnetism and Magnetic Materials (MMM) 2017 for his artwork entitled "Magnetic Nanobeacon." Efrai­n Perez, who is supervised by Professor Jurgen Kosel, won the award at the MMM's annual showcase which was held in Pittsburgh from November 6 to 10, 2017. His colleague Zahra Albu presented and accepted the award on his behalf.

Liang Chen

Education Ph.D., Microelectronics and Solid-State Electronics, Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences (CAS), Shanghai, China, 2012 M.S., Microelectronics and Solid-State Electronics, Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences (CAS), Shanghai, China, 2009 B.S., Applied Physics, Southeast University, Nanjing, China, 2007 Professional Appointments Postdoctoral Research Fellow in Electrical and Computer Engineering, Division of Computer, Electrical and Mathematical Science and

Haiding Sun

Postdoctoral Research Fellow, Advanced Semiconductor Laboratory
Haiding Sun was a Postdoctoral Research Fellow working with Professor Xiaohang Li at the Advanced Semiconductor Laboratory at King Abdullah University of Science and Technology (KAUST). Education and Early Career Dr. Sun received his Ph.D. in Electrical Engineering from Boston University, Massachusetts, in the United States in 2015. His Ph.D. dissertation title was “Development of Aluminum Gallium Nitride-Based Emitters In The Form of Graded-Index Separate Confinement Heterostructure (GRINSCH)." Research Interests Dr. Sun ’s research works cover various aspects of semiconductor device designs
<> networks (5)

Enabling Seamless Connectivity via Virtualization Technologies in 6G Integrated Networks

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B1 R4214

This thesis investigates how integrated networks powered by such technologies can be designed and optimized to enable seamless connectivity.

β-contraction: a Framework for Contracting Coloured Networks. Use Cases and Applications

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B4 L5 R5220

Networks are nowadays pervasive in Big Data. It is often useful to regroup such data in clusters according to distinctive node features and use a representative element for each cluster, hence generating a novel contracted graph that shrank in size.

A clique away from more efficient networks

1 min read ·
An old branch of mathematics finds a fertile new field of application.

Intelligent surfaces signal better coverage

1 min read ·
A mathematical model shows specialized reflective panels could be deployed on a large scale to enhance communication networks in urban areas.

Sahar Ammar

Sahar Ammar’s research focuses on network slicing in integrated terrestrial and non-terrestrial networks.
<> nonlinear PDEs (5)

The invisible architect

4 min read ·
Most people never see the mathematics running beneath modern life. CEMSE Professor Miguel Urbano is making sure it works when it matters most.

Rafayel Teymurazyan

Rafayel Teymurazyan works on nonlinear partial differential equations and free boundary problems arising from applications in bio-technologies, chemical engineering, financial mathematics, and optimal design, among others.

Miguel Urbano

Professor Urbano’s research interests are in regularity theory for nonlinear partial differential equations, in particular of singular or degenerate type, arising from different applications, like phase transitions, flows in porous media or semi-supervised learning. He is also interested in free boundary problems, focusing on understanding the local behaviour of weak solutions and the geometric properties of interfaces.

Diogo Gomes

Professor Diogo Gomes, a distinguished expert in Applied Mathematics and Computational Science at KAUST, leverages advanced mathematics – including partial differential equations, numerical methods and mean-field game models – to solve complex problems in social sciences, economics and finance

Athanasios Tzavaras

KAUST Professor of Applied Mathematics and Computational Science Athanasios (Thanos) Tzavaras specializes in mathematical modelling, analysis and computation of partial differential equations pertaining to fluid mechanics or modeling of materials.
<> nonparametric statistics (5)

Emmanuel Ambriz

Postdoctoral Research Fellow, Statistics

Bayesian Regression Trees, Nonparametric Heteroscedastic Regression Modeling and MCMC Sampling

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B1 L2

In this talk, we introduce a new Bayesian regression tree model that allows for possible heteroscedasticity in the variance model and devise novel MCMC samplers that appear to adequately explore the posterior tree space of this model.

Ziling Ma

Ph.D. Student, Statistics

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

Pavel Krupskiy

Postdoctoral Research Fellow, Statistics
Krupskiy, Pavel Postdoctoral Fellows ​​Ph.D. 2014, University of British Columbia, Canada​​ Now Assistant Professor at University of Melbourne Education ​ Ph.D. in Statistics 2014, University of British Columbia, Canada M.A. in Economics 2009, New Economic School, Russia B.Sc. in Mathematics 2006, Lomonosov Moscow State University, Russia Research interests copulas, multivariate extremes, nonparametric statistics, spatial data
<> NTN Communication (5)

Mukhtiar Ahmad

Postdoctoral Research Fellow, Electrical and Computer Engineering
Mukhtiar Ahmad is currently a Postdoctoral Researcher at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. His research interests encompass Non-Terrestrial Networks (NTN), terrestrial cellular networks, distributed systems, and edge computing, with a primary focus on enabling Ultra-Reliable Low-Latency Communication (URLLC) applications. Education and Early Career Mukhtiar Ahmad received the M.Sc. and M.Phil. degrees in Electronics from Quaid-i-Azam University, Islamabad, Pakistan, and the Ph.D. degree in Electrical Engineering from the Lahore University of Management

KAUST researchers propose a distributed coordination framework for heterogeneous non-terrestrial networks

2 min read ·
First analyzed the unique characteristics of non-terrestrial networks (NTN) platforms with impact on network specification, and proposed an efficient distributed coordination framework for heterogeneous NTN, verified by a case study on IAB-enabled heterogeneous UAV networks.

Soon: The 6th KAUST 6G Summit

1 min read ·
About the Summit The Internet and Communication Technology (ICT) in bringing a revolution in almost all aspects of human life. As the fifth generation (5G) of wireless communication systems (WCSs) have extensively deployed worldwide, 6G is expected to be the next focus in wireless communication and networking and aim to provide new superior communication services to meet the future hyper-connectivity demands in the 2030s. The 6th KAUST 6G Summit promotes research and innovation in 6G technology, which has the potential to revolutionize industries like telecommunications, manufacturing
KAUST-CEMSE-ECE-Omar-Khalifa-Winner-Of-Non-Terrestrial-Networks-for-6G-(NTNYS'24

KAUST ECE students achieve high honors in Competition on Non-Terrestrial Networks for 6G (NTNYS'24)

4 min read ·
KAUST Ph.D. candidate Omar Khalifa earned an impressive second place in the global Competition on Non-Terrestrial Networks for 6G (NTNYS'24). The IEEE Future Networks Initiative organized the competition as part of the "Connecting the World from the Skies Global Forum," which took place last November in Riyadh. Second place, and a prize of $10,000, was awarded to Khalifa based on his work titled "Supplying Data for Digital Twins in Green Smart Cities: A Non-Invasive NTN-IoT Approach." The international forum, which focused on the theme “Shaping the Future of Converged Connectivity,” was hosted

Hao Lin

KAUST provides the best environment for us to develop. At KAUST, there are many excellent Professors and friends who can study and do research together. Communication Engineering is an interesting subject that is a key tech for the future. Communication Theory is highly worthy of our in-depth research.
<> oil and gas sensors (5)

Additively Manufactured Conformal Microwave Sensors for Applications in Oil Industry

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B3 L5 R5220

Modern industries are adapting smart ways of monitoring their processes to ensure smooth operations. Sensors capable of early detection of a problem are becoming the norm in industrial processes. This is key to the development of the “Internet of Things” (IoT), in which billions of interconnected devices will work together to make smart decisions. Sensors that can detect and communicate the process information are essential ingredients of any IoT-enabled network. Since billions of such sensor nodes will be required in the future, the low cost will be an important feature for these devices. Consistent with the above-mentioned trends, the oil industry is also adapting smart monitoring and actuation mechanisms for its day-to-day operations. This thesis is focused on developing low-cost sensors, which can increase oil production efficiency through real-time monitoring of oil wells and also help in the safe transport of oil products from the wells to the refineries.

Muhammad Akram Karimi secures 3rd prize Best Paper Award at IMS - world's most prestigious microwaves conference

1 min read ·
Karimi's work on low cost and zero weight water-cut sensors stood out for its quality and distinctive application-direct approach. Successfully, he proved cost reductions of 100 times lower and dropping weight to 1,000 times below than the ones currently available in the market.

Ph.D. student Muhammad Akram Karimimi among Best Paper Award finalists

1 min read ·
Ph.D. student Muhammad Akram Karimimi from the research team of Atif Shamim, Assistant Professor of Electrical Engineering at KAUST and Director of IMPACT Laboratory, was one of the finalists in the Student Paper Competition at the International Microwave Symposium held in San Francisco, California, in May 2016.

CEMSE Students: Muhammad Akram Karimi

2 min read ·
Muhammad Akram Karimi describes himself as an inquisitive-minded researcher who loves to solve industrial challenges through science and technology. Karimi is a third-year Ph.D. student working in the Integrated Microwaves Packaging Antennas & Circuits Technology (IMPACT) Lab under the supervision of Professor Atif Shamim. His current research focus is on the design of low-cost and printed microwave sensors for various industrial applications, with a prime focus on the oil industry.

Muhammad Akram Karimi

Muhammad Akram Karimi obtained his Ph.D. 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). Research Interest Muhammad's research interests included the Design of Cost-Effective and robust Fluidic Sensors to characterize fluids (esp. Crude Oil) and Energy Harvesting. Selected Publications ​Journal : M. A. Karimi, M Arsalan and A. Shamim, "Low cost and pipe conformable microwave-based water cut sensor", IEEE Sensors
<> organic electronics (5)

Organic Electronics for Diagnostics in Physiological Media

Prof. Sahika Inal, Biological, Environmental Science and Engineering, KAUST

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B9 L2 H1

Organic mixed (ionic and electronic) charge conductors and devices offer a new toolbox for interfacing with biological systems.

Sahika Inal

Associate Professor, Bioengineering
Professor Sahika Inal's research bridges the fields of organic electronics and biology, focusing on the development of bioelectronic materials for real-time health monitoring and intervention.

Murilo Calil Faleiros

M.S. Student, Bioengineering
Murilo Calil Faleiros is a Medical Physicist, currently a Bioengineering Ms/PhD student at Sensors Lab, King Abdullah University of Science and Technology (KAUST). His areas of focus include Organic Electronics, Organic Transistors, Biosensors and Device developments. Education and Early Career Murilo Calil Faleiros received his bachelor’s degree in Medical Physics from University of São Paulo, Brazil. Research Interests Murilo Calil Faleiros is interested in the development of devices for biomedical applications and organic electronics, such as organic field effect transistors and others

Jokubas Surgailis

Research Interest Jokūbas is currently investigating mixed conduction in organic semiconductors. Using combined electrochemical characterization methods, he aims to advance the understanding of ion-to-electron coupling. Along with his background in Electrical Engineering, Jokūbas plans to use this research to push the frontier of interfacing the two halves of Bioelectronics. KAUST Affiliations ​Biological and Environmental 
Science & Engineering Division (BESE) Education Profile 2018 - 2024: PhD student, Organic Bioelectronics Lab, KAUST, Thuwal, Saudi Arabia 2017: Visiting student, Organic

Eloise Bihar

Postdoctoral Research Fellow, Sensors
Eloise is a postdoctoral fellow specialized in the field of Printed electronics for biomedical applications. Education and early career Eloise received her M.Sc. in engineering, from Grenoble INP-Pagora, in Grenoble, France, in 2010. She later received her PhD. in bioelectronics from Ecole des Mines de Saint Etienne in France in 2016 under the guidance of Prof. George Malliaras. She is currently working in Prof. Khaled Salama’s group, in collaboration with the groups of Prof. Inal and Prof. Baran. Research Interests Eloise’s current research focuses on the fabrication of printed autonomous
<> parabolic-hyperbolic PDE (5)

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

Part 1B | PDE Backstepping Boundary Control of Parabolic PDEs

Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

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KAUST

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

Part 1A | PDE Backstepping Boundary Control of Parabolic PDEs

Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

-

KAUST

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

Part 2A | PDE Backstepping Boundary Control of Parabolic PDEs

Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

-

KAUST

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

Part 2B | PDE Backstepping Boundary Control of Parabolic PDEs

Prof. Mamadou Diagne, Rensselaer Polytechnic Institute

-

KAUST

Partial Differential Equations (PDEs) are often used to model various complex physical systems. Representative engineering applications such as heat exchangers, transmission lines, oil wells, road traffic, multiphase flow, melting phenomena, supply chains, collective dynamics, and even chemical processes governing the state of charge of Lithium-ion battery, extrusion, reactors to mention a few. This course will explore the boundary control of a class of parabolic PDE via the well-known backstepping method.
<> phononics (5)

Acoustic metamaterials and metasurfaces for controllable wave manipulation

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B1 L2 R2202

I will provide an overview on recent researches on acoustic and elastic metamaterials and metasurfaces for controllable wave manipulation, we are developing in my group in the University of Lorraine. I first will present some advances related to low-frequency acoustic and vibration shielding/absorption making use of metamaterials1,2 and metasurfaces3,4, and describe the added value that such artificial engineered materials can bring to consider some innovative applications.

Ying Wu awarded Phononics Young Investigator 2017

5 min read ·
Prof. Ying Wu received the 2017 Phononics Young Investigator Award as the Phononics community gathered in Changsha, China, for the 4th International Conference on Phononic Crystal/Metamaterials, Phonon Transport/Coupling, and Topological Phononics, on June 4-9 2017.

Zeguo Chen

Master, Nanjing University 2014 Bachelor, Nanjing University 2011 Research Interests Wave propagation in Metamaterials and Phononic Crystals.

Ying Wu

Professor Wu works on theoretical modeling and numerical simulations of classical wave propagation in complex media, including metamaterials, metasurfaces, topological materials and random systems. She is recognized by effective medium theory, perturbation theory for periodic structures with resonances.

Mohamed D. Farhat

Research Scientist, Waves in Complex Media
Mohamed Farhat is currently a Research Scientist at King Abdullah University of Science and technology (KAUST), Thuwal, Saudi Arabia.
<> plasmonics (5)

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.

New nanolasers for quantum information sources

1 min read ·
Integrating coherent light sources at the nanoscale with spasers is one of the most promising applications of plasmonics. In a spaser, localized plasmon polaritons (LPPs) waves occurring at the metal-dielectric interface are amplified by an active medium. Under specific conditions, the gain of plasmonic modes can overcome the absorption losses occurring in the metal and stimulated emission of radiation occurs, as experimentally observed in optically pumped spasers. Despite the large body of experimental research, the theoretical understanding of the spaser dynamics is still challenging

Mohamed D. Farhat

Research Scientist, Waves in Complex Media
Mohamed Farhat is currently a Research Scientist at King Abdullah University of Science and technology (KAUST), Thuwal, Saudi Arabia.

Ismail Enes Uysal

Ismail Enes Uysal is a Ph.D. candidate in Electrical engineering at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Hakan Bagci. Ismail received the Bachelor of Science and Master of Science degrees in Physics from Koc University, Turkey in 2009 and 2011, respectively. Research Interests Ismail's research interests include Computational physics and electromagnetics scattering properties of dispersive media and plasmonic structures. Education Profile M.S. in Physics, Koc University, Istanbul, Turkey 2011 B.S. in Physics, Koc University, Istanbul

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
<> printed electronics (5)

Weiwei Li

Weiwei Li is a Postdoctoral Fellow working under the supervision of Professor Atif Shamim at Integrated Microwaves Packaging Antennas and Circuits Technology (IMPACT) Research Group in King Abdullah University of Science and Technology (KAUST). Research Interests ​Weiwei's research interests include Ink formulation, Printed electronics, Electromagnetic metamaterials, and Diodes. Education Profile Ph.D. in Nanoscience and Technology, National Center for Nanoscience and Technology, Chinese Academy of Sciences, 2013-2017. M.S. in Materials Physics and Chemistry, Beijing Institute of Graphic

Nidhi Mishra

Nidhi Mishra 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 Nidhi's research interests included ​Printed electronics, Antennas, and Microwave circuits. Education Profile Bachelor's in Electronics and Instrumentation, M.J.P. Rohi​lkhand University​​, India. Master's in Digital Communication, Uttarakhand Technical University, India.

Mitta Divya

Dr. Mitta Divya is a Postdoctoral Researcher, joined in May 2023, in Professor Atif Shamim's Integrated Microwave Packaging Antennas and Circuits Technology (IMPACT) research group at King Abdullah University of Science and Technology (KAUST) Research Interests Printed electronics Inorganic oxide semiconductors Electrolyte gating Field-effect transistors and circuits Low temperature processing for flexible devices Sensors Selected Publications Mitta Divya, Nikhil Cherukupally, Sanat Kumar Gogoi, Jyoti Ranjan Pradhan, Sandeep Kumar Mondal, Manish Jain, Anatoliy Senyshyn, Subho Dasgupta, “Super

Derya Baran

Derya Baran is a leading researcher in organic and hybrid semiconductors, focusing on their applications in solar cells, thermoelectrics, and bio-electronics, with an emphasis on interface engineering and sustainable, solution-processable materials.

Dante Serrano Kobylyansky

Dante Serrano Kobylyansky is an MS student in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), conducting research within the Integrated Microwaves Packaging Antennas & Circuit Technology Research Group under the supervision of Professor Atif Shamim. Educational Profile Dante obtained his bachelor's degree in Nanotechnology from the National Autonomous University of Mexico in June 2023. He joined KAUST as an Electrical and Computer Engineering student with the Integrated Microwaves Packaging Antennas & Circuit Technology (IMPACT) Research Group
<> Quantitative finance (5)

Statistical Modeling of Financial Extremes and Volatility Dynamics

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B2 R5220

This thesis provides comprehensive statistical tools for understanding and modeling extreme risks and volatility dynamics in financial markets.

Christian Bayer

Christian Bayer's research focuses on financial mathematics and stochastic numerics, including modelling stock indices and numerical approximation of stochastic optimal control problems.

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

2 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.

Junshu Jiang

Ph.D. Student, Statistics

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
<> Radio Frequency Integrated Circuits (5)

CEMSE New Faculty: Abdulrahman Alhamed, assistant professor of electrical and computer engineering

2 min read ·
CEMSE Professor Abdulrahman Alhamed’s research path was formed by a deep recognition of the pivotal role integrated circuits play in shaping the modern world. “While there was no single 'eureka' moment, my progression into academia was deliberate and purpose-driven,” he noted. “I was fortunate to have mentors who challenged me early on and environments that cultivated intellectual rigor.” Dr. Alhamed is an assistant professor of electrical and computer engineering, specializing in RF integrated circuits and systems. His research spans transceivers, phased arrays, radar systems and creating

Abdulrahman Alhamed

Dr. Abdulrahman Alhamed is an assistant professor of Electrical and Computer Engineering at KAUST, specializing in RF integrated circuits and systems. His research focuses on advancing wireless technologies for telecommunications and sensing applications

Two KAUST students selected for the Three Minute Thesis 3MT competition final at IMS2017

3 min read ·
This year, KAUST took the lion's share at the Three Minute Thesis (3MT(R)) contest at the annual IEEE microwave symposium IMS2017, with two students selected to take part in the final and one of them - Dr. Farhan Abdul Ghaffar - finishing within the top 4 and getting Honorable Mention for his presentation.

Haoran Zhang

Haoran Zhang is a Ph.D. student in the Electrical Engineering department at Integrated Microwaves Packaging Antennas & Circuit Technology Research Group under the supervision of Professor Atif Shamim at King Abdullah University of Science and Technology (KAUST). Research Interests Millimeter-wave on-chip antenna design and Radio Frequency Integrated Circuits (RFIC)​ design 5G Array Antenna in Package design Education Profile Bachelor of Engineering in Electrical Engineering, University of Electronics of Science and Technology, China (2013 - 2017).

Farhan Abdul Ghaffar

Farhan Abdul Ghaffar graduated with a Ph.D. degree and an M.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, Farhan is working as a Post Doctoral Fellow/Instructor at the University of Ontario Institute of Technology (UOIT)​. Research Interests Farhan's research interests included Fractal Antenna Design for System on Package (SoP) and System on Chip (SoC) Applications, Ferrite LTCC Based Tunable
<> regularity (5)

A very short introduction to regularity theory for linear elliptic equations - Part 1

Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal

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B1 L3 R3119

Mini Course Part 1 of 4. The course is a very short introduction to regularity for linear elliptic pdes of second order. We start with equations with regular coefficients and the difference quotient method of Nirenberg. We then treat the case of coefficients that are merely measurable and bounded, putting forward the basics of De Giorgi-Nash-Moser theory. If time permits, we present some characterizations of Hölder spaces which are very useful in regularity theory.

A very short introduction to regularity theory for linear elliptic equations - Part 3

Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal

-

B1 L3 R3119

Mini Course Part 3 of 4. The course is a very short introduction to regularity for linear elliptic pdes of second order. We start with equations with regular coefficients and the difference quotient method of Nirenberg. We then treat the case of coefficients that are merely measurable and bounded, putting forward the basics of De Giorgi-Nash-Moser theory. If time permits, we present some characterizations of Hölder spaces which are very useful in regularity theory.

A very short introduction to regularity theory for linear elliptic equations - Part 4

Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal

-

B1 L3 R3119

Mini Course Part 4 of 4. The course is a very short introduction to regularity for linear elliptic pdes of second order. We start with equations with regular coefficients and the difference quotient method of Nirenberg. We then treat the case of coefficients that are merely measurable and bounded, putting forward the basics of De Giorgi-Nash-Moser theory. If time permits, we present some characterizations of Hölder spaces which are very useful in regularity theory.

A very short introduction to regularity theory for linear elliptic equations - Part 2

Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal

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B1 L2 R2202

Mini Course Part 2 of 4. The course is a very short introduction to regularity for linear elliptic pdes of second order. We start with equations with regular coefficients and the difference quotient method of Nirenberg. We then treat the case of coefficients that are merely measurable and bounded, putting forward the basics of De Giorgi-Nash-Moser theory. If time permits, we present some characterizations of Hölder spaces which are very useful in regularity theory.

Rafayel Teymurazyan

Rafayel Teymurazyan works on nonlinear partial differential equations and free boundary problems arising from applications in bio-technologies, chemical engineering, financial mathematics, and optimal design, among others.
<> research conference (5)

Prof. Keyes opening virtually the ISC event

1 min read ·
Prof. Keyes and team successfully run virtually the ISC event: catch up on the opening session below! Read the full article here.

ECRC contributions to SIAM CSE21

4 min read ·
ECRC @ SIAM CSE21! Follow us @KAUST_ECRC As in previous SIAM conferences on Parallel Processing (PP) and Computational Science and Engineering (CSE), ECRC members and their collaborators will have a strong presence at SIAM CSE21, nominally in Fort Worth, Texas, but held virtually due to the pandemic. ************************************************** SIAM CSE21 will run virtually with live sessions. ************************************************** Registration to SIAM CSE is required to gain access to the online platform and attend live sessions. Once registered, please use your personal

KAUST Research Conference of Robotics and Autonomy 2021

1 min read ·
The KAUST Research Conference on Robotics and Autonomy 2021, #RobotoKAUST, brought together leading international and in-Kingdom robotics researchers and government and industry representatives from the robotics industry to discuss robotics and its applications. The online event was organized by Prof. E. Feron, Prof. B. Ghanem, Prof. X. Zhang and had six sessions on Marine Robotics, Human-Robot Interactions, Aerospace Robotics, Mobile Robotics, Wearable Robotics & Microrobotics, Assured Autonomy. Twenty-seven speakers (seven from KSA including three from KAUST, and three from industry)

The Recordings of the #RobotoKAUST talks are available

1 min read ·
The first KAUST Research Conference on Robotics and Autonomy 2021, #RobotoKAUST, brought together leading international and in-Kingdom robotics researchers and government and industry representatives from the robotics industry to discuss robotics and its applications. The recordings of the talks are available online! To watch the talks, please visit our website #RobotoKAUST or our KAUST RISC Lab YouTube Channel.

The KAUST Research Conference on Robotics and Autonomy 2022 #RobotoKAUST

1 min read ·
Building upon our successful online conference in spring 2021, the KAUST Robotics, Intelligent Systems, and Control Lab (RISC Lab) will host the KAUST Research Conference on Robotics and Autonomy 2022 (#RobotoKAUST2022) from February 28 until March 2, 2022. The conference will address the most recent trends of robotics application in a range of disciplines.
<> scientific research (5)

The Role of Humans in Scientific Discovery in the Age of LLMs — Beyond Asking: Turning LLMs into Research Collaborators

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B9 R2325

Rather than offering definitive conclusions, this talk seeks to stimulate dialogue, question assumptions, and inspire new forms of collective thinking about the future of scientific research and doctoral training in an AI-driven world.

Publication Ethics and Authorship - Including the Responsible and Ethical Use of AI in Research

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B9 R2325

This talk outlines essential publication ethics and best practices at KAUST, focusing on authorship criteria, researcher responsibilities, dispute resolution, and the ethical use of AI in scholarly writing.

Introduction to Research Ethics and Integrity - Including Issues Around Research Misconduct

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B9 R2325

This talk outlines KAUST's research ethics governance, detailing the submission processes for Research Ethics Committees and the institutional procedures for reporting misconduct and grievances.

Everything PhD students always wanted to know about research* (*but were afraid to ask)

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B9 L2 R2322 H1

From my experience, I will try to answer doubts and dilemmas PhD students are often faced with, in their path towards a degree. Namely, I'll discuss how advisors, colleagues, peers, reviewers and so forth, fit in the universe of a PhD student, and I will end sharing my own definition of 'excellence', as an objective to pursue.
Qusai Ghabrah

Qusai A. Ghabrah

M.S. Student, Computer Science
Qusai Ghabrah is a computer science master's student at KAUST with a strong background in software engineering and technical project management, who has worked on an LLM-assisted system testing tool for microservices as part of his research project.
<> seismic imaging (5)

Superior seismic imaging for better drilling

1 min read ·
Software could transform underground imaging of fossil fuel reserves by providing unprecedented detail in record time.

Code of collaboration

2 min read ·
David Keyes's and Matteo Ravasi's cross-disciplinary project results in improved efficiency for seismic processing, with promising applications for the energy industry.

Designing Tomorrow's Algorithms on Today's Architectures: a Case Study with Stencil Computations Using AMD 3D V-Cache™ Technology

2 min read ·
Regular stencil computations constitute the main core kernel in many temporally explicit approaches for structured grid finite-difference, finite-volume, and finite-element discretizations of partial differential equation conservation laws. For various blocking dimensions, the Spatial Blocking (SB) approach enables data reuse within multiple cache levels. However, the straightforward generalization of SB to manycore architectures, with each core owning an exclusive share of cache may leave performance on the table. The next two figures show the typical 25-point 3D star stencil used in seismic

Long Qu

Kadir Akbudak

Dr. Kadir Akbudak is a Consultant at Extreme Computing Research Center at KAUST, working with Professor David E. Keyes and Dr. Hatem Ltaief. Research Interests Kadir Akbudak's research interests include Combinatorial scientific computing, Graph and hypergraph partitioning, Locality-aware partitioning and scheduling, High performance kernels for sparse computations, Vectorization for irregular applications, Iterative numerical methods and Parallel numerical algorithms. Education Profile Ph.D., Computer Engineering, Bilkent University, 2015. M.S., Computer Engineering, Bilkent University, 2009
<> semiconductor laser (5)

Professor Boon Ooi elected Fellow of the American Physical Society

3 min read ·
KAUST Professor Boon S. Ooi has been elected an APS Fellow for pioneering work in semiconductor photonics integration and laser technology.

Semiconductor Epitaxy for Micro-LEDs and Novel Lasers

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B9 L2 H2

InGaN-based monolithic RGB LED arrays would be the key to producing micro-LED displays. The micro-LED displays will reduce the frequency of battery charging for mobiles and make head-mount displays thinner and lighter weight. It will become a game changer.

Lasers bridge the rainbow

1 min read ·
Subtle changes to the composition of a semiconductor structure enable laser light at colors previously not thought possible.

New publication on eLight

3 min read ·
On 4 Jan., Integrated Photonics Lab (IPL) has published a latest review article on eLight titled “ Prospects and applications of on-chip lasers”. The article received plenty of attention in a short period of time and was selected as the cover article of the issue. Prof. Huiyun Liu's team from UCL has wrote the News & Views about the article and published on Light, titled as " From past to future: on-chip laser sources for photonic integrated circuits". Now is available online. The following quotes from the EurekAlert! report on this work. ( original report page) Global consumer Internet

Guangyu Liu

Dr. Guangyu Liu is the assistant dean of CEMSE at KAUST, supporting the Division’s strategic priorities, interdisciplinary research and external engagement.
<> Smart Cities (5)

Saudi smarter cities start with KAUST

1 min read ·
A KAUST-developed system offers scalable, real-time data to address urban air pollution

LEAP Tech Conference 2023

1 min read ·
MERGE Group participated in the LEAP Tech Conference from 6-9 February 2023 in Riyadh. Leap Tech Conference is a global platform for future technologies where pioneering technology professionals worldwide convene to network and share innovations. It was an exciting four-days conference where we showcased innovative ideas on Digital Twin Cities. As the Kingdom has embraced metaverse technologies like city-scale digital twins. A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or process. City-scale digital twins are a key component

KAUST Research Open Week 2023

2 min read ·
KAUST Research Open Week (KROW) was held from 27 February 2023 to 2 March 2023. A week-long forum held at the University Campus under the theme “Research for the Future of Saudi Arabia”. KROW is an opportunity to bring science to the heart of KAUST community and celebrate the excellent research in KAUST. KROW provided a unique forum for a broader discussion providing networking opportunities to faculty, research staff, students and colleagues from industry and government entities. MERGE Group participated in the Scientific Exhibition, Poster Session and ANPERC Open Doors. KAUST Digital Twin
Hakim Ghazzai

Hakim Ghazzai

Senior Research Scientist, Electrical and Computer Engineering
Hakim is a researcher focusing on designing multi-disciplinary innovative solutions for diverse smart city applications and services.

Charalampos Antoniadis

<> software (5)

Trees, Algebras, and Differential Equations: Extending the B-series.jl package for numerical analysis of initial value problems

In this project we seek to extend the capabilities of bseries.jl to new classes of methods and/or new kinds of analysis. There are a number of possible directions and the specific one chosen will depend on the interests and knowledge of the student. Possibilities include extensions to:- Multi-derivative methods - Partitioned methods (e.g. for Hamiltonian systems) - General linear (multistep, multistage) methods - Exponential methods - Alternative bases for order conditions - Application of simplifying assumptions in method design - Generalized additive Runge-Kutta methods - Characterization of energy-preserving B-series - Extensions of B-series, such as aromatic B-series, exotic B-series, and S-series.

Yasser Jaber

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).

Vulnerability discovery in binaries and protocols

Prof. Sven Dietrich, the Computer Science Department, Hunter College, the City University of New York (CUNY)

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B5 L5 R5209

Vulnerability discovery can be challenging: many software packages, both open and closed-source projects, build on existing code from public software repositories to network drives, derived from earlier versions or related software packages. Even implemented protocols rely on such repositories. It is important to detect such copies of code when the original code contains a software vulnerability, especially one that is exploitable, as seen with flaws such as the bash vulnerability Shellshock or the SSL vulnerability Heartbleed.

Efficient Computation Through Tuned Approximation

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B9 L2 R2322 H1

Numerical software is being reinvented to provide opportunities to tune dynamically the accuracy of computation to the requirements of the application, resulting in savings of memory, time, and energy. Floating point computation in science and engineering has a history of “oversolving” relative to expectations for many models. So often are real datatypes defaulted to double precision that GPUs did not gain wide acceptance until they provided in hardware operations not required in their original domain of graphics. However, computational science is now reverting to employ lower precision arithmetic where possible. Many matrix operations considered at a blockwise level allow for lower precision and many blocks can be approximated with low rank near equivalents.

Efficient Machine Learning across Hardware, Software, and Algorithms

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B2 L5 R5209

Deep neural networks (DNNs) are revolutionizing computing, necessitating an integrated approach across the computing stack to optimize efficiency. In this talk, I will explore the frontier of DNN optimization, spanning algorithms, software, and hardware. We'll start with hardware-aware neural architecture search, demonstrating how tailoring DNN architectures to specific hardware can drastically enhance performance.
<> SPDEs (5)

SPDE-Based Geostatistical and Point Process Models for Environmental and Urban Network Applications

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This thesis develops statistical models based on stochastic partial differential equations (SPDEs) for geostatistical and point process data, with applications to oceanographic monitoring, traffic safety, and urban air quality.

rSPDE

rSPDE: A Computational Framework for Rational Approximations of Fractional Stochastic Partial Differential Equations

Statistical Models and Methods Based on Stochastic Partial Differential Equations

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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.

Statistical models based on stochastic partial differential equations

Prof. David Bolin, Statistics, KAUST

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B9 L2 H1 R2322

The talk will give an overview of some recent developments of statistical models based on stochastic partial differential equations. We will in particular focus on equations with non-local differential operators or non-Gaussian driving noise, and explain when any why such models are useful. As motivating applications, analysis of longitudinal medical data and ocean waves will be considered.

Stochastic Partial Differential Equations (SPDEs)

1 min read ·
Mathematical models are widely used in physics and engineering applications as predictive tools. However, in many situations, the input parameters of the model are uncertain due to either a lack of knowledge or an intrinsic variability of the system. Examples are the study of subsurface phenomena, biological tissues, complex materials, whose properties are often heterogeneous, not perfectly characterized and, possibly, changing in time in an uncertain way. In this line of research we consider the case in which the uncertainty can be described reasonably well in a probabilistic setting and we
<> stochastic algorithm (5)

Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2026

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B2/3 A0215

Workshops
Bringing together experts in stochastic algorithms, numerical analysis and statistical learning with applications in climate modeling and quantitative finance.
Stochastic Numerics and Statistical Learning Workshop

Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2025

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Auditorium 0215 between B2 & B3

Explore the latest in stochastic algorithms, statistical learning and optimization at KAUST’s Stochastic Numerics and Statistical Learning Workshop 2025.

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.

Proximal Algorithms for Large-Scale Convex Non-smooth Optimization

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B2 L5 R5220

Convex nonsmooth optimization problems, whose solutions live in very high dimensional spaces, have become ubiquitous. To solve them, the class of iterative fixed-point algorithms known as proximal splitting algorithms is particularly adequate: they consist of simple operations, handling the terms in the objective function separately. I will present a selection of recent primal-dual algorithms within a unified framework, which consists in solving monotone inclusions with well-chosen spaces and metrics.

Slavomir Hanzely

Slavomir Hanzely is an MS/Ph.D. student in the Applied Mathematics and Computational Science Program under the supervision of Professor Peter Richtarik at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Slavomir earned his Bachelor's Degree in Informatics with a background in both Mathematics and Computer Science from the Faculty of Mathematics, Physics and Informatics University (FMPH UK), Slovakia in 2019. Research Interest He is interested in Machine Learning, Federated Learning, and Stochastic Algorithms. Education
<> stretchable electronics (5)

Stretchable Electronics Make Thermotherapy Easier for Arthritis Patients

2 min read ·
A paper has been published to cover a new technology that makes electronic devices stretchable while retaining their electrical and thermal properties.

Smart skin for flexible monitoring

1 min read ·
An electronic tag that stretches and flexes while it records location and environmental data can monitor marine animals in their natural habitat.

Plant Wearables and Airdropped Sensors Could Sow Big Data Seeds

1 min read ·
Stretchable plant wearables and smart tags dropped by drones aim to help give farming a big data makeover. The relatively cheap technologies for mass monitoring of individual plants across large greenhouses or crop fields could get field tests in three countries starting in 2019. The idea came from researchers at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia with expertise in flexible electronics. After talking with colleagues who were cultivating genetically engineered plants in greenhouses, they recognized the need for inexpensive sensors that could be deployed

Transforming electronics

2 min read ·
KAUST Professor of Electrical Engineering Muhammad Mustafa Hussain was recently elected as an Institute of Electrical and Electronics Engineers (IEEE) Fellow, effective January 1, 2020, for his "contributions to flexible and stretchable electronic circuits," IEEE stated.

Aftab Hussain

Aftab Hussain received both his Master's degree and Ph.D. in Electrical Engineering from King Abdullah University of Science and Technology under the supervision of Prof. Muhammad Mustafa Hussain. He now works as a faculty member at the International Institute of Information Technology in Hyderabad, India. Research Interest Aftab's research interests include nanoelectronics, fabrication processes especially mask design and epitaxial growth process. Education Profile Ph.D., Electrical Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. (2013-2016) M.S
<> synthetic biology (5)

Sharing expert experimental knowledge to expedite design

1 min read ·
A repository of metabolic information provides a quick reference tool for designing useful synthetic biological systems.

Takashi Gojobori

Ibn Sina Distinguished Professor (former), Bioscience
Takashi Gojobori is a Distinguished Professor of Bioscience and Acting Director at the Computational Bioscience Research Center (CBRC) in King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. He currently holds the position of Project Professor at the National Institute of Genetics (NIG), Mishima, Japan. He also works for a number of leading universities such as the University of Tokyo, Waseda University, and Fukushima Prefecture College of Medicine. He is a Visiting Professor for Keio University, Nihon University, and National Cheng Kong University in Taiwan. After

Meshari Alazmi

As a Ph.D. student in Xin Gao's group, Meshari earned his degree in synthetic biology, systems biology, thermodynamics, and protein structure prediction. Thereafter he worked in a similar capacity in Stefan Arold's group and later went on to become an assistant professor at the University of Hail, KSA. Research Interests Meshari Alazmi's research interests are in ​Synthetic Biology, Systems Biology, Thermodynamics, Protein Structure Prediction Scientific and Professional Membership Association for Computing Machinery (ACM) student Chapter Education Profile Ph.D. in computer science, King

Majed Alzahrani

Majed Alzahrani obtained PhD degree in Computer Science from King Abdullah University of Science and Technology in 2017. His PhD thesis supervisor was Professor Xin Gao. After graduating, he joined Saudi Aramco as a data scientist in its Drilling Data Science unit. Working in one of the largest companies in the world is a dream come true for many, for Majed Alzahrani, things couldn't be better. Research Interest Majed's research interests were in machine learning, structural bioinformatics, synthetic biology.

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
<> systems biology (5)

Towards rational design of biosynthesis pathways

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B3 R5209

Recent advances in genome editing and metabolic engineering enabled a precise construction of de novo biosynthesis pathways for high-value natural products. One important design decision to make for the engineering of heterologous biosynthesis systems is concerned with which foreign metabolic genes to introduce into a given host organism.

AI4GH Seminar Series - Towards Rational Design of Biosynthesis Pathways

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B2 R5220

Recent advances in genome editing and metabolic engineering enabled a precise construction of de novo biosynthesis pathways for high-value natural products. One important design decision to make for the engineering of heterologous biosynthesis systems is concerned with which foreign metabolic genes to introduce into a given host organism.

Meshari Alazami defends his thesis proposal

1 min read ·
Meshari Alazami, a Ph.D. student under the supervision of Associate Professor Xin Gao, successfully defended his thesis proposal on May 22, 2018. His topic, "Towards Rational Design of Biosynthesis Pathways", was well received by committee members Associate Professor Xin Gao, Distinguished Professor Takashi Gojobori and Assistant Professor Robert Hoehndorf.

Meshari Alazmi defends his Ph.D. thesis

1 min read ·
Meshari Alazmi, a Ph.D. candidate under the supervision of Associate Professor Xin Gao, defended his Ph.D. dissertation on October 24, 2018.

Meshari Alazmi

As a Ph.D. student in Xin Gao's group, Meshari earned his degree in synthetic biology, systems biology, thermodynamics, and protein structure prediction. Thereafter he worked in a similar capacity in Stefan Arold's group and later went on to become an assistant professor at the University of Hail, KSA. Research Interests Meshari Alazmi's research interests are in ​Synthetic Biology, Systems Biology, Thermodynamics, Protein Structure Prediction Scientific and Professional Membership Association for Computing Machinery (ACM) student Chapter Education Profile Ph.D. in computer science, King
<> thin films (5)

Meng Tang

Meng Tang’s research focuses on the physics and applications of spintronics, with an emphasis on the experimental exploration of spin-orbit torque phenomena and their applications in developing new types of information storage and processing devices. His work aims to contribute to the advancement of information technology with ultra-low power consumption.

Applications of Magnetic Transition Metal Dichalcogenide Monolayers to the Field of Spinorbitronics

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KAUST

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

Methanol and Humidity Capacitive Sensors Based on Thin Films of MOF Nanoparticles

1 min read ·
Miguel Andrés, et al., "Methanol and Humidity Capacitive Sensors Based on Thin Films of MOF Nanoparticles." ACS Applied Materials & Interfaces 12 (3) ,2020, 4155. The successful development of modern gas sensing technologies requires high sensitivity and selectivity coupled to cost effectiveness, which implies the necessity to miniaturize devices while reducing the amount of sensing material. The appealing alternative of integrating nanoparticles of a porous metal–organic framework (MOF) onto capacitive sensors based on interdigitated electrode (IDE) chips is presented. We report the

Coating of Conducting and Insulating Threads with Porous MOF Particles through Langmuir-Blodgett Technique

1 min read ·
Sakandar Rauf, et al., "Coating of Conducting and Insulating Threads with Porous MOF Particles through Langmuir-Blodgett Technique." Nanomaterials 11 (1), 2021, 160. The Langmuir-Blodgett (LB) method is a well-known deposition technique for the fabrication of ordered monolayer and multilayer thin films of nanomaterials onto different substrates that plays a critical role in the development of functional devices for various applications. This paper describes detailed studies about the best coating configuration for nanoparticles of a porous metal-organic framework (MOF) onto both insulating or

Idris H. Smaili

Idris H. Smaili is a Ph.D. student in the electrical and computer engineering program at Computational Physics & Materials Science Lab under the supervision of Prof. Udo Schwingenschlogl at King Abdullah University of Science and Technology (KAUST). Idris obtained his bachelor's degree in Electrical Engineering, Electronics, and Communications from King Abdul-Aziz University (KAU) in Jeddah, Saudi Arabia, in 2007. After that, he joined Rochester Institute of Technology (RIT), Rochester, NY, USA, to receive his master's degree in Microelectronic Engineering in 2014. Idris is a lecturer at the
<> Transistors (5)
KAUST-CEMSE-ECE-PhD-Dissertation-Defense-Dhanu-Chetri-Ultrawide-Bandgap-Semiconductor-Devices-and-Monolithic-Circuits

Ultrawide Bandgap Semiconductor Devices and Monolithic Circuits

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B3 L5 R5220

This thesis investigates the potential of ultrawide bandgap (UWBG) semiconductors like gallium oxide (Ga2O3) and aluminium nitride (AlN) for high-power applications, focusing on the development of monolithic devices and circuits, including pseudo-CMOS inverters, bidirectional switches, and MOSFETs, demonstrating their potential for next-generation electronics operating in extreme environments.

Dr Sandeep's review on OFET is out

1 min read ·
We are excited to share our review on Organic Field Effect Transistors sensing platforms. This is Dr Sandeep's first paper with the group and more to come soon. Organic field effect transistors (OFETs) have been the focus of sensing application research over the last two decades. The challenges and possible future directions of OFET arrays in embedded sensing platforms are presented. More details at: Sandeep G.Surya, Harshil N.Raval, Rafiq Ahmad, PrashantSonar, Khaled N.Salama, V.Ramgopal Rao, Organic field effect transistors (OFETs) in environmental sensing and health monitoring: A review

Approximate Computing With Stochastic Transistors’ Voltage Over-Scaling

1 min read ·
Ren Li, et al., "Approximate Computing With Stochastic Transistors’ Voltage Over-Scaling" IEEE Access 7, 2019, 6373. Ubiquitous computing and the ever-rising need for energy efficiency pose challenges in terms of the processing requirements and the corresponding machine complexity. Nonetheless, the nature of the underlying applications, particularly dealing with real-world data, offers alternative paradigms toward the efficient utilization of the available design resources. In this paper, approximate computing is addressed as an accommodating technique that can benefit from the inherent

All‐Oxide Thin Film Transistors and Rectifiers Enabling On‐Chip Capacitive Energy Storage

1 min read ·
Wang Zhenwei, et al., "All‐Oxide Thin Film Transistors and Rectifiers Enabling On‐Chip Capacitive Energy Storage." Advanced Electronic Materials 5 (12), 2019, 1900531. All-oxide, fully-transparent thin film transistors and rectifiers, processed entirely by atomic layer deposition, have been developed for on-chip capacitive energy storage. Fully depleted thin film transistor (TFT) operation is achieved by optimizing the carrier concentration in the ZnO channels. The TFTs show an average saturation mobility of 10.5 cm2 V−1 s−1, a stable positive turn-on voltage of 0.88 V, a low subthreshold
KAUST-CEMSE-ECE-ASL-Dhanu-Chettri-0561

Dhanu Chettri

<> trustworthy machine learning (5)

The Three Pillars of Practical Machine Learning

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This thesis establishes methods, evaluation protocols, and insights toward machine learning systems that are practical, adaptive, efficient, and trustworthy paving path for practical machine learning that rests on key three pillars: adaptation, efficiency, and trustworthiness.

Learning under Limited Information across Federated, Multi-Agent, and LLM Settings

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B3 R5220

This dissertation studies learning under structural information constraints across three major paradigms: federated learning, cooperative multi-agent reinforcement learning, and black-box optimization of large language models.

What Survives When Code Doesn’t?

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B9 R2325

This talk explores how AI-driven code generation shifts the role of software from a durable artifact to a disposable implementation and argues for a new computational model for agentic software that formalizes the fundamental guarantees of intent, state, composition, and effect into explicit, enforceable contracts.

Yulian Wu

Ph.D. Student, Computer Science
Yulian Wu is a Ph.D. candidate under the supervision of Professor Francesco Orabona at King Abdullah University of Science and Technology (KAUST).

Salma Kharrat

Ph.D. Student, Computer Science
<> Unmanned aerial vehicles UAVs (5)
kaust-cemse-ece-ccsl-yousef-awad

Yousef Awad

Three papers accepted at IEEE WCNC 2019

1 min read ·
Our papers entitled "A Distributed Mechanism for Joint 3D Placement and User Association in UAV-Assisted Networks", "SectOR: Sector-Based Opportunistic Routing Protocol for Underwater Optical Wireless Networks", and "Online Q-Learning Scheme for Energy Efficient Power Allocation in Cognitive Radio Networks" have been accepted for publication at IEEE WCNC.

Our paper entitled "Learn-As-You-Fly: A Distributed Algorithm for Joint 3D Placement and User Association in Multi-UAVs Networks", has been accepted for publication at IEEE Transactions on Wireless Communications.

1 min read ·
Our paper entitled "Learn-As-You-Fly: A Distributed Algorithm for Joint 3D Placement and User Association in Multi-UAVs Networks", has been accepted for publication at IEEE Transactions on Wireless Communications.

Meet KAUST new student: Zhengying Lou

1 min read ·
Zhengying Lou is a communication engineering graduate who joined KAUST from the University of Electronic Science and Technology of China. Zhengying first came to KAUST in June 2020 as a visiting student and was instantly impressed by the university’s high academic standards and convenient living environment.

Bilal Maassarani

Mechatronic systems and control enthusiast currently working on a novel scalable hybrid-flight mode aerial system at the RISC lab with Professor Eric Feron.
<> Wearable (5)

New tech detects dehydration by touching a screen

1 min read ·
A smartphone-style sensor reads moisture levels in skin, offering a low-cost way to monitor health during fasting, exercise or everyday life.

Flexible, Wearable, Disposable Wireless Communication and Sensing Systems Through Additive Manufacturing - 2020

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KAUST

With the advent of wearable sensors and internet of things (IoT), there is a new focus on electronics which can be bent so that they can be worn or mounted on non-planar objects. Due to large volume (billions of devices), there is a requirement that the cost is extremely low, to the extent that they become disposable. The flexible and low-cost aspects can be addressed through additive manufacturing technologies such as inkjet, screen and 3D printing. This talk introduces additive manufacturing as an emerging technique to realize low cost, flexible and wearable wireless communication and sensing systems. The ability to print electronics on unconventional mediums such as plastics, papers, and textiles has opened up a plethora of new applications. In this talk, various innovative antenna and sensor designs will be shown which have been realized through additive manufacturing. A multilayer process will be presented where dielectrics are also printed in addition to the metallic parts, thus demonstrating fully printed components. Many new functional inks and their use in tunable and reconfigurable components will be shown. In the end, many system level examples of wireless sensing applications will be shown. The promising results of these designs indicate that the day when electronics can be printed like newspapers and magazines through roll-to-roll and reel-to-reel printing is not far away.

The raw power of human motion

1 min read ·
Standalone power modules that harvest and convert vibrations from their surroundings into electricity could soon fuel future microsystems.

KAUSTat: A Wireless, Wearable, Open-Source Potentiostat for Electrochemical Measurements

1 min read ·
Ahmad Rafiq, et al. "KAUSTat: A Wireless, Wearable, Open-Source Potentiostat for Electrochemical Measurements." 2019 IEEE SENSORS. IEEE 27, 2019, 1. Advanced technology is needed every day for wireless, wearable sensors/potentiostats to record real-time measurements and monitor the chemical processes and physiological signals of the human body. Most of the potentiostats present on the market work as “black boxes” without access to their internal structure and their limited information of circuitry makes it challenging to develop new measurement methods and further integration with other

Broadening horizons for people with quadriplegia

1 min read ·
An assistive technology uses magnetic skin to support freedom of movement for people with quadriplegia.
<> wearable devices (5)

Self-aware biosensors boost digital health monitoring

1 min read ·
Intelligent system actively self-checks biosensor-skin connections to secure better quality health data.

KAUST showcases its smart health technologies at global forum

1 min read ·
Through AI, smart sensors, and computational biology, KAUST is transforming healthcare with practical solutions that address critical health needs in Saudi Arabia and beyond.

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

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B2 B3 A0215

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

TAQADAM Grant from Sabb Bank

1 min read ·
​Prof. Ghanem was awarded a TAQADAM grant from Sabb Bank for a project that focuses on developing AR on wearable devices for the sensory impaired.

Wedyan Babatain

Wedyan Babatain is a doctoral candidate of MMH Labs in the Electrical Engineering program at KAUST. She has an interdisciplinary background obtaining her bachelor's degree in Biomedical Engineering from the University of Delaware, USA, in 2017, and her master's degree in Electrical Engineering from King Abdullah University of Science and Technology (KAUST), KSA, in 2019. Her research interests include sensors, actuators, microfluidics, and flexible and soft electronics for healthcare and environmental applications. She was a finalist at the 2022 SXSW Innovation Awards and has presented her
<> wireless mesh networks (5)

TV and Video Broadcasting Framework for Mobile Networks

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The work on multimedia over wireless mesh networks has inspired us to explore other wireless transmission standards.

M3: Multimedia for Mobile Nodes in a Wireless Mesh Network

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This project committed to address the key problems for supporting multimedia over wireless mesh networks.

Buffer Management in Wireless Mesh Networks

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Wireless mesh networks (WMNs) are a type of ad hoc wireless network that uses multi-hop wireless communications to provide or improve connectivity between wireless devices.

Faisal Nawab

Faisal Nawab graduated with an MS degree in Computer Science from King Abdullah University of Science and Technology (KAUST) in 2011. Nawab currently works as an Assistant Professor of computer science and engineering in the Department of Computer Science and Engineering at the University of California, Santa Cruz, where he works on developing‏ systems for quick and accurate data analysis of new applications in cloud computing and Big Data. Education and Early Career Nawab earned a B.S degree in Computer Science from the KFUPM (King Fahd University of Petroleum and Minerals). He then studied

Ahmad Al-Madani

Visiting Student, Networking Research Lab
Ahmad Al-Madani is a visiting student from the King Fahd University of Petroleum and Minerals (KFUPM), KSA, at the Networking Research Lab, in King Abdullah University of Science and Technology (KAUST), Saudi Arabia.
<> wireless sensors networks (5)

Workshop on Green Electronics at WEP-2012 KAUST

1 min read ·
​Dr. Atif Shamim hosted a workshop titled Miniaturized, Flexible and Green Electronics for Sensing and Communication Systems.

Accepted paper at IEEE Infocom MiSeNet Workshop 2016

1 min read ·
A. Halafi, L. Sboui, R. Naous, and B. Shihada, "Green Task-Based Wireless Sensor Networks", in Proc. IEEE International Conference on Computer Communications (INFOCOM) MiSeNet Workshop, pp. 136-143, 2016.

​Prof. Shamim gave keynote talk at InCAP 2018

1 min read ·
Prof. Atif Shamim was invited as a keynote speaker for Indian Conference on Antennas & Propagation (InCAP) 2018 held in Hyderabad, India.

Professor Atif Shamim named IEEE Antennas and Propagation Society Distinguished Lecturer

2 min read ·
KAUST Associate Professor of Electrical and Computer Engineering Atif Shamim has been selected as a Distinguished Lecturer (DL) for the IEEE Antennas and Propagation Society (AP-S) from 2022 to 2024. In his new role, sponsored by the IEEE, Shamim will give lectures to AP-S chapter members on topics of interest and importance to the global AP community.

Thang Nguyen Quang

Ph.D. Student (former), Electrical and Computer Engineering
Thang Nguyen has recently joined the Sensors group as an Ms/PhD student. Education and early career Thang Nguyen received his BE in Electronics & Communications Engineering (honor program) from HCMUT in 2017. He had served as a research assistant at RFIC Lab, HCMUT for a year before joining KAUST. Research Interests Thang is interested in working in RF energy harvesting and Wireless Sensors Networks. Areas of Expertise and Research Interests RF energy harvesting Wireless Sensor Networks Cognitive Radios Education Profile BE in Electronics & Communications Engineering (honor program), 2017
<> 6G and Beyond (4) <> adaptive linearizing control (4)

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

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 1B

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

Dynamical Modeling, Analysis, Monitoring and Control of Wastewater Treatment Processes - Part 1A

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

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

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

Prof. Denis Dochain, ICTEAM, Université Catholique de Louvain

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KAUST

There are three main classes of wastewater treatment processes (WWTP’s): activated sludge, anaerobic digestion, and lagoon. The course will start to give a short introduction on these three types of WWTP’s. Each topic considered in the course will be illustrated via these three processes.
<> Agricultural Automation (4)

Harnessing the potential for robotics and automation for restoring the worlds coral reefs

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B18 Fellowship Hall

Featured Sessions
Abstract Restoration of Earth's ecosystems has accelerated as a critical management tool in the past decade, particularly for coral reefs where stakeholders have adopted restoration to offset continued declines in reef health. Most coral reef restoration programs remain locally targeted and sub-hectare, where scalability is generated through people networks. Of the few programs that are now beginning to operate at the largest multi-hectare scales - including the KAUST Reefscape Restoration Initiative (KRRI) - implementation of innovative robotics and automation is seen as key to deliver more

Semi-autonomous systems enable advances in Earth Observation

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B18 Fellowship Hall

Featured Sessions
Abstract The description and characterization of the Earth system is a field that routinely leverages technological advances to improve our understanding of diverse ecosystems. One of the most promising areas of application is the use of autonomous and semi-autonomous platforms in precision agriculture. Such systems are capable of performing data collection, analysis, and decision-making tasks with minimal human intervention. The Hydrology, Agriculture, and Land Observation (HALO) laboratory at KAUST is at the forefront of this technology, employing a combination of satellites, UAVs and most

Optimal Design of Agricultural Walking Robot

Prof. Sayat Ibrayev, Institute of Mechanics and Engineering

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B18 Fellowship Hall

Featured Sessions
Abstract Legged machines that can adapt to off-road conditions and irregular terrain, have a number of advantages over traditional wheeled and tracked vehicles. In particular, in agriculture, they cause the least damage to the soil, in comparison with wheeled and tracked vehicles, due to the discrete track on the ground. Meanwhile, attaining to increase productivity of agricultural machines leads to an increase of machine weight that cause increased soil pressure and unfavorable conditions for plant growth. Various designing concepts of legged robots have been proposed by research teams by now

Smart Agricultural Robotics for Monitoring Coral Reefs and Plants: A vertical farming perspective

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B18 Fellowship Hall

Featured Sessions
Abstract Aquaponics is a vertical farming technique and an integrated production of fish and hydroponic crops with recirculation of the aquaculture effluent used by the plant as fertilizer. This technique offers high water efficiency, a faster growth rate, and high crop yields. Despite all the advantages offered by this technology, its implementation on a commercial scale is hindered by many technical and economic factors, which can be addressed by integrating smart technologies, automation, and control. Together with the landmark technologies of Industry 4.0, such as robotics, artificial
<> agriculture (4) <> Analysis of PDE's (4)
Analysis and PDEs Workshop-2025

Workshop on Analysis and PDEs

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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.

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

Myrto Galanopoulou

Short Bio Dr. Myrto Galanopoulou received a B.Sc. and a M.Sc. in Applied Mathematics in 2015 from the University of Crete and a Ph.D. from KAUST in 2020. During her Ph.D. studies she worked on the problem of polyconvex thermoelasticity. In September 2021 she joined the School of Mathematical And Computer Sciences, Heriot-Watt University, as a Research Associate Fellow. Dr. Galanopoulou's research interests lie in the area of analysis of partial differential equations with applications in fields as continuum physics or mechanics. Currently she is working on the mathematical theory of

Aseel AlNajjar

<> applied geometry (4)

Workshop on Applied Geometry and Visual Computing

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B4 L5 R5209

The “KAUST Workshop on Applied Geometry and Visual Computing” brings together leading scientists from Europe and the United States, presenting their latest results in - Applied and Discrete Differential Geometry - Geometry Processing - Computational Fabrication The talks are related to various problems in Applied Mathematics in general and to further areas of Visual Computing such as Computer Graphics, Physical Simulation and Scientific Visualization. The workshop provides a great opportunity to learn about latest developments and to discuss ongoing work with top researchers in the field.

Victor Ceballos Inza

Ph.D. Student, Computer Science
Victor Ceballos Inza is a Ph.D. student under the supervision of Prof. Helmut Pottmann at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST).

Florian Rist

Florian Rist is a Research Scientist at the Visual Computing Center (VCC) working with Professor Helmut Pottmann at KAUST. He is a founding member of the Center for Geometry and Computational Design at TU Vienna and currently holds a double affiliation as a research scientist at the Visual Computer Center at the King Abdullah University of Science and Technology and as a senior scientist at the Institute of Arts and Design at TU Vienna. He studied at TU Munich and the University of Technology Tokyo and is a licensed architect and member of the Chamber of Architects in Bavaria, Germany. Before

Anthony Ramos

Anthony Ramos is an MS/PhD Student at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Helmut Pottman in his research group. Education and Early Career Anthony have obtained Bachelor's degree in Physicist from Yachay Tech University, Urcuqui, Ecuador - government project with the idea of making an international university for the country, from which he was part of the second generation of students. Research Interest Anthony Ramos is passionate about geometry and programming. He loves to bring problems to
<> architecture (4)

A Novel HVDC Architecture for Offshore Wind Farm Applications

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

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KAUST

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

Quantum Computing with Xanadu

Catalina Albornoz, Quantum Community Manager at Xanadu

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KAUST

Xanadu is a Canadian quantum computing company with the mission to build quantum computers that are useful and available to people everywhere. Xanadu is one of the world’s leading quantum hardware and software companies and also leads the development of PennyLane, an open-source software library for quantum computing and application development.

A Best-First Soft/Hard Decision Tree Searching MIMO Decoder for a 4$ times $4 64-QAM System

1 min read ·
Shung An Shen, et al., "A Best-First Soft/Hard Decision Tree Searching MIMO Decoder for a 4$\times $4 64-QAM System." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 20 (8), 2011, 1537. Abstract: This paper presents the algorithm and VLSI architecture of a configurable tree-searching approach that combines the features of classical depth-first and breadth-first methods. Based on this approach, techniques to reduce complexity while providing both hard and soft outputs decoding are presented. Furthermore, a single programmable parameter allows the user to tradeoff throughput

Florian Rist

Florian Rist is a Research Scientist at the Visual Computing Center (VCC) working with Professor Helmut Pottmann at KAUST. He is a founding member of the Center for Geometry and Computational Design at TU Vienna and currently holds a double affiliation as a research scientist at the Visual Computer Center at the King Abdullah University of Science and Technology and as a senior scientist at the Institute of Arts and Design at TU Vienna. He studied at TU Munich and the University of Technology Tokyo and is a licensed architect and member of the Chamber of Architects in Bavaria, Germany. Before
<> Asymptotic Performance Analysis (4)

Asymptotic properties of composites

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B9 L2 R2322 H1

In this talk, I will start with an overview of my research to date. Then, I will address in more detail the study of the asymptotic behavior of a two-dimensional variational model within finite crystal plasticity for high-contrast bilayered composites. More precisely, we consider materials arranged into periodically alternated thin horizontal strips of an elastically rigid component and a softer one with one active slip system. The energies arising from our modeling assumptions are of integral form, featuring linear growth and non-standard differential constraints.

Asymptotic Analysis and Numerical Methods for Compressible Flows at Low Mach Numbers

Prof. Dr. Andreas Meister, Professor, Department of Mathematics and Natural Sciences, University of Kassel

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B1 L4 R4102

We will present a comprehensive study of a finite volume method for inviscid and viscous flow fields at high and low speeds. Thereby, the results of a formal asymptotic low Mach number analysis are used to extend the validity of the numerical method from the simulation of compressible flow fields at transonic as well as supersonic speed to the low Mach number regime.

Rita A. Ferreira

Rita's research activities intersect applied and pure mathematics and are driven by applications to physical and socio-economic sciences and engineering.

Houssem Sifaou

Houssem Sifaou is a Ph.D. candidate in Electrical Engineering, King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Laboratory (CTL). Education and Early Career Houssem Sifaou received the Engineering Degree (Hons.) in Signal and Systems from Tunisia Polytechnic School, La Marsa, Tunisia, in 2014 and the M.S. degree in Electrical Engineering from King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, in 2016. Scientific Interest Houssem Sifaou is interested in Random Matrix Theory
<> asynchronous algorithms (4)

First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data

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B4/5 L0 A0215

This thesis introduces a novel framework for asynchronous first-order stochastic optimization centered on heterogeneous worker speeds that remain fast, stable, and even provably optimal.

First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data

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B9 L2 R2325

This talk will discuss how to design asynchronous optimization methods that remain fast, stable, and even provably optimal.

KAUST Research Workshop on Optimization and Big Data

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B19 L3 H2

The age of "big data" is here: data of unprecedented sizes is becoming ubiquitous, which brings new challenges and new opportunities. With this comes the need to solve optimization problems of unprecedented sizes.

Amani Alonazi

Amani Alonazi is a Visiting Researcher in the Image and Viedo Understanding Lab (IVUL) Research Group working with Professor Bernard Ghanem. Previously, she was a Ph.D. candidate in Computer Science at CEMSE, KAUST, and a member of KAUST's Extreme Computing Research Center, ACM, and SIAM. Areas of expertise and current scientific interests Amani's research focuses on developing novel asynchronous task-based algorithms of solvers in scientific simulations. The core of her work lies within the domain of high-performance computing, which combines performance optimizations, modeling, and
<> Automous Vehicles (4) <> autonomy (4) <> Bayesian Estimation (4)

Graphpcor: Prior for Correlation Matrices

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B9 L2 R2325

This talk introduces a scalable, graph-based framework for modeling correlation matrices that integrate expert-informed priors.

Study finds Red Sea may be cooling rather than warming

1 min read ·
A recent study by a team including KAUST Earth scientists and oceanographers revealed that surface temperatures in the Red Sea may be cooling rather than rising. Analysis of long-term data sets shows that the current high warming rates of the Red Sea appear to be a combined effect of global warming and natural long-duration changes in sea surface temperature. "Our study has revealed a sequence of alternating positive and negative trends in Red Sea surface temperatures. Over the next decades, the trends indicate a cooling phase that may counter the effects of global warming," stated Ibrahim

Red Sea temperatures to cool in coming decades

1 min read ·
Exploring the links between natural climate cycles and the sea-surface temperature of the Red Sea reveals a cooling trend during the next few decades.

New preprint available from research on quasi-Newton methods for stochastic optimization

1 min read ·
A preprint of a new research project of our group named " Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization" is available at arXiv. The manuscript is authored by André Carlon, Prof. Luis Espath, and Prof. Raúl Tempone. Abstract: Using quasi-Newton methods in stochastic optimization is not a trivial task. In deterministic optimization, these methods are often a common choice due to their excellent performance regardless of the problem's condition number. However, standard quasi-Newton methods fail to extract curvature
<> big data analytics (4)

How data is transforming transplantation in Saudi Arabia

3 min read ·
Every organ transplant is a race against time. The outcome often hinges on finding a biologically compatible donor at the right time. Success depends on a complex combination of factors: organ quality, timing, patient readiness, logistics, clinical practices and long-term risks. Transplantation medicine relies on care coordination among multidisciplinary providers across institutions and on long-term patient monitoring. Improving data systems plays a crucial role in assessing key performance indicators, ensuring timely transplants and determining which patients benefit most from the organ

KAUST Research Conference Digital Health 2020

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B19 L2 H1

Computational Bioscience Research Center at King Abdullah University of Science and Technology is pleased to announce the KAUST Research Conference on Digital Health 2020.

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.

Muhamad Felemban

Muhamad Felemban obtained his Master's degree in Computer Science under the supervision of Professor Basem Shihada at King Abdullah University of Science and Technology (KAUST) in 2011. Muhamad received a B.S. degree from King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, in 2008, and a Ph.D. degree from the School of Electrical and Computer Engineering, Purdue University, in 2018. Currently, he is an Assistant Professor in the Computer Engineering department at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. Master's Thesis title: " Optimal Node
<> biomedical electronics (4)

BioChips: Leveraging Integrated Electronics for Sensing, Medicine, and Science

Pamela Abshire, Professor, Department of Electrical and Computer Engineering and Institute for Systems Research at the University of Maryland, College Park

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B9 L2 R2322

This talk will provide a brief overview of LoCMOS systems, the technologies used to construct them, and their application to novel applications in biosensing, medical diagnostics, and neuroscience. The integration of integrated circuits into LoCMOS devices poses a number of distinct and vexing challenges, increasing complexity while reducing the need for external instrumentation.

Heba Almorad

Visiting student in the Communication Theory Lab (CTL) and the Information System Lab (ISL), at King Abdullah University of Science and Technology,

Esraa Fakeih

Aeron Jones

Aeron Jones is a PhD student in the Electrical Engineering department at Integrated Microwaves Packaging Antennas & Circuit Technology (IMPACT) Research Group under the supervision of Professor Atif Shamim at King Abdullah University of Science and Technology (KAUST). Education MScRes Electronic Engineering from Bangor University BEng Electronic Engineering from Bangor University Research Interests Microwave Sensors in the Oil industry and Use of Microwaves for biomedical applications Selected Publications A. Jones, S. Preston, M. White and C. Hancock, "A Prototype System for Optical
<> black-box optimization (4)

Learning under Limited Information across Federated, Multi-Agent, and LLM Settings

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B3 R5220

This dissertation studies learning under structural information constraints across three major paradigms: federated learning, cooperative multi-agent reinforcement learning, and black-box optimization of large language models.

Reinforcement Learning and Optimization in Large Action Spaces under Limited Feedback

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B2 R5209

This dissertation develops theoretical foundations and scalable algorithms for reinforcement learning and optimization in large decision spaces under limited feedback.

Salma Kharrat

Ph.D. Student, Computer Science

Fares Fourati

Fares Fourati is a Ph.D. student at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini.
<> channel estimation (4) <> chaos (4)

Implementation and Statistical Characterization of High Efficiency True Random Number Generators (RNGs) for Cryptographic Applications

Practical implementations of RNGs can be classified into two major categories, namely pseudo-RNGs and physical-RNGs. Pseudo-RNGs are deterministic, numeric algorithms that expand short seeds into long bit sequences. Conversely, physical-RNGs rely on microscopic processes resulting in macroscopic observables which can be regarded as random noise (quantum, thermal,…). Pseudo-RNGs generally depart more from the ideal specifications: are based on finite memory algorithms, thus exhibit periodic behaviors and generate correlated samples and are therefore unsuitable for data security and cryptography

Generalized Hardware Post Processing Technique for Chaos-Based Pseudorandom Number Generators

1 min read ·
Mohamed L. Barakat, et al., "Generalized Hardware Post Processing Technique for Chaos-Based Pseudorandom Number Generators" ETRI Journal, 35, (3), 2013, 448. Abstract: This paper presents a generalized post‐processing technique for enhancing the pseudorandomness of digital chaotic oscillators through a nonlinear XOR‐based operation with rotation and feedback. The technique allows full utilization of the chaotic output as pseudorandom number generators and improves throughput without a significant area penalty. Digital design of a third‐order chaotic system with maximum function nonlinearity is

Fully digital jerk-based chaotic oscillators for high throughput pseudo-random number generators up to 8.77 Gbitss

1 min read ·
Abhinav S. Mansingka, et al., "Fully digital jerk-based chaotic oscillators for high throughput pseudo-random number generators up to 8.77 Gbitss" Microelectronics Journal 44, (9), 2013, 744. Abstract: This paper introduces fully digital implementations of four different systems in the 3rd order jerk-equation based chaotic family using the Euler approximation. The digitization approach enables controllable chaotic systems that reliably provide sinusoidal or chaotic output based on a selection input. New systems are introduced, derived using logical and arithmetic operations between two system

Robust fractional-order proportional-integral observer for synchronization of chaotic fractional-order systems

1 min read ·
Ibrahima N' Doye, et al., "Robust fractional-order proportional-integral observer for synchronization of chaotic fractional-order systems", IEEE/CAA Journal of Automatica Sinica 6 (1), 2019, 268. Abstract: In this paper, we propose a robust fractional-order proportional-integral (FOPI) observer for the synchronization of nonlinear fractional-order chaotic systems. The convergence of the observer is proved, and sufficient conditions are derived in terms of linear matrix inequalities (LMIs) approach by using an indirect Lyapunov method. The proposed FOPI observer is robust against Lipschitz
<> chaotic systems (4)

Mohammed Zidan (EE PhD Candidate) received the best postgraduate poster award at the SIECPS conference

1 min read ·
Mohammed Zidan received the best postgraduate poster award at the second Saudi International Electronics, Communications and Photonics conference, held 27-30 April 2013 in Riyadh, KSA.

Prof. Salama's publications recognized by Elsevier's Top 25 hottest articles list

1 min read ·
Ph.D. student, Mohammed Zidan 's paper on Memristor-based memory: The sneak paths problem and solutions are recognized by ScienceDirect as one of the Top 25 hottest papers.

Mohammed Zidan awarded IEEE Circuits and Systems Society Pre-Doctoral Fellowship

1 min read ·
Mohammed Affan Zidan, sensors lab member and Ph.D. candidate in the Electrical Engineering (EE) Program at the Computer, Electrical, and Mathematical Science and Engineering (CEMSE) Division, received the IEEE Circuits and Systems (CAS) Society Pre-Doctoral Fellowship.

Mohammed Affan Zidan

Mohammed Affan Zidan obtained his Ph.D. Degree in the Electrical Engineering (EE) Program from King Abdullah University of Science and Technology, under the supervision of Prof. Khaled Nabil Salama. Mohammed Zidan earned his M.Sc. in Electronics and Communications Engineering from Faculty of Engineering, Cairo University, Egypt in 2010, where he was ranked first. In 2006, he received his B.Sc. in Electronics and Communications Engineering, Institute of Aviation Engineering and Technology (IAET), Egypt, also ranking first. Before joining KAUST, he worked as a teaching assistant at the German
<> climate data (4)

Resilient renewable energy networks designed for the desert

1 min read ·
Accounting for weather extremes is essential for designing reliable renewable energy systems in hot, arid regions.

Towards an Early Warning System for Climate-Sensitive Infectious Diseases: Spatio-Temporal Modeling and Deep Learning for Dengue Forecasting in Brazil

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B5 R5209

This dissertation develops integrated spatio-temporal forecasting approaches that combine deep learning, climate data, spatial dependencies, and human mobility to improve dengue prediction and support early-warning systems in Brazil.

KAUST climate research named finalist for ADIA Lab Climate Data Sciences Award

3 min read ·
KAUST team develops breakthrough method for wind data generation, earning finalist spot for ADIA Lab’s climate science award.

Statistical models for long-range dependent climate data

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B9 L2 R2322

In this talk I will discuss statistical models which incorporate temperature response to the radiative forcing components. The models can be used to estimate important climate sensitivity measures and give temperature forecasts. Bayesian inference is obtained using the methodology of integrated nested Laplace approximation and Monte Carlo simulations. The resulting approach will be demonstrated in analyzing instrumental data and Earth system model ensembles.
<> complex models (4)

Reproducibility in Computer Science - Part 1

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B9 L3 R3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Reproducibility in Computer Science - Part 2

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B9 L3 R3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Reproducibility in Computer Science - Part 3

-

B9 L3 R3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Extraction of Complex DNN Models: Real Threat or Boogeyman? - Graduate Seminar

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B9 L2 H2 H2

The success of deep learning in many application domains has been nothing short of dramatic. The success has brought the spotlight onto security and privacy concerns with deep learning. One of them is the threat of "model extraction": when a machine learning model is made available to customers via an inference interface, a malicious customer can use repeated queries to this interface and use the information gained to construct a surrogate model. In this talk, I will describe our work in exploring whether model extraction constitutes a realistic threat. I will also discuss possible countermeasures, focussing on deterrence mechanisms that allow for the verification of ownership of ML models.
<> computational science and engineering (4)

ECRC contributions to SIAM CSE21

4 min read ·
ECRC @ SIAM CSE21! Follow us @KAUST_ECRC As in previous SIAM conferences on Parallel Processing (PP) and Computational Science and Engineering (CSE), ECRC members and their collaborators will have a strong presence at SIAM CSE21, nominally in Fort Worth, Texas, but held virtually due to the pandemic. ************************************************** SIAM CSE21 will run virtually with live sessions. ************************************************** Registration to SIAM CSE is required to gain access to the online platform and attend live sessions. Once registered, please use your personal

The Arab World Prepares the Exascale Workforce

1 min read ·
The April 2021 Communications of the ACM special section on computing in the Arab world features an article by ECRC Director and KAUST founding dean David Keyes on preparing the exascale workforce. Keyes muses on the lure of hands-on opportunities to resolve today’s application-architecture tension with innovative algorithms for recruiting students, and he follows the placement of a dozen recent ECRC doctoral students from the MENA region in the US exascale computing project and Saudi industry. For them, “graduation” means an upgrade to a more powerful computer :-). Several have also seen

Stefano Zampini

As a computational mathematician and software engineer, Stefano Zampini's work lies at the intersection of numerical analysis, predictive simulations, and high-performance computing, with recent forays into machine learning.

David Keyes

David Keyes works at the interface of computational science and engineering and high performance computing, which he helped edit into the DNA of KAUST as a founding Dean in 2009 and then as director of the Extreme Computing Research Center. He currently serves as Senior Associate to the President, Chair of the KAUST RDIA Economies of the Future committee, and delegate to the Saudi Center for the Fourth Industrial Revolution.
<> computational simulations (4)

Reduced-Order High Fidelity Simulations of Reacting Flows Using Low Dimensional Manifolds and Machine Learning

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B1 R3119

This talk will provide an overview of historical developments in mathematical and computational approaches to reduced order models for accelerated high fidelity reacting flow simulations in modern computing hardware.

Jonathan Klein

Research Scientist, Computer Science
My fields of research interests include computational simulation, plant simulation and modeling, synthetic training data, machine learning architectures, none-line-of-sight imaging, and computational photography.
ACM Gordon Bell Prize for Climate Modelling

KAUST wins the “Nobel” of high-performance computing for climate modeling

1 min read ·
KAUST has been awarded the “Nobel" prize of high-performance computing—the ACM Gordon Bell Prize for Climate Modelling—in partnership with the NSF National Center for Atmospheric Research, U.S. and other partner institutions.

Mani Sarathy

Professor Sarathy's research interest is in developing sustainable energy technologies with decreased net environmental impact. A major thrust of research is improving the operation of power generation technologies. The goal of Professor Sarathy's research is study conventional and alternative fuels (e.g., biofuels, synthetic fuels, etc.), so the environmental impact of combustion systems can be reduced. He applies AI and ML techniques to study complex energy related problems such as fuel design, renewable hydrogen production, and process control and optimization in energy intensive operations.
<> Computer Vision for Automation (4)

The future of coral reef monitoring

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B18 Fellowship Hall

Featured Sessions
Abstract Saudi Arabia is undertaking an unprecedented development along its Red Sea coast, including launching multiple "GigaProjects", with ambitions to be a major ecotourism destination. At the same time, the country has committed to the highest levels of protection for the natural environment and 'regenerative tourism' approaches that will improve the quality of the targeted habitats. Of particular focus are the Kingdom's numerous coral reefs, renowned for their biodiversity. Traditional approaches for monitoring the health of coral reefs are difficult to scale up sufficiently to meet the

KAUST Reefscape Restoration Initiative

Dr. Maram Abadi, KAUST Reefscape Restoration Initiative, King Abdullah University of Science and Technology (KAUST)

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B18 Fellowship Hall

Featured Sessions
Abstract KAUST Reefscape Restoration Initiative is the world's largest coral reef restoration initiative. The initiative will begin with a 100-hectare reef restoration project at Shushah Island in the Red Sea. This will be a global demonstration of coral restoration that integrates innovative, in-Saudi Arabia, and internationally developed technologies, pioneering propagation, planting, and monitoring approaches, and international expertise to accelerate solutions for reef ecosystems at a time of unprecedented environmental change. The effort will be a mix of coral conservation protection

Smart Agricultural Robotics for Monitoring Coral Reefs and Plants: A vertical farming perspective

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B18 Fellowship Hall

Featured Sessions
Abstract Aquaponics is a vertical farming technique and an integrated production of fish and hydroponic crops with recirculation of the aquaculture effluent used by the plant as fertilizer. This technique offers high water efficiency, a faster growth rate, and high crop yields. Despite all the advantages offered by this technology, its implementation on a commercial scale is hindered by many technical and economic factors, which can be addressed by integrating smart technologies, automation, and control. Together with the landmark technologies of Industry 4.0, such as robotics, artificial

José Maria Sosa Gómez

PhD student at KAUST leveraging machine learning and radar systems to enhance patient procedures, under the guidance of Prof. Mohamed-Slim Alouini at the Communication Theory Lab (CTL).
<> Continual Learning (4)

Andres Villa

Postdoctoral Research Fellow
Andres Villa is a Postdoctoral Fellow in the IVUL lab at King Abdullah University of Science and Technology (KAUST), focusing on AI for Science, Continual Learning, Visual Language Models, and Action Understanding.

Yasir Ghunaim

Yasir is a Computer Science Ph.D. student in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem.

Habib Slim

Ph.D. Student, Computer Science
Habib Slim is a Computer Science Ph.D. candidate at the Visual Computing Center (VCC)/Vison-CAIR at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Mohamed Elhoseiny Education: M.Sc Data Science, Grenoble Institute of Technology, France, 2021 M.Eng Applied Mathematics and Computer Science, Grenoble Institute of Technology, France, 2021

Deyao Zhu

Ph.D. Student, Computer Science
Deyao Zhu is a Computer Science Ph.D. student at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Mohamed Elhoseiny in the Vision-CAIR Group. Education and Early Career Deyao obtained his Master's degree in Electrical Engineering and Information Technology at Gottfried Wilhelm Leibniz Universität Hannover, Germany. His Master thesis is done in Max Planck Institute for Intelligent Systems which focuses on representation learning. Before that, he received his Bachelor’s degree in Mechatronics at Tongji University
<> Cross-layer protocol design (4)

Wireless Multihop Networks: Finding the Best Way Home

4 min read ·
In contrast to conventional cellular networks, devices in wireless multihop networks have dual roles: while each device is a source of information it also acts as a router for its peers.

Post-Doctoral Fellow Ahmed Bader bestowed YPs Best Innovation Award at IEEE WCNC 2017

1 min read ·
Dr. Ahmed Bader, a CEMSE Post-Doctoral Fellow in electrical engineering, won the IEEE Communications Society (ComSoc) Young Professionals (YPs) Best Innovation Award at Wireless Communications and Networking Conference 2017, in San Francisco, USA, on March 22.

Teamwork pays off at startup Insyab

2 min read ·
Insyab, a technology startup specializing in smart solutions allowing robots and drones to collaborate on the execution of common tasks, resulted from three years of its founders' dedicated research at KAUST.

Ahmed Bader

Research Scientist, Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). Managing Director in Insyab Wireless Limited, Dubai, United Arab Emirates.
<> cyber-physical energy systems (4)

Load-Altering Attacks Against Power Grids under Low-Inertia Conditions

1 min read ·
Load-Altering Attacks Against Power Grids under COVID-19 Low-Inertia Conditions: The COVID-19 pandemic has impacted our society by forcing shutdowns and shifting the way people interacted worldwide. In relation to the impacts on the electric grid, it created a significant decrease in energy demands across the globe. Recent studies have shown that the low demand conditions caused by COVID-19 lockdowns combined with large renewable generation have resulted in extremely low-inertia grid conditions. In our work, in collaboration with Subhash Lakshminarayana, University of Warwick, UK, and Juan

Mitigation of Cyberattacks through Battery Storage for Stable Microgrid Operation

1 min read ·
Mitigation of Cyberattacks through Battery Storage for Stable Microgrid Operation: Power grids are undergoing radical changes to meet energy demands, comply with environmental regulations, and improve the quality of service and system resilience. The inclusion of information and communication technologies and embedded devices enables the remote coordination, and control of microgrids (MG) and has transformed traditional power systems into cyber-physical systems. The security of MG-enabled power systems should not be overlooked given the plethora of cyberattacks against this pillar of critical

An Effective Security Scheme for Attacks on Sample Value Messages in IEC 61850 Automated Substations

1 min read ·
The trend of transforming substations into smart automated facilities has led to their swift digitalization and automation. To facilitate data exchange among equipment within these substations, the IEC 61850 standard has become the predominant standard. However, this standardization has inadvertently made these substations more susceptible to cyberattacks, which is a significant concern given the confidential information that is transmitted. As a result, cybersecurity in substations is becoming an increasingly critical topic. IEC 62351 standard provides guidelines and considerations for

Distributed Energy Resources Cybersecurity Outlook: Vulnerabilities, Attacks, Impacts, and Mitigations

1 min read ·
The digitization and decentralization of the electric power grid represent crucial steps toward achieving both economic and environmental sustainability. In pursuit of this objective, distributed energy resources (DERs), such as rooftop solar panels, battery storage systems, and electric vehicles, are increasingly integrated into power systems. These DERs offer several advantages to power utilities by reducing operational costs and deferring investments for the expansion of the power system network while also affording users and aggregators greater control over their electricity generation and
<> data (4) <> Data Privacy (4)

Private and Robust Learning for Decision Making

-
This thesis develops the theoretical foundations of decision-making under privacy, heavy-tailed feedback, and data contamination, establishing fundamental limits and designing near-optimal algorithms across bandits, reinforcement learning, and RLHF.

Provable and Measurable Machine Unlearning in Modern Learning Systems

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B2 L5 R5209

This dissertation examines the foundations of machine unlearning under realistic learning system constraints and proposes both theoretically grounded unlearning algorithms and principled evaluation frameworks for modern learning systems.

CybeResil Research Opportunities

Broad Research Topics Robust and Adaptive Fault and Intrusion Tolerance; Ultra-Reliable Micro Trusted Execution Environments; Privacy and Integrity-preserving Data Processing; Next-generation Threat and Intrusion Detection / Prevention Systems; High-confidence Vertical Software Verification. Focused PhD-level Research Opportunities Fault and Intrusion Resilience Systems for Modern Vehicles Modern software-defined vehicles are prone to software faults and intrusions. A modern vehicle is composed of up to hundred commuting units, called Electronic Control Units (ECUs), connected via different

Cheng-Long Wang

Ph.D. Student, Computer Science
Cheng-Long Wang is a PhD candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), advised by Prof. Di Wang.
<> decentralized systems (4)

Learning under Limited Information across Federated, Multi-Agent, and LLM Settings

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B3 R5220

This dissertation studies learning under structural information constraints across three major paradigms: federated learning, cooperative multi-agent reinforcement learning, and black-box optimization of large language models.

Fully Decentralized Inference for Spatial Data Using Low-Rank Models

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B9 R2325

This talk introduces a novel, fully decentralized optimization framework to enable scalable parameter inference in large spatial low-rank models, supported by both theoretical guarantees and empirical validation.

Jianwei Shi

Postdoctoral Research Fellow, Statistics

Salma Kharrat

Ph.D. Student, Computer Science
<> diffusive phenomena (4)

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 named Fellow of the Institute of Mathematics and its Applications

1 min read ·
Prof. Peter Markowich has been named a Fellow of the Institute of Mathematics and its Applications (IMA). IMA Fellowships are awarded to individuals who have shown demonstrable achievement and competence in the development or application of 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.
<> digital health (4)

Resilient Computing: when Dependability meets Cybersecurity

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B9 L2 H2 R2325

Computing and communications infrastructures have become commodities that transact huge quantities of data and are pervasively interconnected, inside countries, and worldwide. Modern societies largely depend on them.

KAUST Research Conference Digital Health 2020

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B19 L2 H1

Computational Bioscience Research Center at King Abdullah University of Science and Technology is pleased to announce the KAUST Research Conference on Digital Health 2020.

KAUST-MBSC Invitational Healthcare Analytics and Data Science Workshop

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B3 L5 R5220

The amount of collected medical data and computational power are growing rapidly, which creates new opportunities to impact and improve healthcare by advanced analytics and data science. We aim to bring together practitioners and researchers from across the Kingdom to exchange knowledge and explore possible collaborations. To register, please, fill form here.

Exciting News from LEAP2024!

1 min read ·
Exciting News from LEAP2024! We are thrilled to announce that our two innovative startup companies, Qawam and MOBiSENSE, participated in LEAP2024, showcasing their cutting-edge products and services. Qawam, known for its groundbreaking posture correction solutions, has now developed an app that utilizes sensors from Apple Airpods. This app eliminates the need for a separate clip-on device, providing consumers with a more convenient and seamless posture correction experience. MOBiSENSE specializes in extracting valuable insights for mobile network operators (MNOs) and communications services
<> Distributed Robot Systems (4)

Early Versus Late Traffic Management for Autonomous Agents

-
This dissertation investigates how the timing of centralized traffic management affects the performance of autonomous agents in autonomous vehicle and robotic fleets.

The future of coral reef monitoring

-

B18 Fellowship Hall

Featured Sessions
Abstract Saudi Arabia is undertaking an unprecedented development along its Red Sea coast, including launching multiple "GigaProjects", with ambitions to be a major ecotourism destination. At the same time, the country has committed to the highest levels of protection for the natural environment and 'regenerative tourism' approaches that will improve the quality of the targeted habitats. Of particular focus are the Kingdom's numerous coral reefs, renowned for their biodiversity. Traditional approaches for monitoring the health of coral reefs are difficult to scale up sufficiently to meet the

Frontiers in Marine Research Robotics

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B18 Fellowship Hall

Featured Sessions
Abstract Marine robotics have evolved substantially since the early days of autonomous underwater vehicles which meant a multimillion-dollar vehicle always accompanied by a surface vehicle. An early step forward in scientific vehicles was the development of the buoyancy-driven autonomous underwater vehicles which could stay at sea for months and traverse large distances and depths down to 1000m, albeit slowly. Critical needs exist for vehicles that can map, image and characterize the sea bottom, and for intelligent fleet management schemes. The mesophotic (below diver accessible depths) and

Estimation and control of underwater optical wireless communication systems

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B18 Fellowship Hall

Featured Sessions
Abstract Underwater optical wireless communication (UOWC) technologies are essential for the growth of future underwater communication applications. As the demand for capacity increases, UOWC is considered an emerging alternative technology in the underwater communication area. However, maintaining a controlled line-of-sight link between transmitter and receiver is a significant challenge because the alignment angle required for trajectory tracking control is not directly measured and has to be estimated. In this talk, I will present our recent works on estimating the alignment angle between
<> Dynamic programming (4)

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

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KAUST

Dynamic programming is an efficient technique to solve optimization problems. It is based on decomposing the initial problem into simpler ones and solving these sub-problems beginning from the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. We developed extensions of dynamic programming which allow us (i) to describe the set of objects under consideration, (ii) to perform a multi-stage optimization of objects relative to different criteria, (iii) to count the number of optimal objects,(iv) to find the set of Pareto optimal points for the bi-criteria optimization problem, and (v) to study the relationships between two criteria.

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining - 2022-10-04

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B9 L2 R2322

Dynamic programming is an efficient technique to solve optimization problems. It is based on decomposing the initial problem into simpler ones and solving these sub-problems beginning from the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects.

Ph.D. Student’s Research Listed in The American Journal of Transplantation’s “Top 10 Articles of 2019”

2 min read ·
Research work carried out by Michał Mańkowski, a Ph.D. student in the KAUST Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, was recently selected for inclusion by the editors of The American Journal of Transplantation (AJT) in their “Top 10 Articles of 2019.

Michal A. Mankowski

<> Efficient AI (4) <> Electroencephalograms (4)

Omar Ahmed

M.S. Student, Bioengineering
Omar Ahmed is an MS student in the Bioengineering department at KAUST. His research explores the mechanisms that enable brain signal generalisability across individuals, addressing how neural activity patterns can be reliably interpreted despite significant inter-subject and temporal variability. A major challenge in neuroscience is that brain activity varies substantially between people and even within the same person over time, which limits the development of universal diagnostic and therapeutic tools. Towards this goal, Omar is developing deep learning models that can identify consistent
KAUST-CEMSE-CS-VISION-CAIR-Dalal-Aldossary

Dalal E. Aldossary

M.S. Student, Computer Science
Dalal Aldossary is a Master’s student in Computer Science at KAUST. She is part of the VISION-CAIR and the Neuroscience & AI Lab (NAIL), where she works on developing machine learning models that interpret and learn EEG representations and behavior.

Hernando Ombao

Professor, Statistics
KAUST Professor of Statistics Hernando Ombao is an expert in time series models and their applications to designed medical experiments on complex biological processes.
Portrait picture, smiling, blue Abaya, blue-brown gradient Hijab, and brown background with metal beems

Farah Abdulrazak Gomawi

Ph.D. Student, Statistics
Farah Abdulrazak Gomawi is a Ph. D. student in Statistics at the King Abdullah University of Science and Technology (KAUST) under the supervision of Prof. Hernando Ombao. Education and Early Career Farah Abdulrazak Gomawi received her Bachelor of Science in Applied Mathematics from the University of California, Los Angeles (UCLA) in the United States, with the KAUST Gifted Student Program (KGSP) scholarship in 2023. Prior to this, she was a visiting student in the Biostatistics group in the summer of 2022. Research Interest Farah's research interests include time series analysis, machine
<> electromagnetic (4)

KAUST scientists use new mathematical approach to protect aircraft from 5G interference

1 min read ·
Study offers first application of stochastic geometry for the safe deployment of 5G towers around runways

Exploring the Potentials of EM Waves from Body-scale to Nano-communications for Healthcare and Next Generation Wireless Applications

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

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KAUST

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

Efficient and Accurate Numerical Methods for Transient Electromagnetic Analysis - 2020

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KAUST

Electromagnetic devices and systems are at the heart of technological advances revolutionizing many fields of science and engineering including energy management, biomedical electronics, communications and computing, and even environmental monitoring and civil design. Many of these systems are electrically large, their frequency of operation has a wide dynamic range, their device components are geometrically intricate with dimensions varying by orders of magnitude, and finally their optimal design requires many repetitions of characterizations with different parameters.

A Compact, Passive Frequency-Hopping Harmonic Sensor Based on a Microfluidic Reconfigurable Dual-Band Antenna

1 min read ·
Liang Zhu, et al., "A Compact, Passive Frequency-Hopping Harmonic Sensor Based on a Microfluidic Reconfigurable Dual-Band Antenna," IEEE Sensors Journal, 2020, 1. We propose here a fully-passive wireless liquid sensor using a harmonic transponder, which comprises a dual-band microstrip antenna reconfigured by different types of liquids injected in a fluidic cavity. Different from traditional radio-frequency (RF) backscatter sensors, the proposed harmonic-transponder sensor (or harmonic sensor) receives frequency-hopped RF monotones and backscatters their second harmonics, with the peak
<> electromagnetic waves (4) <> Energy-efficient wireless multihop networks (4)

Wireless Multihop Networks: Finding the Best Way Home

4 min read ·
In contrast to conventional cellular networks, devices in wireless multihop networks have dual roles: while each device is a source of information it also acts as a router for its peers.

Post-Doctoral Fellow Ahmed Bader bestowed YPs Best Innovation Award at IEEE WCNC 2017

1 min read ·
Dr. Ahmed Bader, a CEMSE Post-Doctoral Fellow in electrical engineering, won the IEEE Communications Society (ComSoc) Young Professionals (YPs) Best Innovation Award at Wireless Communications and Networking Conference 2017, in San Francisco, USA, on March 22.

Teamwork pays off at startup Insyab

2 min read ·
Insyab, a technology startup specializing in smart solutions allowing robots and drones to collaborate on the execution of common tasks, resulted from three years of its founders' dedicated research at KAUST.

Ahmed Bader

Research Scientist, Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). Managing Director in Insyab Wireless Limited, Dubai, United Arab Emirates.
<> explainable AI (4)

Causal Reasoning in Medical Digital Twins: Methods and Architectures

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B3 R5209

This dissertation develops a principled computational framework for causal reasoning in Medical digital twins (MDT) systems, moving beyond correlation-driven approaches toward explainable and biologically grounded decision support.

Towards an Early Warning System for Climate-Sensitive Infectious Diseases: Spatio-Temporal Modeling and Deep Learning for Dengue Forecasting in Brazil

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B5 R5209

This dissertation develops integrated spatio-temporal forecasting approaches that combine deep learning, climate data, spatial dependencies, and human mobility to improve dengue prediction and support early-warning systems in Brazil.
KAUST-CEMSE-AMCS-PhD-Dissertation-Defense-Lijie-Hu-Towards-Usable-and-Useful-Explainable-A

Towards Usable and Useful Explainable AI

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This talk presents advancements in Explainable AI, spanning from classical deep learning to large language models, with contributions that enhance both the usability and usefulness of interpretability methods to improve trust, performance, and safety in AI systems.

Xiang Chen

Ph.D. Student, Statistics
Xiang Chen's research focuses on spatio-temporal modeling of climate-sensitive infectious diseases, integrating large-scale health, climate, and human mobility data to improve epidemiological forecasting and support public health decision-making.
<> extreme events (4)

Statistical Modeling of Financial Extremes and Volatility Dynamics

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B2 R5220

This thesis provides comprehensive statistical tools for understanding and modeling extreme risks and volatility dynamics in financial markets.

Understanding Extreme Market Behavior: The Efficient Tail Hypothesis

2 min read ·
A new study by researchers Junshu Jiang, James Richards, Raphaël Huser, and David Bolin introduces the Efficient Tail Hypothesis (ETH), an analogue of the Efficient Market Hypothesis focused on extreme events in financial markets. Drawing on extreme value theory, the team developed a novel statistical measure to evaluate whether asset markets remain informationally efficient even during rare, extreme fluctuations. Their findings not only challenge conventional wisdom on market efficiency but also open the door to identifying potential opportunities (and risks) that emerge during market

A sharper view of flood risk

1 min read ·
Extreme weather patterns and regions at risk of flooding could be easier to spot using a new statistical model for large spatial datasets.

Junshu Jiang

Ph.D. Student, Statistics
<> FD-MIMO (4)

Prof. Alouini selected as an IEEE Communications Society Distinguished Lecturer for 2016 and 2017

1 min read ·
Congratulations to Prof. Alouini for being selected to give a Distinguished Lecture for 2016 and 2017 in IEEE Communications Society

Marie Sklodowska-Curie Fellowships in Photonics @ CEMSE – call 4 - 2018

1 min read ·
A group of professors working in the area of photonics at KAUST, most of them with CEMSE Division, offer hosting of outgoing Marie Sklodowska-Curie Fellowships in their research groups within the EU H2020 COFUND Postdoctoral Fellowship Programme MULTIPLY.

Paving the way towards 5G wireless communication networks

1 min read ·
KAUST Ph.D. student Qurrat-Ul-Ain Nadeem received a 2018 Marconi Society Paul Baran Young Scholar Award for her work in full-dimension (FD) massive multiple input multiple output (MIMO) transmission technology.

Mohamed-Slim Alouini

Al-Khawarzmi Distinguished Professor, Electrical and Computer Engineering
KAUST is a fertile place for any researcher who wants to develop rigorous computational and engineering methods to solve real-world problems. Its unique support of science allows the most advanced scientific revolution.