Profiles

Erik von Schwerin's research interests include Deterministic and stochastic differential equations, Computations with uncertainty, Error control and adaptivity, Systematic coarse graining, Hybrid modeling, and Multiscale methods.

Hakim Ghazzai, Senior Member, IEEE, joined the CEMSE Division as a Research Scientist in 2021. Previously, he held several research scholar positions with the Qatar Mobility Innovations Center (QMIC), Qatar, Karlstad University, Sweden, and Stevens Institute of Technology, NJ, USA. Since 2019, he has been on the Editorial Board of the IEEE Communications Letters and the IEEE Open Journal of the Communications Society. Since 2020, he joined the Board of IoT and Sensor Networks (a specialty section of Frontiers in Communications and Networks) as an associate editor. He is a recipient of appreciation for being an exemplary reviewer for IEEE Wireless Communications Letters in 2016 and IEEE Communications Letters in 2017. He is the recipient of the best paper awards at the 2023 IEEE International Conference on Smart Mobility and the 2017 International Conference on Advances in Vehicular Systems, Technologies, and Applications. He is the author and co-author of more than 190 publications. His general research interests include applied artificial intelligence for smart cities, the Internet of things, Intelligent Transportation Systems (ITS), mobile and wireless networks, and Unmanned Aerial Vehicles (UAVs).

Hakim's research focuses on the following areas:

• Green communications
• Smart city applications
• Artificial intelligence
• The Internet-of-Things
• Intelligent transportation systems

In 2019, Dr. Ruzayqat received his PhD in Mathematics from the University of Tennessee-Knoxville, USA. In 2012, he received a Bachelor degree in Physics and mathematics from Birzeit University, Palestine. Dr. Hamza Ruzayqat joined KAUST in November 2019 as a Post-Doctoral Research Fellow in the group of Computational Probability (COMPPROB). Late in 2022, he was promoted to Research Scientist and now a member in Omar Knio's Research Group. 

Dr. Ruzayqat main research is focused on Monte Carlo algorithms, data assimilation and uncertainty quantification. In particular, he is working on particle filters, SMCMC filters, unbiased estimators, inverse problems, parameter estimation and Bayesian inference in discrete/continuous-time, linear/nonlinear, low or high dimensional state-space models. In the past he worked on off-lattice kinetic Monte Carlo methods for atomic simulations.

Dr. Hatem Ltaief is a Principal Research Scientist in the Computer Electrical and Mathematical Sciences and Engineering Division at KAUST. His research focuses on mixed-precision algorithms, low-rank matrix computations, parallel programming models, and performance optimizations for high-performance computing (HPC) systems equipped with hardware accelerators.

He has contributed to integrating numerical algorithms into major scientific libraries including NVIDIA cuBLAS and Cray LibSci. Collaborating with domain scientists across diverse fields such as ground-based astronomy, geospatial statistics, computational chemistry, bioinformatics, and geophysics, Dr. Ltaief helps their scientific applications meet the exascale computing challenges.

Dr. Ltaief has co-authored all four of KAUST Gordon Bell finalist papers since 2022. In November 2024, he received the prestigious ACM Gordon Bell Prize (shared) in climate modeling for his contributions to developing an exascale climate emulator. This groundbreaking work addresses the computational and storage demands of high-resolution Earth System Model simulations and was achieved in collaboration with a distinguished team of experts.

He earned his engineering degree from Polytech Lyon at the University of Claude Bernard Lyon I in 2003, followed by an M.Sc. in applied mathematics in 2004 and a Ph.D. in computer science from the University of Houston in 2008. Before joining KAUST, Dr. Ltaief served as a research scientist at the Innovative Computing Laboratory in Knoxville Tennessee.

Dr. Ltaief has received multiple accolades including the Best Paper Award at the ACM PASC conference in 2018 and the Gauss Award for Best Paper at the ISC Conference in 2020. He currently serves as co-Editor-in-Chief of the ACM Transactions on Mathematical Software and as an Associate Editor-in-Chief of the Elsevier Parallel Computing Journal.

Dr. Hatem Ltaief's research focuses on mixed-precision algorithms, parallel numerical algorithms, parallel programming models, and performance optimizations for manycore architectures and high-performance computing.

ISLAM ASHRY received the B.S. and M.S. degrees from the University of Alexandria, Alexandria, Egypt, in 2003 and 2007, respectively, and the Ph.D. degree from Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA, in 2012. He is currently a Senior Research Scientist with the Photonics Laboratory, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. His research interests include optical sensors, fiber-optic sensors, optical communication, machine learning. He is a Senior Member of the National Academy if Inventors (NAI), a Senior Member of IEEE, a Senior Member of IEEE Photonics Society, and a member of SPIE.

Optical sensors; Fiber-optic sensors; Optical communication; Machine learning 

Janet van Niekerk is a Research Scientist in the Bayesian Computational Statistics and Modeling group. She works on Bayesian methods including prior construction and computational framework development for various applications, with a focus on Biostatistics.

Efficient Bayesian methods for practical implementation, statistics for medical applications, complex survival analysis, INLA.

Dr. Laurent Condat received his Ph.D. in Applied Mathematics in 2006 from Grenoble Institute of Technology, France. Following a postdoc at Helmholtz Zentrum München, Germany, he joined the French National Center for Scientific Research (CNRS) in 2008 as a permanent researcher. He worked at GREYC, Caen, before moving to GIPSA-Lab, Grenoble, in 2012. From 2016 to 2019, he served as a member of the French National Committee for Scientific Research. Since 2019, he has been on leave from the CNRS and is currently a Senior Research Scientist at KAUST.

He is a Senior Member of the IEEE and a Senior Area Editor of IEEE Transactions on Signal Processing. His recognitions include a Best Student Paper Award at IEEE ICIP 2005, the Best Ph.D. Award from Grenoble Institute of Technology, and several Meritorious Reviewer Awards. Since 2020, he has been listed among the world’s top 2% most influential scientists by Stanford University.

Dr. Condat’s research focuses on continuous optimization and its applications in machine learning, including deterministic and stochastic algorithms, convex relaxations and applications to machine learning in signal and image processing.

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

Dr. Mohamed Farhat received his Ph.D. in Optics and Electromagnetism from Aix-Marseille University where he obtained as well his Master degree in Theoretical Physics. His PhD dissertation was titled by “Metamaterials for Harmonic and Biharmonic Cloaking and Superlensing.” He has authored over 100 publications, including 1 edited book, 98 journal papers, 7 book chapters, and 5 international patents, as well as over 90 conference papers, with over 5100 citations, as of November 2023. He has organized several special sessions at the Meta conferences, and is active reviewer for many international journals in Physics including Physical Review Letters and Nature Physics. He has co-edited the book “Transformation Wave Physics: Electromagnetics, Elastodynamics and Thermodynamics” at Pan Stanford Publishing. 

His research is in the fields of plasmonics and metamaterials with applications spanning optical and acoustical waves.

Mohamed Elobaid is a Research Scientist at King Abdullah University of Science and Technology (KAUST). Prior to joining KAUST, he was a Postdoctoral researcher with the Italian Institute of Technology in Genoa where he was responsible of a joint research lab with Honda R&D. Elobaid obtained his PhD in Automatic Control (magna cum laude) from Sapienza University of Rome in cotutelle with University of Paris Saclay (2022).

• Molecular communication.
• Terahertz Communications.
• communication networks.
• AI for healthcare.
• Security and reliability analysis of next generation communication networks.

NABIL MOHAMMED (Senior Member, IEEE) received the B.Eng. degree (Hons.) in electrical power engineering from Tishreen University, Latakia, Syria, in 2013, the M.Eng. degree (Hons.) in electrical engineering from Universiti Teknologi Malaysia, Johor Bahru, Malaysia, in 2017, and the Ph.D. degree in power electronics from Macquarie University, Sydney, NSW, Australia, in 2022. 

During Summer 2019, he was a Visiting Researcher with the Department of Energy Technology, Aalborg University, Aalborg, Denmark. From 2021 to 2024, he was a Post-Doctoral Research Fellow with Monash University, Clayton, Australia. He is currently a Research Scientist with the Computer, Electrical, and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.

NABIL MOHAMMED research interests include power electronics, grid integration of renewable energy resources, microgrids, energy storage and management systems, and modeling, control, and stability of power electronic-based power systems.

Peter started his academic life at Vienna University of Technology (TU Wien). He obtained his bachelor degree in Media Computer Science in 2003. After that, he worked as a teacher assistant for one year. In 2005, he received his master degree in Computer Graphics and Digital Image Processing. During his preparation for the master degree, he worked part-time as a Computer Science teacher at a School for Social Services.

He was a Research Assistant from 2005 to 2009 at TU Wien. In that period, he was also preparing doing his PhD in Computer Science. He received his doctoral degree in 2009. Before joining KAUST, Peter was a Postdoctoral Fellow at the Vienna University of Technology until 2011.

Peter is interested in Scientific Visualization, particularly in advanced methods of fluid flow visualization, Computer Graphics in general, Augmented and Virtual Reality, as well as large language models (LLMs) and their applications in interactive systems.

Rafayel Teymurazyan obtained his PhD in Mathematics from the University of Lisbon (Portugal) in 2013. After postdoc and research positions at the Federal University of Ceará (Brazil), the University of Texas at Austin (USA) and the University of Coimbra (Portugal), he joined KAUST in May of 2023. He works on regularity theory for nonlinear PDEs and the mathematical analysis of free boundary problems.

Rafayel Teymurazyan works on nonlinear  partial differential equations (PDEs) and free boundary problems. The term free boundary problem (FBP) refers to a PDE to be solved both for an unknown function and for an unknown domain. FBPs arise in range of mathematical models that are used to describe a physical or biological phenomenon (for example, ice melting into water, population dynamics), or an economical or financial occurrence (American options, stock markets).

Ricardo has a Chemical Engineering Diploma (5 years degree) and a PhD in Chemical Engineering in the area of Process Systems Engineering. He obtained his Diploma and PhD at the Faculty of Engineering from the University of Porto (FEUP), Portugal, under the supervision of Professor Romualdo Salcedo and Professor Domingos Barbosa.

After completing his PhD studies, Ricardo became a post-doctoral fellow in the Department of Chemical Engineering at the Carnegie Mellon University (CMU), USA, where he worked with Professor Ignacio Grossmann. During his stay at CMU, he collaborated with PPG Industries in several projects. He was an invited researcher in the Glass Process Engineering/Process Control group located in the PPG Glass Business and Discovery Center, where he worked with Dr Yu Jiao.

In 2011, Ricardo was awarded a Marie Curie Fellowship to pursue research on sustainable power systems at the National Laboratory of Energy and Geology in Portugal.

Ricardo joined KAUST in 2014, where he has been involved in problems concerning chemical processes flexibility, optimization of isolated and hybrid energy systems, the motion planning of autonomous underwater vehicles, optimal operation of virtual power plants, optimization under uncertainty, robust optimization, and in a project with the Ministry of Health of Saudi Arabia.

My research interests lie at the intersection of optimization, modeling, uncertainty, and computer science. I am interested in the modeling and optimization of complex problems related to energy systems, chemical engineering, and oil industries. Target applications include integration, planning and scheduling of renewable energy systems, process synthesis, planning and scheduling of chemical engineering systems, and path planning of autonomous under-water vehicles. Development of mathematical programming methodologies, namely combinatorial optimization models, continuous optimization models, deterministic global optimization solution approaches, optimization under uncertainty models, and decomposition algorithms to solve large-scale problems.

Dr. Sameh Abdulah is an HPC senior research scientist specializing in high-performance computing (HPC), and large-scale data analytics. He is a Senior Research Scientist at the Computer, Electrical and Mathematical Sciences and Engineering Division at KAUST. His work focuses on developing scalable algorithms and efficient software frameworks to address complex computational challenges across diverse scientific and engineering domains, including spatial statistics.

He serves as a key link between three major research groups within the extreme computing research at KAUST: the Hierarchical Computations on Manycore Architectures (HiCMA) group led by Professor David Keyes, the Spatio-Temporal Statistics & Data Science (STSDS) group led by Professor Marc Genton, and the Environmental Statistics (ES) group led by Professor Ying Sun. His primary role is to bridge advanced parallel linear algebra (LA) innovations with high-performance computing (HPC) in the spatial statistics field in the context of climate and weather applications.

Dr. Abdulah was honored with the ACM Gordon Bell Prize for Climate Modelling in November 2024. His team's pioneering work in climate simulation set new benchmarks in computational efficiency and resolution, transforming how climate data is modeled and analyzed. He was also part of the KAUST team nominated for the ACM Gordon Bell Prize in the general track for spatial data modeling/prediction in 2022.

He has significantly contributed to scalable matrix computations, particularly in designing numerical libraries that leverage modern hardware architectures. His expertise includes mixed-precision matrix computations, geostatistical modeling, and prediction. He has also developed cutting-edge methodologies for accelerating data-intensive simulations, enabling transformative weather/climate modeling advancements.

As a passionate advocate for open-source software, Dr. Abdulah is actively involved in collaborative research and software development, sharing tools and libraries that empower researchers globally. His work is driven by a commitment to innovation and interdisciplinary collaboration, harnessing the power of HPC to tackle some of the most pressing challenges in computational science.

Adding the HPC capabilities to existing science is a big challenge. Statistics has a huge number of tools and methods that can be more attractive if they scaled up. Dr Abdulah is doing this by working through two different groups to transfer knowledge and experience between two different views of the same problem. In other words, he is moving the traditional statistical tools and methods to the HPC era.

Silvio Giancola is a Research Scientist at KAUST, where he leads initiatives at the intersection of computer vision, artificial intelligence, and sports. He co-founded the SoccerNet project, a large-scale benchmark for soccer video understanding now adopted by hundreds of research groups worldwide. His research spans video understanding, 3D perception, and sports analytics, with applications ranging from athlete biomechanics to broadcast automation. Dr. Giancola has published more than 25 peer-reviewed papers, co-authored a book on 3D camera technologies, and organized workshops and challenges at premier conferences such as CVPR. At KAUST, he plays a central role in the newly established FIFA Research Institute, collaborating with FIFA and industry partners to translate cutting-edge AI research into real-world football solutions.

Silvio is mainly interested in Computer Vision, Deep learning, Sports, and Robotics.

​Stefano Zampini earned his PhD in Computational Mathematics from the University of Milan in 2010. His work mainly focused on non-overlapping domain decomposition preconditioners of the dual-primal type (namely, BDDC and FETI-DP type methods) for solving large and sparse linear systems arising from finite elements discretizations and IsoGeometric Analysis. Before joining KAUST in 2014, he worked for the Italian Supercomputing center CINECA, with a specific interest in optimization and parallelization of oil and gas applications, and for the Italian weather forecast agency.

While a theorist by training, he spent his working career in the design and implementation of algorithms for the simulation of physical applications including electromechanical cardiology, computational fluid dynamics, electromagnetics, geophysics, chemistry, isogeometric analysis, fractional diffusion, and PDE constrained optimization. His contributions to the field of Domain Decomposition have been recognized by two plenary talk invitations at the sesquiannual International Conference on Domain Decomposition Methods.

Dr Zampini research interests revolve around the solution of large scale nonlinear-equations such as those arising in the solution of partial differential equations and optimization problems, He is one of the principal developers of the Portable and Extensible Toolkit for Scientific Computing (PETSc), which is a R&D 100 award-winning massively parallel framework for the solution of large scale nonlinear system of equations. His contributions to the open-source software community for Computational Science and Engineering extends to widely adopted frameworks in the US Department of Energy ecosystem for the numerical solution of partial differential equations, namely the MFEM and deal.II libraries for finite-element based simulations. He is also a member of the HPC technical committee of the CFD software package OpenFOAM.

• Digital Signal Processing & algorithms.
• Low sampling & low complexity systems.
• Image Processing.
• Ultra-wideband (UWB) sensing and communications.
• UWB channel impulse response estimation.
• Acoustic sensing and communications.
• Sonars and radars.
• Movement detection and tracking using RF and acoustic waves.
• Respiration detection and tracking.
• Robust estimation and regularization.
• Experimentation and testing.

Tien Khee Ng (Fellow of IET and InstP) is a principal research scientist and a laboratory-operation-manager of the Photonics Laboratory at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He co-established the Photonics Laboratory (2009-) and KACST Technology Innovation Center on Solid-State Lighting at KAUST (2013-2021), and currently focuses on molecular-beam-epitaxy-grown group-III-oxides photonics/electronics and quantum-devices. He was a research fellow and a member-of-technical-staff at Nanyang Technological University and Tinggi Technologies (Singapore), respectively, developing group-III-arsenide, -phosphide, -antimonide and - nitride semiconductor nanostructures and optoelectronic devices. He was an associate editor of digital Encyclopedia of Applied Physics (July 2018–June 2023).

Semiconductor photonics, Multistack membrane semiconductor; Quantum photonic integrated circuits; Optoelectronic devices for optical wireless communication