Topics

<> precision medicine (3) <> protein function prediction (3) <> protein structures (3)

The awesome scope of big data

1 min read ·
Sifting through huge amounts of data may bring a better understanding of whale shark social structures, protein targets for drug therapies and disease-causing genes.

Islam Almasri

Islam Almasri obtained his Master's degree in Computer Science under the supervision of Professor Xin Gao at Structural and Functional Bioinformatics Group (SFB) at King Abdullah University of Science and Technology (KAUST). Currently, Islam is a Ph.D. candidate in the Computer Science program under the supervision of Prof. Nina Fedoroff. at Fedoroff Research Group. Islam is specialized in developing various software tools for solving problems in other scientific domains, including Image Processing, Medical Imaging, Chemical Networks, and Protein Structure. Selected Publications Almasri, Islam

Gian Marco Messa

Ph.D. Student, Computer Science
Gian Marco is a Ph.D. student at the Structural and Functional Bioinformatics Group (SFB) under the supervision of Professor Xin Gao at King Abdullah University of Science and Technology (KAUST). Gian Marco, upon finishing high school in Lecce (Italy), applied to the Politecnico of Milan in the year 2009 in Physics engineering. Due to personal issues, he came back to his hometown to complete the Bachelor's Degree at the University of Salento in Biotechnology. For his master's degree, seeking innovation and cutting edge knowledge, he moved to the University of Bologna, which offered an M. Sc
<> prototyping (3)
H

Hussein Al-Shatri

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

KAUST student wins global sensors and measurement systems competition

1 min read ·
KAUST master's degree student José Ilton de Oliveira Filho recently won first place at the second edition of the IEEE International Sensors and Measurement Systems Student Contest (IEEE IS&M-SC). IEEE IS&M-SC is a global competition directed at teams of advanced undergraduates, master's degree and Ph.D. students and seeks to stimulate creative ideas for sensor and measuring systems applications.

Jose Ilton De Oliveira Filho

Postdoctoral Research Fellow, Electrical and Computer Engineering
José Ilton is currently a Postdoctoral Fellow in the Electrical and Computer Engineering program, at King Abdullah University of Science and Technology (KAUST). José is focused on instrumentation, prototyping, and communication theory. Education and Early Career José Ilton did his bachelor’s in electrical engineering on the track of Power Systems at Federal University of Piaui with 1.5-year exchange period at Budapest University of Technology and Economics, in 2015. At King Abdullah University of Science and Technology (KAUST) he did his master’s in electrical engineering on the topic of
<> Queueing theory (3)

Hesham ElSawy gains ISWCS Best Scientific Contribution Award 2017

1 min read ·
The imminent era of the smart world is foreseen to involve massively many power and computationally constraint wireless devices with sporadic traffic patterns. The surging Internet of things (IoT) and cyber physical systems (CPS) are clear examples that rely on massive wireless networks. Hence, realizing such extensive wireless connectivity is mandatory to unlock the potentials and reap the benefits of the foreseen smart era.

Li Xia

Postdoctoral Research Fellow, Networking Research Lab
Li Xia was a Postdoctoral Research Fellow at Networking Research Lab (NETLAB) in King Abdullah University of Science and Technology (KAUST), working with Professor Basem Shihada in his research group. Currently, Li is an Associate Professor at Tsinghua University, China. Research Interests Li's research interests included Operations research, stochastic optimization, queueing theory, Markov decision processes. Selected Publications L. Xia and B. Shihada, "Decentralized Transmission Scheduling in Energy-Critical Multi-Hop Wireless Networks", in Proc. American Control Conference, pp. 113-118

Hesham ElSawy

Postdoctoral Research Fellow, Communication Theory Lab
From April 2014 to June 2018 Hesham ElSawy was a postdoctoral fellow in the Communication Theory Lab (CTL), at the Computer, Electrical, and Mathematical Sciences and Engineering division (CEMSE), King Abdullah University for Science and Technology (KAUST), Kingdom of Saudi Arabia. He is now an assistant professor in King Fahd University of Petroleum and Minerals (KFUPM), Eastern Province, KSA Selected Publications Ph.D. Thesis H. ElSawy, “Modeling, Analysis, and Optimization of Random Wireless Networks: Stochastic Geometry Approach,” University of Manitoba, Winnipeg, MB, Canada, March 2014. M
<> radio frequency communication (3)

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

Professor Mohamed-Slim Alouini named a Fellow of SPIE and a Distinguished Lecturer of the IEEE Photonics Society

4 min read ·
Professor Mohamed-Slim Alouini earns SPIE Fellow and IEEE Distinguished Lecturer titles, highlighting his influential contributions to optical wireless communications.

Outstanding KAUST research acknowledged by leading photonics journal

1 min read ·
KAUST professors Boon Ooi and Osman Bakr and their respective research groups have recently had their collaborative research recognized by one of the major journals for optics and photonics, Light: Science & Applications (LSA). The teams’ paper— titled "High-speed color-converting photodetector with all-inorganic CsPbBr3 perovskite nanocrystals for ultraviolet light communication—" was awarded as an “Outstanding Paper of Light: Science & Applications in 2020.”
<> reliability testing (3)

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

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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.
<> renewable energy systems (3) <> reproducibility issues (3)

Reproducibility in Computer Science - Part 1

-

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

-

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.
<> resiliency (3) <> resilient cyber-physical (3) <> RF circuits (3)

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

1 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.

Srujana Kagita

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

Jose Manuel Gonzalez

Jose Manuel Gonzalez worked as a Post Doctorate Fellow at Integrated Microwaves Packaging Antennas & Circuit Technology (IMPACT) Research Group with Professor Atif Shamim at King Abdullah University of Science and Technology (KAUST) during (2012-2013). Currently, Jose is working as an Adjunct Professor, in the Electronic Technology Department​ at the University of the Basque Country UPV-EHU (Universidad del País Vasco-Euskal Herriko Unibertsitatea). Research Interests Jose' research interests include RF circuit and EM structure design for agile wireless communications, Advanced LTCC System-on
<> risk assessment (3)

Control Theoretic Approaches to Computational Modeling and Risk Mitigation for Large Crowd Management

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KAUST

Abstract We develop a computational framework for risk mitigation in high population density events. With an increased global population, the frequency of high population density events is naturally increased. Therefore, risk-free crowd management plans are critical for efficient mobility, convenient daily life, resource management, and most importantly mitigation of any inadvertent incidents and accidents such as stampedes. The status-quo for crowd management plans is the use of human experience/expert advice. However, most often such dependency on human experience is insufficient, flawed

Flexible Multivariate, Spatial, and Causal Models for Extremes

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B4 L5 R5220

Risk assessment for natural hazards and financial extreme events requires the statistical analysis of extreme events, often beyond observed levels. The characterization and extrapolation of the probability of rare events rely on assumptions about the extremal dependence type and about the specific structure of statistical models. In this thesis, we develop models with flexible tail dependence structures, in order to provide a reliable estimation of tail characteristics and risk measures. Our novel methodologies are illustrated by a range of applications to financial, climatic, and health data.

Yan Gong

Ph.D. Student, Statistics
Yan Gong was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Yan successfully defended her PhD thesis entitled " Flexible Multivariate, Spatial, and Causal Models for Extremes" on March 28th, 2023; see her PhD thesis here. Her PhD committee was composed of Professors Raphaël Huser (chair), Valérie Chavez-Demoulin (external examiner from HEC Lausanne at UNIL, Switzerland), David Bolin, and Mohammed-Slim Alouini. For her next career steps, Yan has accepted a short-term postdoctoral research position at
<> RNA genes (3)

Promoters identification and analysis

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B1 L2 R2202

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

Computational Analysis of Transcriptional Regulation after Single and Multiple Drug Administration.

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B3 L5 R5209

With the advances in transcriptomic analysis, the monitoring of genome-wide gene expression provides a powerful approach for determining the action of drugs. In this thesis, we analyzed the transcriptional responses of cells treated with drugs either alone or in combinations to explore their effects in two different applications: breast cancer therapy and cell conversion.

Novel computational methods for promoter identification and analysis

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B2 L5 R5209

In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.
<> safe autonomy (3) <> scientific enterprise (3)

Reproducibility in Computer Science - Part 1

-

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

-

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.
<> SDN (3)

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.

Building SANDS at KAUST

1 min read ·
​​​​​We live in a connected world where networked systems play an increasingly important role. These systems, which are the foundational pillars of our modern digital lives, are the result of some remarkable technological advancements and progress in computer science over the past three decades.

Wiem Abderrahim

Postdoctoral Research Fellow (former), Networking Research Lab
Wiem Abderrahim was a postdoctoral fellow under the supervision of Prof. Mohamed-Slim Alouini and Prof. Basem Shihada at the Communication Theory Lab, King Abdullah University of Science and Technology (KAUST). She completed her engineering studies in telecommunications with honors at the Higher School of Communications of Tunis, Carthage University, in 2013. In 2017, she received her doctoral degree in Information and Communications Technologies from the same institution. Before joining KAUST, she worked as an adjunct professor at the Higher School of Communications of Tunis in 2017. She
<> Security and Privacy (3)

Rehana Yasmin

Rehana Yasmin is currently a Research Scientist at the CyberSaR Lab in KAUST. Before joining KAUST, she had been working as a researcher in the area of Automotive Cybersecurity and Resilience at Huawei International. Prior to above, she served as a lecturer at University of Azad Jammu and Kashmir, and later as an assistant professor at Mirpur University of Science and Technology, in Pakistan. She also obtained a short experience of postdoc from University of Padova, Italy. Research Interests Yasmin's research interests lie in security and privacy protocols, applied cryptography, AI for anomaly

Osama Hassan

Osama Hassan is a Master's student studying under the supervision of Prof. Mohamed-Slim Alouini in the Communications Theory Lab (CTL) at King Abdullah University of Science and Technology (KAUST). Education Osama received his Bachelor of Science in Engineering (BSE) in Electrical Engineering from Princeton University in 2018, with a concentration in Security and Privacy, and a certificate in Applications of Computing. Early Career At Princeton, Osama conducted research at the Houck Lab for Quantum Computing and Condensed Matter Physics, where he worked on designing and testing quantum

Juexiao Zhou

Ph.D. Student, Computer Science
<> semantic analysis (3) <> semiconductor laser (3) <> semiconductor optoelectronic devices (3)
optoelectronic device can adapt to light

Artificial neurons enable neuromorphic computing with light

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

Yasser Khan

Yasser obtained a Master's degree in Electrical Engineering under the supervision of Professor Boon Ooi at King Abdullah University of Science and Technology (KAUST). He worked on his master's thesis, "Energy harvesting in random medium" at Oxford University under the supervision of James Kirkpatrick, Ph.D. (Oxford), Prof. Boon Ooi (KAUST), and Prof. Andrea Fratalocchi (KAUST). He graduated Summa Cum Laude in Electrical Engineering from the University of Texas at Dallas in Spring 2010. Previously, Yasser has worked as a graduate student researcher at the Center for Advanced Molecular

Mohammed Zahed Mustafa Khan

Postdoctoral Research Fellow, Photonics Laboratory
Mohammed Zahed Mustafa Khan worked as a Post-Doctoral fellow at the Photonics lab after receiving his Ph.D. degree in Electrical Engineering under the supervision of Prof. Boon Ooi from King Abdullah University of Science and Technology (KAUST). Mohammed received his Master’s degree in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, in 2004, and Bachelor’s degree in Electronics and Communication from Osmania University, India, in 2001. Mohammed is currently an Assistant Professor at King Fahd University of Petroleum and Minerals, Saudi Arabia
<> sensors fabrication (3) <> signal analysis (3) <> Signal and Image Processing (3) <> Signal Applications (3) <> Social Network Analysis (3)

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.

Efficiency Assessment of Approximated Spatial Predictions for Large Datasets

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KAUST

Our suggested criteria are more useful for the determination of tuning parameters for sophisticated approximation methods of spatial model fitting. To illustrate this, we investigate the trade-off between the execution time, estimation accuracy, and prediction efficiency for the TLR method with intensive simulation studies and suggest proper settings of the TLR tuning parameters.

Critical Phenomena in Financial Markets and Social Networks

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B9 L2 R2322

Analogies between financial markets and critical phenomena have long been observed empirically. So far, no convincing theory has emerged that can explain these empirical observations. Here, we take a step towards such a theory by modeling financial markets as a lattice gas.
<> software/hardware co-design (3) <> spatial modulation (3)

Estimating High-Resolution Red Sea Surface Temperature Hotspots, Using a Low-Rank Semiparametric Spatial Model

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KAUST

In this work, we estimate extreme sea surface temperature (SST) hotspots, i.e., high threshold exceedance regions, for the Red Sea, a vital region of high biodiversity. We analyze high-resolution satellite-derived SST data comprising daily measurements at 16703 grid cells across the Red Sea over the period 1985–2015. We propose a semiparametric Bayesian spatial mixed-effects linear model with a flexible mean structure to capture spatially-varying trend and seasonality, while the residual spatial variability is modeled through a Dirichlet process mixture (DPM) of low-rank spatial Student-t processes (LTPs). By specifying cluster-specific parameters for each LTP mixture component, the bulk of the SST residuals influence tail inference and hotspot estimation only moderately. Our proposed model has a nonstationary mean, covariance and tail dependence, and posterior inference can be drawn efficiently through Gibbs sampling. In our application, we show that the proposed method outperforms some natural parametric and semiparametric alternatives.

Shuaishuai Guo

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

Hui Zhao

Hui Zhao is an MS/Ph.D. student in the Communication Theory Lab (CTL) under the supervision of Professor Mohamed-Slim Alouini at King Abdullah University of Science and Technology (KAUST). Education and Early Career Hui Zhao obtained his bachelor degree in Telecommunications Engineering from Southwest University (SWU) in 2016. Research Interest Hui Zhao is focusing in the area of performance analysis of wireless communication, optimization about power allocation, stochastic geometry, spatial modulation. Education Profile MS in Electrical Engineering, Kind Abdullah University of Science and
<> spatio-temporal modeling (3)

Computational and Statistical Advances in Spatio-Temporal Modeling: Causality, Deep Learning, and High-Performance Computing

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B2, L5, R5209

Recent advances in environmental monitoring and remote sensing have led to an unprecedented increase in spatial and spatio-temporal data complexity, presenting both opportunities and challenges for environmental science. This thesis explores three critical challenges in environmental data analysis.

CEMSE New Faculty: David Bolin, Associate Professor of Mathematical Statistics

1 min read ·
David Bolin is an associate professor of mathematical statistics who joined the KAUST Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division earlier this month from the Department of Mathematical Sciences at the University of Gothenburg. Before joining KAUST, Bolin received both his Ph.D. degree in mathematical statistics and M.S.c in engineering mathematics from Lund University, Sweden, in 2012 and 2007, respectively. Upon completing his Ph.D., he spent one year at Umeå University, Sweden, working as a postdoctoral fellow before moving to the Chalmers University of Technology. In 2016, Bolin became an associate professor of mathematics at the University of Gothenburg, where a year later he received the title of Docent in mathematical statistics.

Pratik Nag

Ph.D. Student, Statistics
Pratik Nag is a Ph.D. candidate at the KAUST Environmental Statistics research group under the supervision of Professor Ying Sun. Before joining KAUST, Pratik obtained a master's degree in statistical quality control and operation research from the Indian Statistical Institute, India. Research Interests Pratik's research interests focus on machine learning, artificial intelligence and statistical techniques to solve problems related to spatio-temporal processes. Education Profile Master's degree in Statistical Quality Control and operation research, Indian Statistical Institute, India
<> statistical inference (3)

High-dimensional Q-learning for Dynamic Treatment Regimes

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B3 L5 R5220

Dynamic treatment regimes are a set of decision rules and each treatment decision is tailored over time according to patients’ responses to previous treatments as well as covariate history. There is a growing interest in development of correct statistical inference for optimal dynamic treatment regimes to handle the challenges of nonregularity problems in the presence of nonrespondents who have zero-treatment effects, especially when the dimension of the tailoring variables is high.

Transparent and Robust Causal Inference in Data Science

Carlos Cinelli, Ph.D. candidate, Department of Statistics, UCLA

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KAUST

The past few decades have witnessed rapid and unprecedented theoretical progress in the science of causal inference, ranging from the “credibility revolution” with the popularization of quasi-experimental designs, to the development of a complete solution to non-parametric identification with causal graphical models. Most of these theoretical progress, however, relies on strong, exact assumptions, such as the absence of unobserved common causes, or the absence of certain direct effects. Unfortunately, more often than not these assumptions are very hard to defend in practice. This leads to two undesirable consequences for applied quantitative work in the data-intensive sciences: (i) important research questions may be neglected, simply because they do not exactly match the requirements of current methods; or, (ii) researchers may succumb to making the required “identification assumptions” simply to justify the use of available methods, but not because these assumptions are truly believed (or understood). In this talk, I will discuss new theories, methods, and software for permitting causal inferences under more flexible and realistic settings. These tools empower scientists, and policymakers to both examine the sensitivity of causal inferences to violations of its underlying assumptions, and also to draw robust and trustworthy conclusions from settings in which traditional methods fail.

Alexandre de Bustamante Simas

Senior Research Scientist, Statistics
<> statistical methods (3)

Geospatial Data Science for Public Health Surveillance

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B9 L2 R2325

This talk will give an overview of statistical methods and computational tools for geospatial data analysis and health surveillance, highlighting challenges related to data biases and availability.

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

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B4 L5 R5220

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

Sarah Alghamdi

Ph.D. Student, Computer Science
Sarah Alghamdi is a Ph.D. candidate in the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Robert Hoehndorf. Research Interests Sarah's research interests include applications of artificial intelligence and using statistical methods to genomics and healthcare. Professional Profile Program Committee for the International Conference of Biomedical Ontology (ICBO 2022) Program Committee for the International Society of Molecular Biology (ISMB 2022) - Bio-Ontology track 2018-2021: Teaching Assistant positions: CS
<> stochastic optimization (3)

Distributed AI: Optimal algorithms for distributed stochastic non-convex optimization

Usman A. Khan, Associate Professor, Tufts University

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KAUST

Featured Sessions
For more information please visit the website

Raul Tempone

Professor Raul Tempone is an worlwide recognized researcher in numerical analysis and uncertainty quantification. Professor Raul Tempone at KAUST leads the stochastic numerics research group, significantly contributing to Saudi Arabia's Vision 2030 goals through advancements in computational science. His work in adaptive algorithms, Bayesian inverse problems, and scientific machine learning drives forward critical applications in technology and sustainability, embodying KAUST's commitment to global scientific leadership and economic diversification.

Li Xia

Postdoctoral Research Fellow, Networking Research Lab
Li Xia was a Postdoctoral Research Fellow at Networking Research Lab (NETLAB) in King Abdullah University of Science and Technology (KAUST), working with Professor Basem Shihada in his research group. Currently, Li is an Associate Professor at Tsinghua University, China. Research Interests Li's research interests included Operations research, stochastic optimization, queueing theory, Markov decision processes. Selected Publications L. Xia and B. Shihada, "Decentralized Transmission Scheduling in Energy-Critical Multi-Hop Wireless Networks", in Proc. American Control Conference, pp. 113-118
<> stochastic partial differential equations (3) <> supercomputers (3) <> Survival analysis (3) <> thin films (3)

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.

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
<> thin-film transistors (3) <> tracking (3)

Pointing and Trajectory Tracking Control for Optical Wireless Communication

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

-

KAUST

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

Rui Li

Rui Li is an Electrical Engineering Ph.D. candidate in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Rui Li obtained bachelor of engineering degree in Telecommunication Engineering from Xidian University in China in 2013. After that in 2016, he received his master degree in Electrical Engineering from University of Science and Technology of China in 2016. Rui started his career life as a Research Assistant at State
<> Training (3) <> Transistors (3)
KAUST-CEMSE-ECE-PhD-Dissertation-Defense-Dhanu-Chetri-Ultrawide-Bandgap-Semiconductor-Devices-and-Monolithic-Circuits

Ultrawide Bandgap Semiconductor Devices and Monolithic Circuits

-

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
KAUST-CEMSE-ECE-ASL-Dhanu-Chettri-0561

Dhanu Chettri

<> Trustworthy AI (3) <> TU Ilmenau (3)

Exact Backstepping Control for Systems in Pure Feedback Form

Prof. Johann Reger, Computer Science and Automation Faculty, TU Ilmenau, Germany

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KAUST

Traditional backstepping approaches may struggle to asymptotically stabilize systems in pure feedback form, due to its inherent implicit equations. Approximation based designs only have a limited domain of validity and turn out sensitive to model uncertainty and disturbances. We propose a new design that circumvents the necessity of solving implicit algebraic equations by introducing new state variables. Additional augmentations to the backstepping Lyapunov design lead to explicit expressions for the associated differential equations. The result is a dynamic state feedback, capable of asymptotically stabilizing the origin of a general class of nonlinear systems, based on just standard assumptions.

Part 1 - Introduction to backstepping control

Prof. Johann Reger, Computer Science and Automation Faculty, TU Ilmenau, Germany.

-

KAUST

Backstepping is a widely applicable control technique based on Lyapunov theory that under rather mild assumptions leads to families of control laws for a large class of nonlinear systems. Focusing on systems of ordinary differential equations, we introduce the basic concept (integrator backstepping), generalize it, among others, to systems in strict feedback form and pure feedback form, which all enjoy an inherent controllability property, captured in the system structure. The course ends with extending the setting to the adaptive backstepping case, resorting to the certainty equivalence principle and Barbalat's lemma. The course is furnished by a series of exercises to let the students gather experience on tailored examples.

Part 2 - Introduction to backstepping control

Prof. Johann Reger, Computer Science and Automation Faculty, TU Ilmenau, Germany.

-

KAUST

Backstepping is a widely applicable control technique based on Lyapunov theory that under rather mild assumptions leads to families of control laws for a large class of nonlinear systems. Focusing on systems of ordinary differential equations, we introduce the basic concept (integrator backstepping), generalize it, among others, to systems in strict feedback form and pure feedback form, which all enjoy an inherent controllability property, captured in the system structure. The course ends with extending the setting to the adaptive backstepping case, resorting to the certainty equivalence principle and Barbalat's lemma. The course is furnished by a series of exercises to let the students gather experience on tailored examples.
<> UAV communications (3) <> Ultra-massive MIMO systems (3)

Analysis and Optimization of Massive MIMO Systems via Random Matrix Theory Approaches

-

B1 L3 R3119

Massive multiple-input multiple-output (MIMO) is a key enabling technology to achieve the required spectral and energy efficiency of the next generation of wireless networks. By endowing the base station (BS) with hundreds of antennas and relying on spatial multiplexing, massive MIMO allows impressive advantages in many fronts. To reduce this promising technology to reality, thorough performance analysis has to be conducted. Along this line, this work is focused on the convenient high-dimensionality of massive MIMO’s corresponding model. Indeed, the large number of antennas allows us to harness asymptotic results from Random Matrix Theory to provide accurate approximations of the main performance metrics. The derivations yield simple closed-form expressions that can be easily interpreted and manipulated in contrast to their alternative random equivalents. Accordingly, in this dissertation, we investigate massive MIMO in different contexts.

Ikram Boukhedimi

Ikram Boukhedimi was born in Blida, Algeria. She received an Electrical Engineering degree from the Ecole Polytechnique d'Alger, Algeria, in 2013 and an M.S. in Mathematics, Control and Electrical Engineering from Universite de Poitiers, France in 2014. and she earned a Ph.D. in Electrical Engineering at King Abdullah University of Science and Technology in June 2019, Saudi Arabia in Professor Mohamed Slim Alouini’s Communication Theory Lab in Electrical Engineering research group. Her research interests include random matrix theory approaches applied to wireless communication systems

Alice Faisal

Visiting Student (former), Electrical and Computer Engineering
Visiting Student at King Abdullah University of Science and Technology (KAUST), chair of IEEE women in engineering affinity group at Effat University student branch.
<> Ultra-wideband communication (3)

Tarig Ballal Khidir Ahmed

Research Scientist Laboratory for Nanomedicine, Computational Bioscience Research Center King Abdullah University of Science and Technology | KAUST

Mohammad Tamim Alkhodary

Ph.D. degree in electrical engineering from the King Fahd University of Petroleum and Minerals. Postdoctoral Fellow at École de technologie supérieure, Montreal, QC, Canada

Mohamed Saadeldin

Postdoctoral Research Fellow, Sensors
Postdoctoral Research Fellow, Sensors Lab at King Abdullah University of Science and Technology (KAUST), Assistant Professor, University College Dublin .
<> Ultrasonic-based Localization (3)

Signal Processing and Optimization Techniques for High Accuracy Indoor Localization, Tracking, and Attitude Determination

-

B1 L3 R3119

High-accuracy indoor localization and tracking systems are essential for many modern applications and technologies. However, accurate location estimation of moving targets is challenging. This thesis addresses the challenges in indoor localization and tracking systems and proposes several solutions. A novel signal design, which we named Differential Zadoff-Chu, allows us to develop algorithms that accurately estimate the distances of static and moving targets even under random Doppler shifts. The results show that the proposed algorithms outperform the state-of-the-art in terms of both accuracy and complexity.

Mohammed Hussain AlSharif

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

Fat-hy Omar Rajab

Master's Thesis Abstract The multi-agent robotic system has been proved to be more superior in undertaking functionalities, arduous or even impossible when performed by single agents. The increased efficiency in multi-agent systems is achieved by the execution of the task in a cooperative manner. But to achieve cooperation in multi-agent systems, a good localization system is an important prerequisite. Currently, most of the multi-agent systems rely on the use of the GPS to provide global positioning information which suffers great deterioration in performance in indoor applications, and also
<> underwater optical communications (3)

Underwater optical communication and sensing technology in silent ocean

-

KAUST

This dissertation aims to investigate and address noisy ocean issues and build large-scale underwater sensor networks by optical communication and sensing technology. The dissertation proposes using UWOC and FC&S technology to replace the conventional acoustic communication technology and reduce the noise in the ocean. UWOC helps achieve high-speed wireless communications between sensors, vehicles, and even humans for UIoT. The significant challenges of developing UWOC systems are the complex underwater environment's attenuation, scattering, and turbulence effects. This dissertation studied the turbulence effects on the UWOC system’s performance and addressed the pointing-acquisition-and-tracking issues.

Gbps Laser-based underwater wireless optical communication

-

B9 L2 H2

I will focus my discussion on optoelectronic devices and system challenges facing long-distance, multiple-Gbps underwater wireless optical communication. The future perspective of underwater photonics will also be discussed.

Mohammed Sait

Mohammed Sait is a Ph.D. student in Photonics Laboratory in the Division of Computer, Electrical and Mathematical Sciences & Engineering (CEMSE) under the supervision of Professor Boon Ooi at King Abdullah University of Science & Technology (KAUST). Research Interests Mohammed's research interests include​Underwater optical communication, and VLC and LiFi technology. Education Profile ​BS. in electronics and communication engineering, University of Leicester, UK (2013-2016). MS. in Digital communication systems, Loughborough University, UK (2016-2017). Awards and Distinctions Clarke Griffith's
<> Underwater Optical Wireless Communications and Networking (3)

Nasir Saeed

Postdoctoral Research Fellow, Electrical and Computer Engineering
Postdoctoral Fellow at Communication Theory Lab, King Abdullah University of Science and Technology (KAUST) working with Professor Mohamed-Slim Alouini and Professor Tareq Y. Al-naffouri ,Associate Professor with the Department of Electrical and Communication Engineering, United Arab Emirates University (UAEU)

Hassan M. Oubei

Hassan Makine Oubei obtained a Ph.D. degree in Electrical Engineering under the supervision of Prof. Boon Ooi at the Computer, Electrical, and Mathematical Sciences and Engineering Division at KAUST. He received the B.S (2007) degree in Electrical Engineering from the City College of New York, USA. He joined Corning Incorporated’s research and development (R&D) division in Corning, New York where he worked as Opto-Electronics Engineer to develop synthetics green lasers for display applications (2007-2011) and Process Measurements Engineer (2011-2013). While working for Corning, Hassan also

Abdulkadir Celik

Associate Professor, University of Southampton
Dr. Abdulkadir Celik, a Senior Research Scientist at KAUST and IEEE senior member, specializes in next-gen wireless networks and serves as an editor for top IEEE journals.
<> underwater sensor platform (3) <> Underwater wireless optical communication (3)

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

-

B3 L5 R5209

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

Underwater optical communication and sensing technology in silent ocean

-

KAUST

This dissertation aims to investigate and address noisy ocean issues and build large-scale underwater sensor networks by optical communication and sensing technology. The dissertation proposes using UWOC and FC&S technology to replace the conventional acoustic communication technology and reduce the noise in the ocean. UWOC helps achieve high-speed wireless communications between sensors, vehicles, and even humans for UIoT. The significant challenges of developing UWOC systems are the complex underwater environment's attenuation, scattering, and turbulence effects. This dissertation studied the turbulence effects on the UWOC system’s performance and addressed the pointing-acquisition-and-tracking issues.

CEMSE's new underwater wireless optical communication (UWOC) opens new frontier for off-shore control system

1 min read ·
Billions of liters of fuel travel every day along an intricate network of pipelines. Reports show that 15 thousand kilometers of infrastructure exist worldwide, with more than a third being underwater. Efficient real-time monitoring is the next frontier to achieve improved industrial productivity and prevent environmental accidents.
<> Université de Montréal (3)

Part 3: Variational structures and Fourier approximation techniques for mean-field game systems

-

B1 L3 R3119

Mean-field game (MFG) systems of partial differential equations (PDE) arise in modeling huge populations of indistinguishable rational agents that play non-cooperative differential games. Mathematically, an MFG system comprises of a Hamilton-Jacobi-Bellman PDE coupled with a Kolmogorov-Fokker-Planck PDE in a highly nonlinear fashion. Hence, theoretical and numerical treatments of MFG systems are highly challenging problems.

Part 1: Variational structures and Fourier approximation techniques for mean-field game systems

-

B1 L3 R3119

Mean-field game (MFG) systems of partial differential equations (PDE) arise in modeling huge populations of indistinguishable rational agents that play non-cooperative differential games. Mathematically, an MFG system comprises of a Hamilton-Jacobi-Bellman PDE coupled with a Kolmogorov-Fokker-Planck PDE in a highly nonlinear fashion. Hence, theoretical and numerical treatments of MFG systems are highly challenging problems. Day 1: I will show how to transform suitable mean-field game (MFG) systems into infinite-dimensional convex optimization problems. Furthermore, I will present Uzawa’s algorithm and augmented Lagrangian approach for solving convex optimization problems. Finally, I will demonstrate how to apply these methods to approximate solutions of corresponding MFG systems.

Part 2: Variational structures and Fourier approximation techniques for mean-field game systems

-

B1 L3 R3119

Mean-field game (MFG) systems of partial differential equations (PDE) arise in modeling huge populations of indistinguishable rational agents that play non-cooperative differential games. Mathematically, an MFG system comprises of a Hamilton-Jacobi-Bellman PDE coupled with a Kolmogorov-Fokker-Planck PDE in a highly nonlinear fashion. Hence, theoretical and numerical treatments of MFG systems are highly challenging problems. Day 2: I will present new Fourier approximation techniques for nonlocal MFG systems and discuss how these techniques fit the variational framework presented on Day 1. Then I will introduce the Chambolle-Pock primal-dual hybrid gradient optimization method and apply a variant of this method to approximate nonlocal MFG models via Fourier approximation techniques above.
<> University of Minnesota (3)

The Evolution of Machine Learning

-

B4 B5 A0215

This talk presents an overview of recent methodological advances in developing item-based nearest-neighbor-based recommender systems that have substantially improved their performance. Biography George Karypis is a Distinguished McKnight University Professor and an ADC Chair of Digital Technology at the Department of Computer Science & Engineering at the University of Minnesota, Twin Cities. His research interests span the areas of data mining, high performance computing, information retrieval, collaborative filtering, bioinformatics, cheminformatics, and scientific computing. His research has

Interesting Problems in Estimation and Control on Smart Road Vehicles

-

B1 L2 R4214

A number of exciting vehicle automation and active safety systems are being developed by research groups around the world. This talk focuses on novel sensors, estimation algorithms and control systems that can fill critical gaps in the automation technologies under development. The first part of this seminar describes interesting sensing and estimation solutions that can significantly improve the effectiveness of active safety systems. The second part of the seminar describes the development of a new class of narrow commuter vehicles designed to address traffic congestion, improve highway mobility and provide very high fuel economy. The final part of the seminar describes the development of a smart bicycle with instrumentation that can track trajectories of nearby vehicles on the road and provide warnings to the motorist, if a potential car-bicycle collision is detected.

PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views

Faisal M. Almutairi, Ph.D. Candidate, Electrical and Computer Engineering, University of Minnesota

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B1 L4 R4214

The proposed method, called PREMA, leverages low-rank tensor factorization tools to provide recovery guarantees under certain conditions. PREMA is flexible in the sense that it can perform the disaggregation task on data that have missing entries, i.e., partially observed. The proposed method considers challenging scenarios: i) the available views of the data are aggregated in two dimensions, i.e., double aggregation, and ii) the aggregation patterns are unknown. Experiments on real data from different domains, i.e., sales data from retail companies, crime counts, and weather observations, are presented to showcase the effectiveness of PREMA.
<> Unmanned aerial vehicles UAVs (3) <> UV Communications (3)

What’s the Story with UAV Cellular Communications?

Prof. Giovanni Geraci, Assistant Professor, University Pompeu Fabra (UPF) in Barcelona, Spain

-

KAUST

What will it take for UAVs—and the associated ecosystem—to take off? Arguably, ubiquitous high-capacity links paired with hyper-reliable command and control all along. And indeed, meeting these aspirations may entail a full-blown mobile network support. While the understanding of UAV cellular communications has been advancing, many fundamental challenges remain to be addressed, with new applications demanding original solutions. In this talk, we blend academic and industrial views, navigating from 4G to 6G UAV use cases, requirements, and enabling technologies

KAUST Discovery - Unleashing ultraviolet brings visible improvement

1 min read ·
High-speed communication systems based on ultraviolet radiation are now in sight.

Jiusi Zhou

Jiusi Zhou is a Ph.D. student under the supervision of Prof. Mohamed-Slim Alouini at the Communication Theory Lab (CTL) in King Abdullah University of Science and Technology (KAUST). Education and Early Career Jiusi Zhou obtained his Bachelor of Engineering from Communication and Information Engineering Department, University of Electronic Science and Technology of China (UESTC), Chengdu, Sichuan, P. R. China in 2018. Before formally joining KAUST, he worked as a internship student at CTL in KAUST during Aug 2017 to Jan 2018. Research Interest Jiusi is familiar with Ultraviolet Communication
<> Virtual Element Method (3)

C1-Conforming Virtual Element Method (VEM) for Optimal Control of Oseen Equations with a Stream-Function Formulation

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B1 L3 R3426

This talk presents a C¹-conforming Virtual Element Method for the optimal control of generalized Oseen equations, detailing its discretization strategies, theoretical error estimates, and numerical validation on polygonal meshes.

Parallel multilevel solvers for virtual element discretizations of saddle point problems

-

B1 L3 R3119

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

Virtual Element Approximation of Eigenvalue Problems

Prof. Francesca Gardini, Università di Pavia

-

B1 L3 R3119

We will discuss the solution of eigenvalue problems associated with partial differential equations (PDE)s that can be written in the generalised form Ax = λMx, where the matrices A and/or M may depend on a scalar parameter. Parameter dependent matrices occur frequently when stabilised formulations are used for the numerical approximation of PDEs. With the help of classical numerical examples we will show that the presence of one (or both) parameters can produce unexpected results.
<> wide bandgap semiconductor (3) <> wireless (3)

Near Field Wireless Power Transfer: Circuits and Application

-

KAUST

Recently, wireless power transfer has been used in mobile phones, electric vehicles, medical implants, wireless sensor networks, unmanned aerial vehicles, and so on. In this seminar, we will walk through circuit theory and simulations that illustrate the nature and constraints of the technology. We will also address contemporary topics related to application of wireless power transfer in electric vehicle applications.

Pointing and Trajectory Tracking Control for Optical Wireless Communication

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

-

KAUST

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

Choosing the right scheme for green communications

1 min read ·
Performance analysis reveals how different resource allocation schemes may impact the energy efficiency of a cognitive radio system.
<> wireless communications network (3) <> wireless communications. (3) <> 3D graphics (2)

Web-based 3D Visualization

-

B9 L2 H2 H2

In this seminar I will present how to create 3D computer graphics and visualization systems for the web, using WebAssmbly and WebGPU language specifications, which are new, bleeding-edge technologies. Previously, accelerated graphics on the web was based on JavaScript libraries, which is still very popular, but they do not offer detailed memory management and code optimization, necessary for systems requiring high memory load and high computational demands. WebAssembly and WebGPU can be compiled from the C++ or Rust code, which also allows the deployment of the same codebase either for web or for the desktop-based applications.

Marco Agus

Marco Agus was a Research Engineer in the High Performance Visualization Group (HPV) working with Professor Markus Hadwiger at King Abdullah University of Science and Technology (KAUST). Education and Early Career He obtained his master degree in Electronic Engineering from the University of Cagliari in Italy in 1999. He has a Ph. D. in Mechanical Design from the University of Cagliari. Before joining KAUST, Marco was a researcher at Visualization and Virtual Reality Group in the Center for Advanced Studies, Research and Development in Sardinia (CRS4) in Italy. After that in 2007, he moved to
<> 3D object detection (2)

Indoor 3D Scene Understanding Using Depth Sensors

-

KAUST

One of the main goals in computer vision is to achieve a human-like understanding of images. This understanding has been recently represented in various forms, including image classification, object detection, semantic segmentation, among many others. Nevertheless, image understanding has been mainly studied in the 2D image frame, so more information is needed to relate them to the 3D world. With the emergence of 3D sensors (e.g. the Microsoft Kinect), which provide depth along with color information, the task of propagating 2D knowledge into 3D becomes more attainable and enables interaction between a machine (e.g. robot) and its environment. This dissertation focuses on three aspects of indoor 3D scene understanding: (1) 2D-driven 3D object detection for single frame scenes with inherent 2D information, (2) 3D object instance segmentation for 3D reconstructed scenes, and (3) using room and floor orientation for automatic labeling of indoor scenes that could be used for self-supervised object segmentation. These methods allow capturing of physical extents of 3D objects, such as their sizes and actual locations within a scene.

Jean Lahoud

Jean Lahoud was a Ph. D. student in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at KAUST. Education and Early Career Jean Lahoud received his Bachelor of Engineering in Mechanical Engineering from Notre Dame University in Lebanon in 2012. In 2014, he obtained his Master of Engineering degree in the same field from American University of Beirut in Lebanon. Before joining KAUST, Jean was a product manager at Murex systems in Lebanon. Research Interest Jean Lahoud is interested in 3​D scene understanding using RGB-D sensors. Honors and Awards In
<> 3D Shape Creation (2)

Mohamed Ibrahim

Postdoctoral Research Fellow, Computer Science
Mohamed Ibrahim is a Postdoctoral Research Fellow in High-Performance Visualization Group (VCCVIS) working with Prof. Markus Hadwiger at King Abdullah University of Science and Technology (KAUST). Education and Early Career He earned his Bachelor’s degree in Computer Engineering from the American University in Cairo (AUC) in 2010. Later on, he obtained a Master’s degree in Computer Science from KAUST in 2012. He graduated from KAUST with a Ph.D. in Computer Science in 2019. Research Interest Mohamed Ibrahim's research is concerned with Large-Scale data visualization. He's especially interested

Ibraheem Alhashim

Ibraheem Alhashim is a Remote Researcher working with Professor Peter Wonka. Education and Early Career Ibraheem Alhashim completed his B.Sc. with honors in Computer Science at the Portland State University in 2008, followed by his M.Sc. in Computer Science in 2011 under the supervision of Prof. Hao Zhang and his Ph.D. in Computer Science in 2016 under the supervision of Prof. Hao Zhang and Prof. Ghassan Hamarneh at Simon Fraser University in Canada. During both his Master and Ph.D., Alhashim was working at the GrUVi Lab at Simon Fraser University in Canada. Dr. Alhashim joined KAUST in 2017
<> 4D seismic (2) <> 5G antennas (2) <> 5th generation cellular (2) <> 6G and Beyond (2) <> accelerators (2) <> Acoustic sensing and communications (2) <> acoustic signal processing (2) <> acoustic-elastic metamaterials (2) <> Adaptive communication systems (2) <> adaptive methods (2) <> Adaptive Optics (2)

Gyan Deep Verma

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

Congli Wang

Congli Wang is a Ph. D. candidate in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Congli Wang obtained his bachelor of engineering in Electrical Engineering from Tianjin University in China in 2015. After that, he joined KAUST and received his master degree in Electrical Engineering in 2016. Research Interest Congli is focusing in his research on Wavefront Sensing, Adaptive Optics, Computational Imaging and Computational Photography. He is working on
<> Advanced Perception (2) <> Aeronautical Sciences (2)

Recent Progress in Aeronautical Sciences: Exquisite Stability of Insect Flight and a New Theory of Lift

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B2 L5 R5220

In this talk, I will present a special variational principle that we revived from the history of analytical mechanics: Hertz’ principle of least curvature. Using this principle, we developed a general (dynamical) closure condition that is, unlike the Kutta condition, derived from first principles. In contrast to the classical theory, the proposed variational theory is not confined to sharp-edged airfoils, i.e., it allows, for the first time, theoretical computation of lift over arbitrarily smooth shapes, thereby generalizing the century-old lift theory of Kutta and Zhukovsky. Moreover, the new variational condition reduces to the Kutta condition in the special case of a sharp-edged airfoil, which challenges the widely accepted concept regarding the viscous nature of the Kutta condition. We also generalized this variational principle to Navier-Stokes’, thereby discovering the fundamental quantity that Nature minimizes in every incompressible flow.

Mathematical Control Theory in Aeronautical Engineering: Boosted Maneuverability in Stall and Unconventional Stability of Insect Flight

Haithem Taha, Visiting Professor, Computer, Electrical and Mathematical Sciences and Engineering, KAUST

-

B9 L2 H2

The great Russian Mathematician Vladimir Arnold once said, “Mathematics is the part of physics where experiments are cheap”. In this talk, I will present two modern applications in aeronautical engineering where simple, but rigorous, mathematical control theory led to game-changing results exploiting nonlinearities and time-variation rather than obviating them.
<> aerospace software engineering (2)

Eric Feron's world: A short introduction

-

B3 L5 R5209

Over the past 30 years, my research has focused on problems involving aerospace information systems, give or take a couple of exceptions - I also seem to like things with wheels-. In the talk, I will introduce and discuss a few research topics that, I believe, best describe the kind of research I like to perform. The topics will include things as diverse as drones, airports, and the hunt for Lyapunov functions. I will also introduce an educational initiative focusing on systematically restoring "the sense of touch" in all Engineering disciplines, and which I would like to experiment with as part of the courses I will be in charge of at KAUST.

12 April 2020 International Day of Human Space Flight

1 min read ·
Rocket Scientists @KAUST Which is your main ongoing RESEARCH in the aerospace and space flight sectors? I study high pressure flames and high speed combustion. Both are simplified versions of what’s happening in rocket engines and other propulsion systems. Prof. Deanna Lacoste I work in high pressure combustion, just what is needed in a rocket engine or other propulsion device. Prof. William Roberts Two keywords here: "turbulence" and "computational aerodynamics". In my group we conduct research in simulating turbulent flows over airfoils, wings and other aerodynamic shapes to better
<> Affective Captioning (2) <> agricultural robotics (2) <> AI4Science (2) <> air pollution (2) <> algorithmics (2) <> Aluminium nitride (2) <> Analog circuit design (2)

Shaik Wasef

Shaik Wasef is a Master's student in the Electrical Engineering department at the Integrated Circuit and System Research Group under the supervision of Prof. Hossein Fariborzi at King Abdullah University of Science and Technology (KAUST). Shaik graduated from BITS-PILANI, India in the year 2018. His bachelor’s thesis project was based on configurational anisotropy based magnetic structures for multi-bit memory storage and logic gates. He pursued his bachelor’s thesis at KAUST under the supervision of Professor Hossein Fariborzi and currently working for the ICS group as an MSc/Ph.D. student

Abdullah Alshehri

My research focuses on designing efficient interfaces between the analog and digital domains through the development of low-power, high-performance CMOS interface circuits. The interface circuit encompasses key components such as amplifiers, filters, comparators, analog-to-digital converters (ADCs), each of which must be carefully optimized to meet the specific requirements of the target application. By addressing the challenges in analog-digital interfacing, this work aims to contribute to the advancement of integrated circuits and systems that can seamlessly connect real-world analog signals to their digital counterparts, with potential applications in sensor interfaces, data acquisition systems, and mixed-signal electronics. The research involves circuit design, simulation, integration, and experimental evaluation to create novel interface circuit topologies and techniques that improve power efficiency, speed, and overall performance.
<> Analog circuits (2) <> analog design optimization (2) <> Applied complexity (2) <> Arabic natural language processing (2) <> Artificial Neural Network (2) <> attitude determination (2) <> augmented reality (2) <> Automatic Control Systems (2) <> Automous Vehicles (2) <> autonomous systems (2) <> Autonomous Underwater Vehicles (2) <> Bayesian and computational Statistics (2) <> Bayesian Estimation (2) <> Big data analysis (2) <> bio-ontology (2) <> biological models (2)

Modeling and Automated Storytelling of Mesoscale Molecular Models

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KAUST

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

A Whole-genome Model of DNA Replication in Human Cells

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B5 L5 R5209

DNA replication is a fundamental cellular process and its precise regulation is crucial for maintaining genomic integrity. Inspired by the mathematical parallelism between DNA replication and the nucleation problem in one-dimensional crystal growth kinetics, we introduce a model that maps whole-genome replication dynamics based on the firing rate profiles of replication origins and fork movement.
<> biomechanics (2)