Profiles

Ahmed M. Eltawil is a professor of the Electrical and Computer Engineering Program at KAUST. He joined the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division in 2019. At KAUST, he founded and directs the Communication and Computing Systems Laboratory (CCSL). Previously, he was a faculty member in the Electrical Engineering and Computer Science Department at the University of California, Irvine (UCI), U.S., from 2005 to 2019.

His research at the CCSL at KAUST focuses on efficient architectures for computing and communications systems, with an emphasis on wireless systems. This research spans several application domains, including low-power mobile systems, machine learning platforms, sensor networks, body area networks, and critical infrastructure networks.

An active participant in the academic community, Eltawil has served on the technical program and steering committees for numerous workshops, symposia and conferences focused on low-power computing and wireless communication system design. He is a recipient of several prestigious awards and grants, including the NSF CAREER grant for his research in low-power computing and communication systems.

He is a Senior Member, Distinguished Lecturer (2023/24) of the IEEE, and a Senior Member of the National Academy of Inventors. In 2021, he was recognized as "Innovator of the Year" by the Henry Samueli School of Engineering at UCI and received two US Congressional Recognition Awards for his pioneering work in wireless systems. Committed to a collaborative, multidisciplinary approach, Professor Eltawil is passionate about translational research, aiming to move practical innovations from the lab to societal applications.

Professor Eltawil’s current research focuses on efficient architectures for computing and communications systems and wireless networks, encompassing low-power mobile systems, sensor networks, body-area networks, cyber-physical systems and critical infrastructure networks.

His research examines the larger context of smart and connected systems where devices seamlessly integrate into our daily lives. His approach to research combines rigorous analysis with a robust experimental background that leverages insights obtained through simulations and corroborated by experiments. By finding innovative solutions to research problems, he aspires to offer practical approaches that can be readily adopted, resulting in significant societal benefits.

Atif Shamim received his M.S. and Ph.D. degrees in electrical engineering from Carleton University, Canada, in 2004 and 2009, respectively. He was an NSERC Alexander Graham Bell Graduate Scholar at Carleton University from 2007 to 2009 and an NSERC Postdoctoral Fellow from 2009 to 2010 at the Royal Military College Canada and KAUST.

In 2006, he joined the VTT Micro-Modules Research Center (Oulu, Finland) as an invited researcher. In August 2010, he joined the Electrical and Computer Engineering (ECE) Program at KAUST, where he is currently a full professor, chair of the ECE Program, and principal investigator of the IMPACTS Lab.

His research work has earned numerous awards, including Best Paper Awards at IEEE ICMAC 2021, IEEE IMS 2016, IEEE MECAP 2016, and IEEE EuWiT 2008. He also received first prize in the IEEE IMS 2019 3MT Competition, the IEEE AP-S Design Competition 2022, and second prize in the IEEE IMS Design Competition 2024. Additionally, he was recognized with finalist or honorable mention awards in several prestigious competitions, including the IEEE AP-S Design Competition 2020 and the R.W.P. King Prize for journal papers in IEEE TAP 2017 and 2020. He has been selected as a Distinguished Lecturer for IEEE AP-S (2022–2024).

In addition to his research accolades, Professor Shamim’s work has been recognized for its broader impact across innovation, industry and entrepreneurship. He received the King’s Prize for the Best Innovation of the Year (2018) for his work on sensors for the oil industry. In 2008, he was honored with the Ottawa Centre of Research Innovation (OCRI) Researcher of the Year Award in Canada. His innovative Wireless Dosimeter earned the ITAC SMC Award at the Canadian Microelectronics Corporation TEXPO in 2007. He has also won several business-related honors, including first prize in Canada’s National Business Plan Competition and the OCRI Entrepreneur of the Year Award in 2010.

Professor Shamim has been actively involved in contributing to the IEEE community through various technical, editorial, and leadership roles. He is a Fellow of IEEE and founded the first IEEE AP/MTT chapter in Saudi Arabia (2013). He served on the editorial board of IEEE Transactions on Antennas and Propagation (2013–2019), as a Guest Editor for an IEEE AWPL Special Issue (2019), and as an Associate Editor for the IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology (2020–2024). He has also participated in several IEEE Technical Committees, including those on Antenna Measurements (AP-S), Microwave Controls (MTT-S 13), and Additive Manufacturing (CRFID). 

He currently chairs the IEEE AP-S Technical Committee on Wireless Communication and serves as Vice Chair of the IEEE AP-S MGA Committee.

Professor Shamim's research focuses on innovative antenna designs and their integration strategies with circuits and sensors for flexible and wearable wireless sensing systems through a combination of CMOS and additive manufacturing technologies. Shamim is particularly interested in developing wearable wireless sensor systems to measure physiological parameters in real time.

Specific research interests include:

• Antenna-on-Chip (AoC) design, integration and efficiency enhancement strategies
• Reconfigurable Intelligent Surfaces (RIS)
  Additive manufacturing (Inkjet, Screen, and 3D printing)
• Wearable and disposable wireless sensors realized through printing technologies
• Mechanically flexible RF electronics and sensing systems
• Reconfigurable microwave components (magnetically controlled)
• Phase Change Materials (PCM) for low cost RF and mm-Wave switching applications
• Terahertz plasmonics antennas and their characterization techniques
   

Daniele Boffi is a professor in the Applied Mathematics and Computational Science Program at KAUST. Before joining KAUST, he spent 14 years as a full professor in the Department of Mathematics at the University of Pavia (UnIPV), Italy.

Boffi received his Ph.D. in Mathematics from UnIPV in 1996 and his M.S. in Mathematics from the same institution in 1990. During his time in Italy, he served as the director of Pavia's Higher Education School and was a member of several academic committees, including the University's Academic Senate and Evaluation Committee.

Boffi's research focuses on the numerical approximation of partial differential equations, spanning various aspects of mathematical modeling and scientific computing. He has made significant contributions to the modeling and simulation of fluid-structure interaction problems and the study of the numerical approximation of eigenvalue problems arising from partial differential equations.

At KAUST, Boffi leads the Numerical Methods for PDEs (NumPDE) research group, which provides a platform for the mathematical analysis and numerical validation of numerical schemes.

Professor Boffi's research is primarily devoted to the numerical approximation of partial differential equations, encompassing various aspects of mathematical modeling and scientific computing.

In particular, he has made significant contributions to the modeling and simulation of fluid-structure interaction problems and the study of the numerical approximation of eigenvalue problems arising from partial differential equations.

He leads the Numerical Methods for PDEs (NumPDE) research group at KAUST, which provides a rigorous platform for the mathematical analysis and numerical validation of numerical schemes.

Diogo Gomes is a professor of Applied Mathematics and Computational Science (AMCS) at KAUST.

He received his Ph.D. in Mathematics in 2000 from the University of California at Berkeley, U.S. Gomes completed his postdoctoral studies at the Institute for Advanced Study, Princeton University, U.S., in 2000, and at the University of Texas at Austin, U.S., in 2001. In 2006, he earned a Habilitation in Mathematics from the Technical University of Lisbon, Portugal.

In recognition of his academic excellence, Gomes was awarded UC Berkeley’s Morrey Prize in 1997. He has served as Editor of Minimax Theory and its Applications and the Journal of Dynamics and Games and Dynamic Games and Applications.

Professor Gomes' work focuses on partial differential equations (PDEs), namely viscosity solutions to elliptic, parabolic and Hamilton-Jacobi equations.

His research encompasses classical PDE questions—such as well-posedness, existence and uniqueness and regularity theory—and numerical methods and their applications. Gomes is particularly interested in applying mean-field game models to social sciences, economics and finance.

Professor Gianluca Setti joined KAUST in 2022 from the Politecnico di Torino, Italy, where he served as a Professor of Electronics for Signal and Data Processing in the Department of Electronics and Telecommunications (DET). He also served as the Rector’s Delegate on Research Quality Evaluation.

He received his Ph.D. in Electronic Engineering and Computer Science ('97) from the University of Bologna, Italy. From 1997 to 2017, he was an assistant, associate and full professor of Circuit Theory and Analog Electronics at the University of Ferrara, Italy. Dr. Setti is the first serving non-US Editor-in-Chief of the Proceedings of the IEEE, the flagship journal of the Institute, a role he has held since 2019. He has also held the IEEE Vice Presidency for Publication Services and Products for two terms. During this period, he ensured ethics in using bibliometric indicators for evaluating the impact of individual scientists' research. Additionally, he served on IEEE's board of directors, where he addressed the impact of open access mandates on IEEE members.

He received the 1998 Caianiello Prize for the best Italian Ph.D. thesis on neural networks. He also received the 2013 IEEE Circuits and Systems Society (CASS) Meritorious Service Award and was an IEEE CASS Distinguished Lecturer in 2004–2005 and 2015–2016. In addition to publishing circa 320 scientific articles in journals and conference proceedings, as well as four books, he has received best paper awards in three different IEEE Transactions and six best paper awards or nominations at major conferences, including the IEEE International Symposium on Circuits and Systems and the Design, Automation and Test in Europe.

The nature of Setti's research interests and approaches is multidisciplinary: they include nonlinear circuits, statistical signal processing, electromagnetic compatibility, compressive sensing, biomedical circuits and systems, power electronics, design and implementation of IoT nodes, as well as machine learning techniques for anomaly detection and predictive maintenance.

Professor Rue earned his Ph.D. in 1993 from the Norwegian University of Science and Technology. He began his academic career at the same institution in 1994 and was promoted to full professor in 1997. He has also held adjunct positions at the Norwegian Computing Center and the Arctic University of Norway. Rue is an elected member of the Norwegian Academy of Science and Letters, the Royal Norwegian Society of Science and Letters, the Norwegian Academy of Technological Sciences and the International Statistical Institute.

Upon joining KAUST in 2017, Rue established the Bayesian Computational Statistics & Modeling research group. The group develops efficient Bayesian inference schemes and tools to improve Bayesian inference and modeling using latent Gaussian models. He received the Guy Medal in Silver from the Royal Statistical Society in 2021 for his groundbreaking work in this area.

Professor Rue’s research interests lie in computational Bayesian statistics and Bayesian methodology, such as priors, sensitivity and robustness. His main body of research is built around the R-INLA project—a project aimed at providing a practical way to analyze latent Gaussian models at extreme data scales using approximate Bayesian analysis. The work also includes efforts to model Gaussian fields with stochastic partial differential equations, which are applied to spatial statistics.

Professor Hakan Bagci is a faculty member in the Electrical and Computer Engineering (ECE) program at KAUST. He specializes in computational electromagnetics, focusing on time-domain integral equations, hybrid methods, and numerical solvers for complex electromagnetic interactions, with applications in photonic, optical, and electronic systems.

Professor Hakan Bagci received his Bachelor's in Electrical and Electronics Engineering ('01) from Bilkent University, Turkey. He obtained his Master's and Ph.D. degrees in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC), U.S., in 2003 and 2007, respectively.

From 2001 to 2006, Bagci was a research assistant with the UIUC Center for Computational Electromagnetics and Electromagnetics Laboratory, U.S. From 2007 to 2009, he was a postdoctoral research fellow at the University of Michigan's Radiation Laboratory, U.S.
Bagci arrived at KAUST in August 2009 as an Assistant Professor of Electrical Engineering. He was promoted to Associate Professor in the same program six years later.

In 2021, he was elevated as an Applied Computational Electromagnetics Society (ACES) Fellow for his "exceptional achievements in computational electromagnetics, including ACES publications, and extensive service to ACES." He is a Senior Member of the International Union of Radio Science (URSI) for his research achievements in the field of computational electromagnetics.

He is an Associate Editor for IEEE Antennas and Propagation Magazine (2019 to present), Associate Editor for IEEE Journal of Multiscale and Multiphysics Computational Techniques (2018 to present), and Associate Editor for IEEE Transactions on Antennas and Propagation (2017 to present).

Professor Bagci’s research focuses on theoretical and applied aspects of the interdisciplinary field of computational electromagnetics (CEM). CEM fuses elements of electrical engineering, physics, applied mathematics and computational sciences to enable the numerical design and characterization of real-life electromagnetic, optical and photonic devices and systems.

The field of CEM complements and facilitates advances in other fields of electromagnetics, optics and photonics.

Bagci’s CEM research group is developing novel, efficient, accurate algorithms and numerical schemes for solving integral/differential forms of Maxwell equations—a set of four complicated equations that describe the world of electromagnetics.

Professor Matteo Parsani received his Master’s in Aerospace Engineering in 2006 from Politecnico di Milano, Italy, and his Ph.D. in Mechanical Engineering in 2010 from Vrije Universiteit, Belgium.

Parsani’s journey at KAUST began when he joined the University as a postdoctoral fellow in 2010. Four years later, while pursuing a postdoctoral fellowship at NASA’s Langley Research Center in the United States, he received an offer to return to KAUST as a professor.

He is now an associate professor of Applied Mathematics and Computational Science in the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division and the principal investigator of the Advanced Algorithms and Simulations Lab (AANSLab). Parsani is also affiliated with the Mechanical Engineering Program at KAUST.

His research focuses on developing self-adaptive, variable-order, robust algorithms for compressible flows and advection-reaction-diffusion, designing efficient simulation codes and deploying them on large parallel platforms.

Parsani's high-performance computational solvers and libraries are utilized to tackle complex engineering challenges in collaboration with industry partners such as Boeing, NASA’s Langley Research Center (LaRC), the McLaren F1 racing team, Airbus, E1 Series and Lucid Motors.

Professor Matteo Parsani’s research interests are related to designing and implementing novel, robust and scalable numerical methods. Specifically, unstructured grids for hyperbolic and mixed hyperbolic/parabolic partial differential equations.

A core focus of Parsani’s research is on efficient and robust algorithms for the aerodynamic and aeroacoustic design of aerospace vehicles. Additionally, he studies non-classical gas-dynamic phenomena for energy conversion systems and the investigation of biological flow in cancer treatments.

His current research examines the stability and efficiency of spatial and temporal discretizations and structure-preserving methods that can mimic results from the continuous to the discrete level. A number of application domains are currently driving his research, including computational aerodynamics, dense gas flow simulations, and computational aeroacoustics.

Dr. Gao received his B.A. in Computer Science in 2004 from Tsinghua University, China, and his Ph.D. in Computer Science in 2009 from the David R. Cheriton School of Computer Science at the University of Waterloo, Canada. Before joining KAUST, he served as a Lane Fellow at the Lane Center for Computational Biology at Carnegie Mellon University, U.S., from 2009 to 2010.

He is the Associate Editor of numerous journals, including Bioinformatics, npj Artificial Intelligence, Journal of Translational Medicine, Genomics, Proteomics & Bioinformatics, Big Data Mining and Analytics, BMC Bioinformatics, Journal of Bioinformatics and Computational Biology, Quantitative Biology, Complex & Intelligent Systems, and the International Journal of Artificial Intelligence and Robotics Research.

Gao has co-authored more than 400 research articles in bioinformatics and AI and is the lead inventor on over 60 international patents.

Professor Gao's research interest lies at the intersection between AI and biology/health. His research focuses on building novel computational models, developing principled AI techniques, and designing efficient and effective algorithms. He is particularly interested in solving key open problems in biology, biomedicine, health and wellness.

In the field of computer science, he is interested in developing machine learning theories and methodologies related to large language models, deep learning, probabilistic graphical models, kernel methods and matrix factorization. In the field of bioinformatics, he works on developing AI solutions to key open problems along the path from biological sequence analysis, to 3-D structure determination, to function annotation, to understanding and controlling molecular behaviors in complex biological networks, and to biomedicine and health care. He is a world-leading expert on developing novel AI solutions for challenges in biology, biomedicine, health and wellness, in particular AI-based drug development, large language models in biomedicine, biomedical imaging analysis, and omics-based disease detection and diagnostics.

Ahmed M. Eltawil is a professor of the Electrical and Computer Engineering Program at KAUST. He joined the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division in 2019. At KAUST, he founded and directs the Communication and Computing Systems Laboratory (CCSL). Previously, he was a faculty member in the Electrical Engineering and Computer Science Department at the University of California, Irvine (UCI), U.S., from 2005 to 2019.

His research at the CCSL at KAUST focuses on efficient architectures for computing and communications systems, with an emphasis on wireless systems. This research spans several application domains, including low-power mobile systems, machine learning platforms, sensor networks, body area networks, and critical infrastructure networks.

An active participant in the academic community, Eltawil has served on the technical program and steering committees for numerous workshops, symposia and conferences focused on low-power computing and wireless communication system design. He is a recipient of several prestigious awards and grants, including the NSF CAREER grant for his research in low-power computing and communication systems.

He is a Senior Member, Distinguished Lecturer (2023/24) of the IEEE, and a Senior Member of the National Academy of Inventors. In 2021, he was recognized as "Innovator of the Year" by the Henry Samueli School of Engineering at UCI and received two US Congressional Recognition Awards for his pioneering work in wireless systems. Committed to a collaborative, multidisciplinary approach, Professor Eltawil is passionate about translational research, aiming to move practical innovations from the lab to societal applications.

Professor Eltawil’s current research focuses on efficient architectures for computing and communications systems and wireless networks, encompassing low-power mobile systems, sensor networks, body-area networks, cyber-physical systems and critical infrastructure networks.

His research examines the larger context of smart and connected systems where devices seamlessly integrate into our daily lives. His approach to research combines rigorous analysis with a robust experimental background that leverages insights obtained through simulations and corroborated by experiments. By finding innovative solutions to research problems, he aspires to offer practical approaches that can be readily adopted, resulting in significant societal benefits.

Andrea Fratalocchi is a full professor in the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division at KAUST. He joined the University in January 2011 as an assistant professor and was promoted to associate professor in 2016. He is one of the founders of the CEMSE Division and the principal investigator of the Primalight Lab.

Before joining KAUST, Fratalocchi was a research fellow at Sapienza University of Rome under a KAUST Fellowship Award. From 2007 to 2009, he was a postdoctoral researcher at Sapienza University under a “New Talent” Award from the Enrico Fermi Research Center. He obtained a Master of Science in Electrical Engineering in 2003 and a Ph.D. in Electrical Engineering in 2007 from the University of Roma Tre, Italy.

Fratalocchi’s career is marked by numerous accolades, including the GCC Enterprise Awards for Best Electrical Engineer of the Year in 2017, the Journal of Optics Outstanding Referee Award in 2017, the Nature Exceptional Referee Award in 2015, and an entry into the Guinness World Records for developing the “Darkest Material Made by Mankind” in 2015.

In 2019, he became a Fellow of the Institute of Physics (IOP), a Senior Member of the IEEE, and a Fellow of the Optical Society of America (OSA).

Fratalocchi has authored over 200 publications, including three books and six patents. He ranks in the top 2% of optics researchers worldwide, based on the standardized citation index compiled by PLOS.

Professor Fratalocchi is dedicated to advancing the field of physics and engineering. His research approach harnesses the potential of complex physical systems, characterized by many degrees of freedom, turning them from theoretical challenges into real-world technological solutions with diverse applications.

His research embraces a nonlinear paradigm, departing from traditional "cause and effect" or linear thinking. This approach finds applications in diverse areas such as chaos theory, rare events, brain functions, natural mimicry and camouflage, swarm's cooperative dynamics and intelligence.

Using disorder as a building block, he proposes novel, low-cost, scalable technologies that outperform current systems by several orders of magnitude.

As part of his engineering research, he has developed world-record-performing nanomaterials for concentrating solar power, steam generation, desalination, solar water splitting, solar and chemical fuel production for carbon-negative technologies, artificial intelligence optical neural networks for hyperspectral imaging and sensing, and machine-learning nanomaterials for wave control and bioimaging, including early disease detection of cancer and diabetes.

Athanasios Tzavaras is a professor in KAUST's Applied Mathematics and Computational Science (AMCS) program, and principal investigator of the Applied Partial Differential Equations (AppliedPDE) research group.

Professor Tzavaras obtained a Diploma in Naval Architecture and Marine Engineering in 1981 from the National Technical University of Athens, Greece. He continued his studies in the United States, earning an M.Sc. in 1983 and a Ph.D. in Applied Mathematics in 1985 from Brown University.

He held academic positions at the University of Wisconsin-Madison from 1987 to 2005, the University of Maryland from 2005 to 2009 and the University of Crete, Greece, from 2002 to 2004 and from 2010 to 2014. Additionally, he has held visiting positions at Purdue University, U.S., Stanford University, U.S., École Polytechnique, France and the Université Marie et Pierre Curie - Paris VI, France.

Tzavaras is a fellow of the European Academy of Sciences. He is a member of the American Mathematical Society (AMS), the Society of Industrial and Applied Mathematics (SIAM) and the International Society for the Interaction of Mechanics and Mathematics. He is Associate Editor of various journals and Corresponding Editor of the SIAM Journal for Mathematical Analysis.

Link to personal website.

Professor Tzavaras' research interests include mathematical modelling, analysis and computation of fluids and materials. He investigates hyperbolic conservation laws and the structure of fluid mechanics and elasticity equations.

Among his other interests are singularity formation in solid mechanics (cavitation and shear bands), multi-scale analysis, hydrodynamic limits and practical properties of fluids, kinetic models of dilute polymeric systems and discrete lattice dynamics.

Atif Shamim received his M.S. and Ph.D. degrees in electrical engineering from Carleton University, Canada, in 2004 and 2009, respectively. He was an NSERC Alexander Graham Bell Graduate Scholar at Carleton University from 2007 to 2009 and an NSERC Postdoctoral Fellow from 2009 to 2010 at the Royal Military College Canada and KAUST.

In 2006, he joined the VTT Micro-Modules Research Center (Oulu, Finland) as an invited researcher. In August 2010, he joined the Electrical and Computer Engineering (ECE) Program at KAUST, where he is currently a full professor, chair of the ECE Program, and principal investigator of the IMPACTS Lab.

His research work has earned numerous awards, including Best Paper Awards at IEEE ICMAC 2021, IEEE IMS 2016, IEEE MECAP 2016, and IEEE EuWiT 2008. He also received first prize in the IEEE IMS 2019 3MT Competition, the IEEE AP-S Design Competition 2022, and second prize in the IEEE IMS Design Competition 2024. Additionally, he was recognized with finalist or honorable mention awards in several prestigious competitions, including the IEEE AP-S Design Competition 2020 and the R.W.P. King Prize for journal papers in IEEE TAP 2017 and 2020. He has been selected as a Distinguished Lecturer for IEEE AP-S (2022–2024).

In addition to his research accolades, Professor Shamim’s work has been recognized for its broader impact across innovation, industry and entrepreneurship. He received the King’s Prize for the Best Innovation of the Year (2018) for his work on sensors for the oil industry. In 2008, he was honored with the Ottawa Centre of Research Innovation (OCRI) Researcher of the Year Award in Canada. His innovative Wireless Dosimeter earned the ITAC SMC Award at the Canadian Microelectronics Corporation TEXPO in 2007. He has also won several business-related honors, including first prize in Canada’s National Business Plan Competition and the OCRI Entrepreneur of the Year Award in 2010.

Professor Shamim has been actively involved in contributing to the IEEE community through various technical, editorial, and leadership roles. He is a Fellow of IEEE and founded the first IEEE AP/MTT chapter in Saudi Arabia (2013). He served on the editorial board of IEEE Transactions on Antennas and Propagation (2013–2019), as a Guest Editor for an IEEE AWPL Special Issue (2019), and as an Associate Editor for the IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology (2020–2024). He has also participated in several IEEE Technical Committees, including those on Antenna Measurements (AP-S), Microwave Controls (MTT-S 13), and Additive Manufacturing (CRFID). 

He currently chairs the IEEE AP-S Technical Committee on Wireless Communication and serves as Vice Chair of the IEEE AP-S MGA Committee.

Professor Shamim's research focuses on innovative antenna designs and their integration strategies with circuits and sensors for flexible and wearable wireless sensing systems through a combination of CMOS and additive manufacturing technologies. Shamim is particularly interested in developing wearable wireless sensor systems to measure physiological parameters in real time.

Specific research interests include:

• Antenna-on-Chip (AoC) design, integration and efficiency enhancement strategies
• Reconfigurable Intelligent Surfaces (RIS)
  Additive manufacturing (Inkjet, Screen, and 3D printing)
• Wearable and disposable wireless sensors realized through printing technologies
• Mechanically flexible RF electronics and sensing systems
• Reconfigurable microwave components (magnetically controlled)
• Phase Change Materials (PCM) for low cost RF and mm-Wave switching applications
• Terahertz plasmonics antennas and their characterization techniques
   

Basem Shihada is a leading expert in computer networking and distributed systems. He is a founding professor of the Computer Science and Electrical and Computer Engineering Programs in the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division at KAUST. He earned his Ph.D. in Computer science from the University of Waterloo, Canada. In 2009, he was appointed visiting faculty in the Department of Computer Science at Stanford University. In 2012, he was elevated to the rank of Senior Member of IEEE. His current research covers energy and resource allocation in wired and wireless networks, software-defined networking, cloud/fog computing, the Internet of Things, data networks, and underwater networks.

Professor Shihada's research expertise lies in developing cutting-edge wireless systems, where he has made groundbreaking contributions across various domains, including intelligent wireless systems, wireless underwater systems, molecular communication systems and non-terrestrial systems. His notable achievements include:

• Aqua-Fi: The creation and successful demonstration of Aqua-Fi, the world's first underwater Wi-Fi, enabling high-speed internet connectivity in aquatic environments.
• Sun-Fi: The demonstration of Sun-Fi, the world's first passive internet via building glass.

Professor Bernard Ghanem is the Chair of the KAUST Center of Excellence for Generative AI (GenAI) and a leading expert in computer vision and machine learning. He is a professor of Electrical and Computer Engineering (ECE) and the principal investigator of the Image and Video Understanding Lab (IVUL).

Ghanem's research focuses on computer vision and machine learning, particularly on large-scale video understanding, 3D scene comprehension and the foundation of machine learning.

At KAUST, Professor Ghanem's work bridges academic innovation and industry needs, advancing AI technologies through interdisciplinary collaborations. As Chair of the KAUST Center of Excellence for Generative AI, he leads efforts to establish world-leading excellence in GenAI research by developing the next generation of models that are efficient, trustworthy and tailored for widespread deployment.

His work supports solutions for the Kingdom's national Research, Development, and Innovation (RDI) priorities—Health and Wellness, Sustainability and Essential Needs, Energy and Industrial Leadership, and Economies of the Future—while accelerating the adoption of GenAI through translational research and talent development in collaboration with industry partners.

Professor Ghanem earned his Ph.D. in Electrical and Computer Engineering in 2010 and his M.Sc. in 2008, both from the University of Illinois at Urbana-Champaign (UIUC), U.S. He served as a graduate research assistant at the Computer Vision and Robotics Lab (CVRL) at the Beckman Institute for Advanced Science and Technology at UIUC.

Professor Ghanem’s research interests and expertise lie in:

1. Robust, large-scale video understanding, including object tracking, activity recognition/detection, and retrieval.
2. Visual computing for automation, including 3D object detection, 3D tracking, 3D indoor and outdoor navigation, and Sim2Real transfer learning.
3. Development and analysis of foundational tools in computer vision and machine learning, including deep graph neural networks, neural network robustness and certification (Trustworthy AI), continual learning, and foundational models in vision and language.

Boon S. Ooi (FNAI, FIEEE, FAPS, FOSA, FSPIE, FInstP) is a Professor of Electrical and Computer Engineering at KAUST. He previously held faculty positions at Nanyang Technological University (Singapore) from 1996 to 2000 and Lehigh University (Pennsylvania, USA) from 2003 to 2009. From 2012 to 2020, he served as the Director of the KACST-Technology Innovation Center at KAUST.

Professor Ooi has trained more than 40 Ph.D. students and 17 postdoctoral fellows, many of whom have secured prestigious fellowships and awards from organizations like the UK Royal Academy, Marie Curie, Humboldt, IEEE, OSA, and SPIE. He holds 45 issued US patents and 21 international patents, many of which have been licensed to leading optics and photonics companies, driving commercialization success.

He has received numerous accolades, including the 2024 Sang Soo Lee Award (Optica/OSA and OSK), the 2023 Khalifa International Award (UAE), and multiple paper awards. Professor Ooi is currently serving as the Editor-in-Chief of IEEE Photonics Technology Letters and has previously held editorial roles with Optics Express and IEEE Photonics Journal.

Beyond his academic achievements, Professor Ooi is actively engaged in professional service, having served on key committees such as the IEEE Fellow Committee and the SPIE Fellow Selection Committee. He chaired the IEEE Photonics Society Distinguished Lecture Selection Committee in 2024.

Professor Ooi’s research focuses on high-speed optoelectronics, optical wireless communications, and distributed fiber optic sensors.

Charalambos Konstantinou is an Associate Professor of Electrical and Computer Engineering (ECE) and Affiliate Professor of Computer Science at KAUST. He is also the principal investigator of the Secure Next Generation Resilient Systems (SENTRY) Lab.

Professor Konstantinou received a Ph.D. in Electrical Engineering from New York University (NYU), U.S., and a Dipl. Ing. M.Eng. Degree in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece. Before joining KAUST, he was an Assistant Professor with the Center for Advanced Power Systems (CAPS) at Florida State University, U.S.

His research interests include critical infrastructure security and resilience, with a special focus on smart grid technologies, renewable energy integration and real-time simulation.

He co-chairs the IEEE Task Force on Cyber-Physical Interdependence for Power System Operation and Control and previously chaired the IEEE Task Force on Resilient and Secure Large-Scale Energy Internet Systems. He is also an associate editor of the IEEE Transactions on Industrial Informatics.

Konstantinou is a senior member of the IEEE, a member of the ACM and an ACM Distinguished Speaker (2021-2024).

Professor Konstantinou's research focuses on critical infrastructure security and resilience, with a specialization in smart grid technologies, renewable energy integration and real-time simulations. His SENTRY Lab investigates the cybersecurity and resilience of industrial control systems, critical power grid infrastructure and embedded systems.

The lab employs a "red team/blue team" approach, where researchers act as attackers ("red team") to test the defenses developed and deployed by the "blue team," who respond to the simulated intrusions.

Using this concept, SENTRY researchers design adaptive modeling methods, monitoring schemes and control algorithms to detect, prevent and mitigate the risk of cyberattacks, especially in critical grid infrastructures.

The group's research aims to create secure and resilient computing systems by employing computer security fundamentals and cyber-physical engineering applications.

Daniele Boffi is a professor in the Applied Mathematics and Computational Science Program at KAUST. Before joining KAUST, he spent 14 years as a full professor in the Department of Mathematics at the University of Pavia (UnIPV), Italy.

Boffi received his Ph.D. in Mathematics from UnIPV in 1996 and his M.S. in Mathematics from the same institution in 1990. During his time in Italy, he served as the director of Pavia's Higher Education School and was a member of several academic committees, including the University's Academic Senate and Evaluation Committee.

Boffi's research focuses on the numerical approximation of partial differential equations, spanning various aspects of mathematical modeling and scientific computing. He has made significant contributions to the modeling and simulation of fluid-structure interaction problems and the study of the numerical approximation of eigenvalue problems arising from partial differential equations.

At KAUST, Boffi leads the Numerical Methods for PDEs (NumPDE) research group, which provides a platform for the mathematical analysis and numerical validation of numerical schemes.

Professor Boffi's research is primarily devoted to the numerical approximation of partial differential equations, encompassing various aspects of mathematical modeling and scientific computing.

In particular, he has made significant contributions to the modeling and simulation of fluid-structure interaction problems and the study of the numerical approximation of eigenvalue problems arising from partial differential equations.

He leads the Numerical Methods for PDEs (NumPDE) research group at KAUST, which provides a rigorous platform for the mathematical analysis and numerical validation of numerical schemes.

Professor David Bolin joined KAUST in 2019 as an Associate Professor of Statistics and Affiliate Professor of Applied Mathematics and Computational Sciences (AMCS).

Bolin received both his Ph.D. degree in Mathematical Statistics and M.Sc. 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, Sweden, as an Assistant Professor.

In 2016, Bolin became an Associate Professor of Mathematical Statistics at the University of Gothenburg, Sweden, where a year later, he received the title of Docent in Mathematical Statistics.

Professor Bolin’s main research interests are stochastic partial differential equations (PDEs) and their applications in statistics, focusing on developing practical, computationally efficient tools for modeling non-stationary and non-Gaussian processes.

The Swedish researcher leads the Stochastic Processes and Applied Statistics (StochProc) research group at KAUST, which focuses on statistical methodology for stochastic processes and random fields based on stochastic PDEs.

This research combines methods from statistics, probability and applied mathematics in order to construct more flexible statistical models and better computational methods for statistical inference. In parallel with the theoretical research, the group works on applications in a wide range of areas, ranging from brain imaging to environmental sciences.

David Ketcheson is a Professor of Applied Mathematics and Computational Science and the principal investigator of the Numerical Mathematics Group. He received his Ph.D. and M.S. in Applied Mathematics from the University of Washington in 2009 and 2008, respectively. Ketcheson obtained B.S. degrees in Mathematics and Physics & Astronomy from Brigham Young University, U.S., in 2004.

Professor Ketcheson’s research involves the analysis and development of numerical methods for integrating ordinary and partial differential equations (PDEs), as well as the implementation of such methods in open source, accessible, high-performance software and its application to understanding the behaviour of nonlinear waves in heterogeneous materials.

David Keyes is a professor in the Applied Mathematics and Computational Sciences, Computer Science, and Mechanical Engineering programs. He served as a founding dean of the Mathematical and Computer Sciences and Engineering Division from 2009 to 2012 and as the director of the strategic initiative and ultimately the Research Center in Extreme Computing from 2013 to 2024. He is also an adjunct professor and former Fu Foundation Chair Professor of Applied Physics and Applied Mathematics at Columbia University, and a faculty affiliate of several laboratories of the U.S. Department of Energy.

Professor Keyes is Fellow of the Society for Industrial and Applied Mathematics (SIAM), the American Mathematical Society (AMS), and of the American Association for the Advancement of Science (AAAS). He is the recipient of the SIAM Prize for Distinguished Service to the Profession (2011), the Distinguished Faculty Teaching Award of Columbia University (2008), the Sidney Fernbach Award of IEEE Computer Society (2007), and the ACM Gordon Bell Prize (1999), and the Prize for Teaching Excellence in the Natural Sciences of Yale University (1991) .

Keyes graduated summa cum laude in Aerospace and Mechanical Sciences with a certificate in Engineering Physics from Princeton in 1978 and earned a doctorate in Applied Mathematics from Harvard in 1984. He was a Research Associate in Computer Science at Yale University 1984-1985, and has had decadal research appointments at the Institute for Computer Applications in Science and Engineering (ICASE), NASA-Langley Research Center, and the Institute for Scientific Computing Research (ISCR), Lawrence Livermore National Laboratory.

Keyes' research lies at the algorithmic interface between parallel computing and the numerical analysis of partial differential equations (PDEs), with a focus on scalable implicit solvers and nonlinear and linear preconditioning for large-scale applications in energy and environmental science on emerging for power-austere emerging architectures. 

Target applications demand high performance because of high resolution, high dimension, and high fidelity physical models and/or the “multi-solve” requirements of optimization, control, sensitivity analysis, inverse problems, data assimilation or uncertainty quantification. Newton-Krylov-Schwarz (NKS, 1994) and Additive Schwarz Preconditioned Inexact Newton (ASPIN, 2002) are methods he co-created and popularized. He also focuses on the discovery of data sparsity and the exploitation of hierarchy in large-scale systems involving dense covariance and kernel matrices in statistics, genomics, data science, and machine learning. 

Charters for his research are the International Exascale Software Project (IESP, 2011) and the Science-based Case for Large Scale Simulation (SCaLeS, 2001/2003) reports.

Di Wang is an assistant professor of Computer Science and the principal investigator of the KAUST Provable Responsible AI and Data Analytics (PRADA) Lab.

Before joining KAUST, he obtained his Ph.D. in Computer Science and Engineering ('20) from the State University of New York (SUNY) at Buffalo, U.S.; a M.S. in Mathematics ('15) from the University of Western Ontario, Canada; and a B.S. in Mathematics and Applied Mathematics ('14) from Shandong University, China.

Professor Wang’s research interests include machine learning (ML), security, theoretical computer science and data mining. His overall research focuses on solving issues and societal concerns arising from ML and data mining algorithms, such as privacy, fairness, robustness, transferability and transparency.

His PART team develops accurate learning algorithms that are equally private, fair, explainable and robust. These algorithms are supported by rigorous mathematical and cryptographic guarantees.

His research includes three perspectives: theory, practice and system. The theoretical component of his work provides rigorous mathematical guarantees for PART’s algorithms. The practical part develops trustworthy learning algorithms for biomedical, health care, genetic and social data, with a final focus on deploying trustworthy learning systems for healthcare and other applicable industries.

Diogo Gomes is a professor of Applied Mathematics and Computational Science (AMCS) at KAUST.

He received his Ph.D. in Mathematics in 2000 from the University of California at Berkeley, U.S. Gomes completed his postdoctoral studies at the Institute for Advanced Study, Princeton University, U.S., in 2000, and at the University of Texas at Austin, U.S., in 2001. In 2006, he earned a Habilitation in Mathematics from the Technical University of Lisbon, Portugal.

In recognition of his academic excellence, Gomes was awarded UC Berkeley’s Morrey Prize in 1997. He has served as Editor of Minimax Theory and its Applications and the Journal of Dynamics and Games and Dynamic Games and Applications.

Professor Gomes' work focuses on partial differential equations (PDEs), namely viscosity solutions to elliptic, parabolic and Hamilton-Jacobi equations.

His research encompasses classical PDE questions—such as well-posedness, existence and uniqueness and regularity theory—and numerical methods and their applications. Gomes is particularly interested in applying mean-field game models to social sciences, economics and finance.

Before founding the Computational Sciences Group (CSG) at KAUST, Professor Michels joined the Computer Science Department at Stanford University, U.S., after completing his postdoctoral studies at Caltech, U.S., and his B.Sc. ('11), M.Sc. ('13), and Ph.D. ('14) at the University of Bonn, Germany.

Since joining KAUST in 2016, he has established his group at the uppermost level of his scientific community. Since its formation, the CSG has developed numerous novel computational methods based on solid theoretical foundations.

The scientific community has recognized Professor Michels’ outstanding research within and beyond KAUST. In 2019, he was awarded a €1.25 million Artificial Intelligence Grant from the German State of North Rhine-Westphalia, Germany. Together with fellow KAUST Professors Mark Tester and Peter Wonka, he received a $1.05 million KAUST Competitive Research Grant in 2021. Moreover, in 2017, he was acknowledged by Procter & Gamble with their inaugural Faculty Award for his research contributions to the consumer goods industry.

Professor Michels is actively engaged in the Association for Computing Machinery (ACM) SIGGRAPH community; he served on the technical paper committees of SIGGRAPH 2022 and 2023, and SIGGRAPH Asia 2020 and 2021.

Michels is a member of the Association for Computing Machinery, the Institute of Electrical and Electronics Engineers, the London Mathematical Society and the AGYA project at the Berlin-Brandenburg Academy of Sciences and Humanities. He is a founding member of the German AI Award top-class jury.

As an alumnus of the German Academic Scholarship Foundation, Michels leads its KAUST partnership program. He was recently inaugurated into the Göttingen Academy of Sciences and Humanities and has been listed among the German business magazine Capital's "Top 40 below 40."

As the head of KAUST's CSG, Michels’ research activities focus on fundamental and applied aspects of computational mathematics and physics to overcome practical problems in scientific and visual computing.

At present, the group addresses a broad range of topics related to algorithmics, artificial intelligence, machine learning, computer graphics, physics-based modeling, differential equations, mathematical modeling and numerical analysis.

Eric Feron is an Electrical and Computer Engineering Program professor,  an affiliate of the Mechanical Engineering Program, and the Principal Investigator of the Aerospace and Transportation Systems (ATS) Research Group at KAUST.

His research focuses on the development of advanced control and optimization techniques for autonomous systems with applications in aerospace, robotics and transportation. At KAUST, he leads efforts in exploring innovative solutions for complex challenges in these fields, emphasizing safety, reliability and efficiency in autonomous systems' design and operation.

His academic journey began in Paris, where he earned a B.S. from École Polytechnique in 1989 and an M.S. from École Normale Supérieure in 1990. He completed his Ph.D. in Aerospace Engineering at Stanford University in 1994. Before joining KAUST in October 2021, he served as a faculty member at the Georgia Institute of Technology and the Massachusetts Institute of Technology’s Aeronautics and Astronautics Department.

Throughout his career, he has taught a wide range of courses, including cyber-physical systems, control systems, and flight mechanics, and is a strong advocate for quality online education resources.

Professor Feron has contributed significantly to both theoretical advancements and practical implementations in control systems, fostering collaborations across disciplines to drive progress in aerospace engineering.

With 31 years of experience in teaching and research, Professor Feron focuses on applying fundamental concepts of control systems, optimization, and computer science to modern aerospace engineering and robotics. His specific research interests include aerobatic control of uncrewed aerial vehicles, multi-agent operations, air traffic control systems and aerospace software system certification. He is also interested in geometric control systems and control theory in general.

Dr. Feron’s ATS research group has made significant technical contributions across a variety of fields, including aerospace engineering, automotive engineering, ocean engineering, biological engineering, electrical engineering, mechanical engineering and robotics, as well as human-machine interaction. These contributions are grounded in a strong foundation of mathematics, computer science and operations research.

Professor Francesco Orabona is a leading researcher in parameter-free online optimization. He joined KAUST from Boston University's Department of Electrical & Computer Engineering. Orabona earned his B.Sc. and M.S. in electrical engineering in 2003 from the University of Naples "Federico II", Italy, and his Ph.D. in electrical engineering in 2007 from the University of Genoa, Italy. 

Prior to joining KAUST, he held positions at several institutions including, Stony Brook University, Yahoo Research, the Toyota Technological Institute at Chicago (TTIC), the University of Milan and the Idiap Research Institute in Switzerland.

He has served as an area chair for several leading conferences, including the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), the Conference on Learning Theory (COLT) and the International Conference on Learning Representations (ICLR). Since 2022, he has been an associate editor of the IEEE Transactions on Information Theory.

Professor Orabona's research combines practical and theoretical machine learning approaches. His research interests encompass online learning, optimization and statistical learning theory.

In his current research, he is researching "parameter-free" machine learning algorithms that function effectively without the use of expensive hand-tuned parameters.

Dr. Wittum obtained his Ph.D. (Dr. rer. nat.) in 1987 from Kiel University, Germany. He then pursued further academic qualifications at the University of Heidelberg, Germany, where he received his Habilitation in 1991 and began his first professorship in numerical analysis.

His academic career continued to advance as he served as Director of the Institute for Computer Applications at the University of Stuttgart, Germany, from 1994 to 1998. Following this, he became the Director of the Simulation in Technology Center at the University of Heidelberg, Germany, a position he held from 1998 to 2008. In 2008, he transitioned to the University of Frankfurt, where he led the Gauss Center of Scientific Computing (G-CSC).

After 25 years of serving as a professor at several leading universities in Germany, he joined KAUST, where he is currently a professor in the Applied Mathematics and Computational Science program.

Wittum’s work developing robust and scalable multi-grid methods and software systems for large-scale computing has led to numerous collaborative projects with industry partners, including ABB, Boston Consulting, Commerzbank, Daimler-Benz, the GICON Group, GRS, Porsche and more. 

His contributions to science have been recognized with several prestigious awards, including the Heinz-Maier-Leibnitz Prize, the Controlled Release Society's Award and the doIT Software Award. Professor Wittum has also authored over 200 scientific publications.

Professor Wittum’s research focuses on a general approach to modelling and simulation of problems from empirical sciences, in particular using high-performance computing (HPC).

Particular areas of focus include the development of advanced numerical methods for modelling and simulation, such as fast solvers like parallel adaptive multi-grid methods, allowing for application to complex, realistic models; the development of corresponding simulation frameworks and tools; and the efficient use of top-level supercomputers.

Wittum applies his methods and tools toward problem-solving in computational fluid dynamics, environmental research, energy research, finance, neuroscience, pharmaceutical technology and beyond.

George Turkiyyah is a research professor in the Applied Mathematics and Computational Science program at KAUST.

Before joining KAUST, he was a professor at the American University of Beirut, where he also served as chair of the computer science department. Prior to joining AUB, he was an assistant professor and later an associate professor at the University of Washington in Seattle.

Turkiyyah earned a Bachelor of Engineering (B.Eng.) in civil and environmental engineering from the American University of Beirut, and both a Master of Science (M.S.) and a Doctor of Philosophy (Ph.D.) in computer-aided engineering from Carnegie Mellon University.

Turkiyyah has been involved in the development of knowledge-based AI systems that have been deployed in practice. He has also developed several widely used simulation codes for high-resolution finite element engineering applications. His work on fast methods for surgical simulation has led to a software startup and several patents.

His research has earned several awards, including the Transportation Research Board K.B. Woods Award in 2003 for best paper in design and construction, the Best Presentation Award at the ACM Solid and Physical Modeling Conference in 2007, and the Best Poster Award at the Medicine Meets Virtual Reality Conference in 2006. 

He chaired the 2003 ASCE Engineering Mechanics Conference and co-chaired the Eighth ACM Symposium on Solid Modeling and Applications (SPM) in 2003. He is a member of ACM and the Society for Industrial and Applied Mathematics (SIAM).

Professor Turkiyyah’s current research interests include hierarchically low-rank matrix algorithms and their HPC/GPU implementations to support the development of simulation models at extreme scales.

His work addresses various applications of hierarchical matrix technology, including PDE-constrained optimization, high-dimensional statistics problems, multi-dimensional fractional diffusion problems, scientific data compression and second-order methods for training neural networks.

Professor Gianluca Setti joined KAUST in 2022 from the Politecnico di Torino, Italy, where he served as a Professor of Electronics for Signal and Data Processing in the Department of Electronics and Telecommunications (DET). He also served as the Rector’s Delegate on Research Quality Evaluation.

He received his Ph.D. in Electronic Engineering and Computer Science ('97) from the University of Bologna, Italy. From 1997 to 2017, he was an assistant, associate and full professor of Circuit Theory and Analog Electronics at the University of Ferrara, Italy. Dr. Setti is the first serving non-US Editor-in-Chief of the Proceedings of the IEEE, the flagship journal of the Institute, a role he has held since 2019. He has also held the IEEE Vice Presidency for Publication Services and Products for two terms. During this period, he ensured ethics in using bibliometric indicators for evaluating the impact of individual scientists' research. Additionally, he served on IEEE's board of directors, where he addressed the impact of open access mandates on IEEE members.

He received the 1998 Caianiello Prize for the best Italian Ph.D. thesis on neural networks. He also received the 2013 IEEE Circuits and Systems Society (CASS) Meritorious Service Award and was an IEEE CASS Distinguished Lecturer in 2004–2005 and 2015–2016. In addition to publishing circa 320 scientific articles in journals and conference proceedings, as well as four books, he has received best paper awards in three different IEEE Transactions and six best paper awards or nominations at major conferences, including the IEEE International Symposium on Circuits and Systems and the Design, Automation and Test in Europe.

The nature of Setti's research interests and approaches is multidisciplinary: they include nonlinear circuits, statistical signal processing, electromagnetic compatibility, compressive sensing, biomedical circuits and systems, power electronics, design and implementation of IoT nodes, as well as machine learning techniques for anomaly detection and predictive maintenance.

Professor Rue earned his Ph.D. in 1993 from the Norwegian University of Science and Technology. He began his academic career at the same institution in 1994 and was promoted to full professor in 1997. He has also held adjunct positions at the Norwegian Computing Center and the Arctic University of Norway. Rue is an elected member of the Norwegian Academy of Science and Letters, the Royal Norwegian Society of Science and Letters, the Norwegian Academy of Technological Sciences and the International Statistical Institute.

Upon joining KAUST in 2017, Rue established the Bayesian Computational Statistics & Modeling research group. The group develops efficient Bayesian inference schemes and tools to improve Bayesian inference and modeling using latent Gaussian models. He received the Guy Medal in Silver from the Royal Statistical Society in 2021 for his groundbreaking work in this area.

Professor Rue’s research interests lie in computational Bayesian statistics and Bayesian methodology, such as priors, sensitivity and robustness. His main body of research is built around the R-INLA project—a project aimed at providing a practical way to analyze latent Gaussian models at extreme data scales using approximate Bayesian analysis. The work also includes efforts to model Gaussian fields with stochastic partial differential equations, which are applied to spatial statistics.

Professor Hakan Bagci is a faculty member in the Electrical and Computer Engineering (ECE) program at KAUST. He specializes in computational electromagnetics, focusing on time-domain integral equations, hybrid methods, and numerical solvers for complex electromagnetic interactions, with applications in photonic, optical, and electronic systems.

Professor Hakan Bagci received his Bachelor's in Electrical and Electronics Engineering ('01) from Bilkent University, Turkey. He obtained his Master's and Ph.D. degrees in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC), U.S., in 2003 and 2007, respectively.

From 2001 to 2006, Bagci was a research assistant with the UIUC Center for Computational Electromagnetics and Electromagnetics Laboratory, U.S. From 2007 to 2009, he was a postdoctoral research fellow at the University of Michigan's Radiation Laboratory, U.S.
Bagci arrived at KAUST in August 2009 as an Assistant Professor of Electrical Engineering. He was promoted to Associate Professor in the same program six years later.

In 2021, he was elevated as an Applied Computational Electromagnetics Society (ACES) Fellow for his "exceptional achievements in computational electromagnetics, including ACES publications, and extensive service to ACES." He is a Senior Member of the International Union of Radio Science (URSI) for his research achievements in the field of computational electromagnetics.

He is an Associate Editor for IEEE Antennas and Propagation Magazine (2019 to present), Associate Editor for IEEE Journal of Multiscale and Multiphysics Computational Techniques (2018 to present), and Associate Editor for IEEE Transactions on Antennas and Propagation (2017 to present).

Professor Bagci’s research focuses on theoretical and applied aspects of the interdisciplinary field of computational electromagnetics (CEM). CEM fuses elements of electrical engineering, physics, applied mathematics and computational sciences to enable the numerical design and characterization of real-life electromagnetic, optical and photonic devices and systems.

The field of CEM complements and facilitates advances in other fields of electromagnetics, optics and photonics.

Bagci’s CEM research group is developing novel, efficient, accurate algorithms and numerical schemes for solving integral/differential forms of Maxwell equations—a set of four complicated equations that describe the world of electromagnetics.

Hernando Ombao is a professor in the Statistics Program and the principal investigator of the Biostatistics Group at KAUST. His research focuses on developing time series models and novel data science methods for analyzing high-dimensional complex biological processes. He leads a group of researchers specializing in spectral and time-series analysis, functional data analysis, state-space models, and signal processing for brain signals and images. His group collaborates closely with neuroscientists to model the associations between neurophysiology, cognition and animal behavior.

Before joining KAUST, Professor Ombao was a tenured faculty member at the University of Illinois Urbana-Champaign, U.S., Brown University, U.S. and the University of California, Irvine, U.S. He earned a B.Sc. in Mathematics in 1989 from the University of the Philippines, an M.Sc. in Statistics in 1995 from the University of California, Irvine, and a Ph.D. in biostatistics in 1999 from the University of Michigan.

Ombao is an elected fellow of the American Statistical Association. He has been awarded several grants as a principal investigator by the U.S. National Science Foundation. In 2017, he received the UC Irvine School of Information Sciences Mid-Career Award for Research. He has served as a panel member of the Biostatistics Study Section at the U.S. National Institutes of Health and as an associate editor of leading statistical journals. He is co-editor of the book Handbook of Statistical Methods for Neuroimaging (CRC Press, 2016) and co-editor of a special issue of the Journal of Time Series Analysis.

At KAUST, he holds secondary appointments in the Applied Mathematics and Computational Sciences (AMCS) and the Bioengineering Programs. He also serves as chair of the Institutional Biosafety and Bioethics Committee. Ombao actively collaborates with researchers across the campus and is a co-founder of the interdisciplinary KAUST Neuro-AI Laboratory (NAIL).

Professor Ombao’s research focuses on the statistical modeling of time series data and the visualization of high-dimensional signals and images.

He has developed a coherent set of methods for modeling and inference on the dependence of complex brain signals: testing for differences in networks across patient groups, identifying biomarkers, classifying diseases based on networks and modeling associations between high-dimensional data from different domains, such as genetics, brain function and behavior.

Ivan Viola received an M.Sc. in Computer Science (Dipl.-Ing.) in 2002 and a Ph.D. in Computer Science (Dr. techn.) in 2005 from TU Wien, Austria. In 2006, he joined the University of Bergen (UiB), Norway, as a postdoctoral researcher and contributed to the establishment of a new visualization research group at UiB’s Department of Informatics.

In 2008, Viola was promoted to associate professor and, in 2011, to full professor at the University of Bergen (UiB). During this period, he also served as a scientific adviser at the Christian Michelsen Institute in Norway.

Throughout his career, he has received numerous honors and recognitions for his contributions to computing visualization, including the Austrian Computer Graphics Award in 2016, the Eurographics Dirk Bartz Prize for Visual Computing in Medicine in 2013 and three Best Paper Honorable Mention awards at the IEEE VIS conference.

Aside from serving as an area or program chair at conferences such as the IEEE Visualization Conference, EuroVis, and Eurographics, Viola has been a reviewer and IPC member for several conferences in computer graphics and visualization. He was an associate editor of the Computer Graphics Forum journal and is currently serving as an associate editor for IEEE Transactions on Visualization and Computer Graphics.

In addition to co-authoring over a hundred scientific papers, he is a member of Eurographics and the IEEE Computer Society’s Visualization and Graphics Technical Community (VGTC).

Viola’s research group seeks to develop next-generation computer graphics and technologies for visualizing life forms in all scales. Focusing on scalable approaches, the research group introduces new methods to model, construct and visualize the entire complex biological cell to atomistic detail. This technology allows people to interact, explore, study and understand life at the nanoscale.

Jian Weng is an assistant professor of computer science at KAUST. Professor Weng joined KAUST from the University of California, Los Angeles (UCLA), U.S., where he completed his Ph.D. in Computer Science in 2023, advised by Professor Tony Nowatzki. He received a Bachelor of Engineering from Shanghai Jiao Tong University, China, in 2017.

Weng’s work has been recognized with an IEEE Micro Top Picks Honorable Mention, and an IEEE/ACM International Symposium on Microarchitecture (MICRO) Best Paper Runner-Up Award. 

Professor Weng’s research interests are related to hardware/software co-designed acceleration, including, but not limited to, designing and analyzing accelerators, accelerator-associated software stacks from abstraction to compiler transformations, and design automation techniques.

Weng aspires to become a long-term leader in computer science and plans to push the boundaries of full-stack computer architectures. His objective is to simplify the design flow for mainstream programmers and to implement programmable accelerators in scenarios relevant to embedded System-on-a-Chip (SoCs).

Professor Xu is a leading figure in the development, design and analysis of fast methods for finite element discretization and large-scale equation solutions. He has made many groundbreaking contributions in these areas, including several fundamental theories and algorithms that bear his name. These include the Bramble-Pasciak-Xu (BPX) preconditioner, the Hiptmair-Xu (HX) preconditioner and the Xu-Zikatanov (XZ) identity.

Xu received his Bachelor's degree from Xiangtan University, China, in 1982, his Master's degree from Peking University, China, in 1984 and his doctoral degree from Cornell University, U.S., in 1989. He joined Pennsylvania State University (Penn State), U.S., in 1989 as Assistant Professor of Mathematics, was promoted to associate professor in 1991, and to professor in 1995.

He was named a Distinguished Professor of Mathematics in 2007, the Francis R. and Helen M. Pentz Professor of Science in 2010 and the Verne M. Willaman Professor of Mathematics in 2015 at Penn State. He was also awarded the first Feng Kang Prize for Scientific Computing in 1995 and the Humboldt Award for senior U.S. scientists in 2005. His work was featured as one of the "Top 10 breakthroughs in computational science" in a 2008 US Department of Energy report.

According to Google Scholar, Xu has published more than 240 scientific papers with more than 18,500 citations. He was a plenary speaker at the International Congress for Industrial and Applied Mathematics in 2007 and an invited speaker at the International Congress for Mathematicians in 2010.

Xu serves on the editorial boards of many influential journals in computational mathematics and co-edits numerous research monographs and conference proceedings. He has organized or served as a scientific committee member for more than 100 international conferences, workshops and summer schools.

He is a Fellow of the Society for Industrial and Applied Mathematics (SIAM), the American Mathematical Society (AMS), the American Association for the Advancement of Science (AAAS) and the European Academy of Sciences (EurASc). In 2023, he was elected to the prestigious Academia Europaea.

Dr. Xu’s research focuses on numerical methods for partial differential equations and big data, specifically finite element methods, multigrid methods and deep neural networks for their theoretical analysis, algorithmic development and practical applications.

Recently, he has devoted himself to mathematical studies of deep learning, working on topics such as the approximation theory of deep neural networks. He has also been developing convolutional neural networks and training algorithms from the multigrid viewpoint and subspace corrections method.

Jürgen Schmidhuber is the co-chair of the Center of Excellence for Generative AI (GenAI) at KAUST and a professor in the Computer Science Program within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. Before joining KAUST, he served as the Director of the Swiss AI Lab, IDSIA, and was a professor of Artificial Intelligence at the University of Lugano (USI) from 2009 to 2021.

Dr. Schmidhuber earned his Ph.D. in Computer Science from the Technical University of Munich (TUM), Germany, in 1991. He is a co-founder and chief scientist of NNAISENSE and has authored over 350 peer-reviewed papers. He is a recognized keynote speaker and adviser on AI strategies to various governments.

His pioneering work in deep learning neural networks has significantly impacted AI, with applications in speech recognition, machine translation, and personal assistants like Apple’s Siri and Amazon’s Alexa. His research group was the first to achieve superhuman performance in official computer vision contests and won a medical imaging contest in 2012.

At KAUST, Professor Schmidhuber collaborates on AI research projects, contributes to developing AI-related educational programs, and engages with public and private sector organizations in Saudi Arabia and globally.

Professor Schmidhuber is a founding leader in artificial intelligence (AI) and machine learning. At KAUST, he leads and works with many current faculty members with research interests in AI. 

He spearheads the research focus on AI applications across various fields, including health care, drug design, chemistry, materials science, speech recognition, natural language processing, automation, robotics and soft robotics.

Katerina Nik is an assistant professor of Applied Mathematics and Computational Sciences (AMCS) in the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division at KAUST. Her work focuses on partial differential equations that describe phenomena in biological growth processes, fluid dynamics, and mechanical engineering. She joined KAUST in 2024 after contributing to research at prominent European institutions.

Prior to joining KAUST, Dr. Nik worked as a principal investigator at the Austrian Academy of Sciences, supported by the APART-MINT Fellowship, which enabled her to lead innovative research in applied mathematics. Before this, she was a postdoctoral researcher at the Delft Institute of Applied Mathematics, TU Delft, where she collaborated with Professor Manuel Gnann's group. She also served as a postdoctoral researcher at the Faculty of Mathematics, University of Vienna, Austria, working with Professor Ulisse Stefanelli from 2020 to 2024.

Earlier in her career, she was a research and teaching assistant at Leibniz University Hannover (LUH), Germany, where she completed her doctorate in mathematics. Her academic contributions during this period focused on nonlinear dynamics and the modeling of complex systems.

Professor Nik works on (nonlinear) partial differential equations that describe phenomena in biological growth processes, fluid dynamics, and mechanical engineering. Additionally, she is interested in modeling with differential equations. In order to solve these problems, Nik employs both applied and pure mathematics methods. Her main research topics include:

• Nonlinear evolution equations and operator semigroups
• Free boundary problems
• Calculus of variations
• Well-posedness and qualitative properties of solutions
• Nonlinear dispersive waves
• Thin fluid film equations
• Microelectromechanical systems (MEMS)
• Biological growth processes, such as volumetric and surface growth

Kazuhiro Ohkawa is a professor of Electrical and Computer Engineering (ECE) Program and the principal investigator of the Energy Conversion Devices and Materials (ECO Devices) Laboratory at KAUST.

Before joining the University, he was a senior research member at Panasonic Ltd, a professor of Physics at the University of Bremen, Germany and a professor of Applied Physics at Tokyo University of Science, Japan.

Professor Ohkawa invented nitrogen-plasma doping for ZnSe and their blue-green lasers and LEDs. The nitrogen-plasma source is now a standard nitride molecular beam epitaxy (MBE) technology. He later became involved in the metalorganic vapor-phase epitaxy (MOVPE) growth of GaN, where he developed world-record deep-red indium gallium nitride (InGaN) LEDs based on the original MOVPE technique. His nitride MOVPE simulations have contributed to industries worldwide that produce InGaN LEDs, lasers and AlGaN electronics. Additionally, he invented nitride photocatalysts, which are instrumental in solar hydrogen production and artificial photosynthesis.

He has received numerous honors and recognitions for his contributions to optoelectronics, including being named an honorary professor (lifelong) at the University of Bremen, Germany; visiting professor at Mie University, Japan; guest professor at Xiamen University, China; and visiting professor (lifelong) at Tianjin University of Technology and Education, China. He is a fellow of the Japan Society of Applied Physics. Approximately 20 companies have sought his consulting expertise in these research areas.

His research has led to over 200 scientific publications, 28 granted US and Japanese patents and more than 70 invited talks.

Professor Ohkawa’s research at KAUST focuses on applying energy-conversion phenomena towards a more sustainable future. The highly regarded researcher’s contributions to applied physics and optoelectronics have resulted in his technologies being adopted by many companies and institutions worldwide.

Three notable contributions include the first doping technologies for II-VI compounds to realize n- and p-types. Notably, the nitrogen plasma source for the p-type has become the standard technology for molecular-beam epitaxy growth of nitride semiconductors. The second is MOCVD technology for nitride semiconductors. The technology has developed InGaN-based RGB full-color LEDs and made it possible to study MOCVD reactors scientifically. The third is the invention of a nitride photocatalyst for water splitting and artificial photosynthesis.

Ohkawa is also the principal investigator of the ECO Devices Laboratory. The lab’s research topics are not only monolithic RGB micro-LEDs but also applications of those micro-LEDs for high-speed visible light communications (so-called "Li-Fi") and vertical-cavity surface-emitting lasers (VCSELs). RGB VCSELs will enable ultimate laser-based head-mounted displays.

Professor Salama received his B.S. (Hons.) degree from Cairo University, Egypt, in 1997. He obtained his M.S. and Ph.D. degrees in electrical engineering from Stanford University, U.S., in 2000 and 2005, respectively.

The principal investigator of the KAUST Sensors Lab, Salama joined the University in 2009. From 2009 to 2011, he served as the founding program chair for Electrical Engineering at KAUST. Before joining KAUST, he worked as an assistant professor at Rensselaer Polytechnic Institute, U.S., from 2005 to 2009.

Dr. Salama—a senior member of the Institute of Electrical and Electronics Engineers (IEEE)—has authored 360 articles and holds 50 patents on low-power mixed-signal circuits for intelligent, fully integrated sensors and nonlinear electronics, particularly memristor devices.

His work on complementary metal-oxide semiconductor (CMOS) sensors for molecular detection has been funded by the National Institutes of Health (NIH) and the Defense Advanced Research Projects Agency (DARPA). He is also the co-founder of Ultrawave Labs, a biomedical imaging company.

Salama received the Stanford-Berkeley Innovators Challenge Award in Biological Science.

Professor Salama’s research interests cover various interdisciplinary aspects of electronic circuit design and semiconductor fabrication. He is actively engaged in developing devices, circuits, systems and algorithms to enable inexpensive analytical platforms for a variety of industrial, environmental and biomedical applications.

Salama’s most recent research has focused on developing neuromorphic circuits for brain emulation.

Marc Dacier is a professor of Computer Science at KAUST. He is the principal investigator of the Security Research Bearing Experimental Results (SeRBER) Group. He previously served as a full professor and head of the Digital Security Department at EURECOM.

Dr. Dacier holds a Ph.D. in computer science (European Doctorate) from the Institut National Polytechnique de Toulouse, France, awarded in 1994. He has received numerous scientific awards and has served on over 120 security and dependability conference program committees.

Dacier has had a distinguished career in both academia and industry, working with several notable companies and institutions. His experience includes consulting for France Telecom and roles at IBM Research, Symantec Research Labs and the Qatar Computing Research Institute (QCRI).

At IBM, Dacier was the director of the IBM Global Security Analysis Laboratory, where his group produced the first market product for intrusion detection alert correlation. During his time at Symantec, his team developed an open platform called Worldwide Intelligent Network Environment (WINE) to share operational security data with researchers worldwide, promoting the reproducibility of security experiments. While at QCRI, he served as the founding director of the institute's cybersecurity research group.

He has served on over 120 program committees for major security and dependability conferences and has been a member of the editorial board of several top-tier peer-reviewed technical journals. In 1998, he founded the Research in Attacks, Intrusions and Defenses (RAID) conference (formerly known as Recent Advances in Intrusion Detection), which is ranked as a "Class A" conference by the Computing Research and Education Association of Australasia (CORE).

The internationally recognized expert in cybersecurity, who joined KAUST in 2021, focuses his research on intrusion detection, intrusion tolerance, network security, cybersecurity, threat intelligence and fraud detection.

At KAUST, Professor Dacier and his SeRBER group address network security issues related to the detection of middleboxes—devices that can serve a legitimate purpose in the connection between a client and a server but can also be misused by attackers to commit man-in-the-middle attacks. Another active area of research involves the security of online gaming (e-games, e-sports) and, more broadly, the metaverse. Additionally, they focus on the IoT ecosystem and operational technology (OT) networks, which are of particular interest to the oil and water industries.

Al-Khawarizmi Distinguished Professor of the KAUST Statistics Program, Marc G. Genton, is a specialist in spatial and spatio-temporal statistics with environmental applications. His work has revolutionized environmental data science, addressing large-scale problems involving spatial and temporal datasets. To emulate climate model outputs of more than one billion temperature data points, he developed 3-D space-time stochastic generators using spectral methods and fast Fourier transforms.

Genton is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, the American Association for the Advancement of Science, and an elected member of the International Statistical Institute (ISI).

In 2010, he received the El-Shaarawi Award for Excellence from the International Environmetrics Society (TIES) and the Distinguished Achievement Award from the Section on Statistics and the Environment (ENVR) of the American Statistical Association (ASA). In 2017, he was honored with the Wilcoxon Award for Best Applications Paper in Technometrics. He received an ISI Service Award in 2019 and the Georges Matheron Lectureship Award in 2020 from the International Association for Mathematical Geosciences (IAMG).

He led a Gordon Bell Prize finalist team with the ExaGeoStat software at Supercomputing 2022. In 2023, he was awarded the Royal Statistical Society’s (RSS) Barnett Award for his outstanding contributions to environmental statistics. He also received the prestigious 2024 Don Owen Award from the San Antonio Chapter of the American Statistical Association and led a Gordon Bell Prize finalist team in Climate Modeling for the Exascale Climate Emulator at SC24.

In addition to authoring over 300 publications, Genton has edited a book on skew-elliptical distributions and their applications. He has given more than 400 presentations at conferences and universities worldwide.

Genton received his Ph.D. in statistics in 1996 from the Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland. He also holds an M.S. degree in applied mathematics teaching, earned in 1994 from EPFL.

Before joining KAUST, he held prominent faculty positions at the Massachusetts Institute of Technology (MIT), North Carolina State University, the University of Geneva and Texas A&M University.

Professor Genton’s research centers around spatial and spatio-temporal statistics, including the statistical analysis, visualization, modeling, prediction and uncertainty quantification of spatio-temporal data. A wide range of applications can be found in environmental and climate science, renewable energies, geophysics and marine science.

Currently, he is developing high-performance computing tools for spatial statistics and expanding the capabilities of ExaGeoStat, the software developed by his Spatio-Temporal Statistics and Data Science (STSDS) research group and the Extreme Computing Research Center (ECRC).

An in-depth, five-year study of wind energy potential in Saudi Arabia, led by Genton, culminated in a comprehensive plan for developing the Kingdom's future wind energy strategy. With the help of apps and 3-D glasses, he has also demonstrated how virtual reality can help visualize environmental data on smartphones.

Marco Canini is an associate professor in the Computer Science program at KAUST. He obtained his Ph.D. in computer science and engineering in 2009 from the University of Genoa, Italy, after spending the last year of his degree as a visiting student at the University of Cambridge, U.K.

He holds a Laurea Degree with Honors in Computer Science and Engineering from the University of Genoa. He was a postdoctoral researcher at the École polytechnique fédérale de Lausanne (EPFL), Switzerland, from 2009 to 2012. He then worked as a senior research scientist at Deutsche Telekom's Innovation Labs and the Technical University of Berlin, Germany, for one year.

Before joining KAUST, Canini was an assistant professor of computer science at the Université catholique de Louvain, Belgium. He has also held industry positions with Intel, Microsoft, and Google.

Professor Canini‘s research interests center on the principled construction and operation of large-scale networked computer systems; in particular, the development of Software-Defined Advanced Networked and Distributed Systems (SANDS).

His research spans a number of areas in computer systems, including distributed systems, large-scale/cloud computing and computer networking with emphasis on programmable networks.

Canini’s current work focuses on improving networked systems design, implementation and operation along several vital properties such as reliability, performance, security and energy efficiency.

A founding member of KAUST, Hadwiger has published numerous scientific papers and books, including "Real-Time Volume Graphics." He has been an Assistant Professor of Computer Science from 2009 to 2014, an Associate Professor of Computer Science from 2014 to 2021, and a Full Professor of Computer Science since 2021.

Professor Markus Hadwiger’s research interests are in scientific visualization and visual computing.

Hadwiger’s investigations span a wide range of topics, including the visualization of extreme-scale data, volume visualization, flow visualization, differential geometry and mathematical physics in visualization, medical visualization, large-scale image and volume processing, multi-resolution and out-of-core techniques, domain-specific languages for visualization, interactive segmentation and feature identification and GPU algorithms and architecture.

Professor Matteo Parsani received his Master’s in Aerospace Engineering in 2006 from Politecnico di Milano, Italy, and his Ph.D. in Mechanical Engineering in 2010 from Vrije Universiteit, Belgium.

Parsani’s journey at KAUST began when he joined the University as a postdoctoral fellow in 2010. Four years later, while pursuing a postdoctoral fellowship at NASA’s Langley Research Center in the United States, he received an offer to return to KAUST as a professor.

He is now an associate professor of Applied Mathematics and Computational Science in the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division and the principal investigator of the Advanced Algorithms and Simulations Lab (AANSLab). Parsani is also affiliated with the Mechanical Engineering Program at KAUST.

His research focuses on developing self-adaptive, variable-order, robust algorithms for compressible flows and advection-reaction-diffusion, designing efficient simulation codes and deploying them on large parallel platforms.

Parsani's high-performance computational solvers and libraries are utilized to tackle complex engineering challenges in collaboration with industry partners such as Boeing, NASA’s Langley Research Center (LaRC), the McLaren F1 racing team, Airbus, E1 Series and Lucid Motors.

Professor Matteo Parsani’s research interests are related to designing and implementing novel, robust and scalable numerical methods. Specifically, unstructured grids for hyperbolic and mixed hyperbolic/parabolic partial differential equations.

A core focus of Parsani’s research is on efficient and robust algorithms for the aerodynamic and aeroacoustic design of aerospace vehicles. Additionally, he studies non-classical gas-dynamic phenomena for energy conversion systems and the investigation of biological flow in cancer treatments.

His current research examines the stability and efficiency of spatial and temporal discretizations and structure-preserving methods that can mimic results from the continuous to the discrete level. A number of application domains are currently driving his research, including computational aerodynamics, dense gas flow simulations, and computational aeroacoustics.

Professor Maurizio Filippone received his Master’s in Physics and a Ph.D. in Computer Science from the University of Genova, Italy, in 2004 and 2008, respectively. During his Ph.D. studies in 2007, Filippone spent a year as a research scholar at George Mason University, U.S.

From 2008 to 2011, he was a research associate at the University of Sheffield, U.K. (2008 to 2009), the University of Glasgow, U.K. (2010), and University College London, U.K. (2011). In 2011, Filippone took up a lecturer position at the University of Glasgow, which he left in 2015 to join EURECOM, France, as an associate professor.

In 2024, Filippone joined the Statistics program at KAUST as an associate professor.

Professor Filippone’s primary focus is Bayesian statistics, which enables sound decision-making through uncertainty quantification in model parameters and predictions; his main interests are in models based on deep learning and Gaussian processes.

Filippone is interested in the foundations of Bayesian statistics and computational aspects related to its use in practice. More specifically, he is developing approximations that enable recover tractability while being principled, practical and scalable.

He is also interested in applications in life and environmental sciences where uncertainty matters.

Professor Miguel Urbano, who joined KAUST in 2022, received his Ph.D. in Mathematical Analysis in 1999 from the University of Lisbon, Portugal. Following a postdoctoral position at Northwestern University in the United States, he became an assistant professor at the University of Coimbra (UC), Portugal. He was promoted to associate professor with tenure in 2004 at UC and awarded a habilitation in mathematics in 2005 before becoming a full professor in 2009.

Professor Urbano is the author of The Method of Intrinsic Scaling, published in the Lecture Notes in Mathematics series, and over 70 scientific papers on nonlinear partial differential equations (PDEs). He has served on panels evaluating grants and research projects for the European Union, the European Research Council, the Academy of Finland, the Latvian Council of Science, the Serrapilheira Institute of Brazil and the Portuguese Science Foundation.

Urbano served on Portugal's National Council for Science and Technology from 2012 to 2015, won the José Anastácio da Cunha Prize from the Portuguese Mathematical Society in 2002, and was an associate editor for Nonlinear Analysis from 2013 to 2021. He is a corresponding academician of the Lisbon Academy of Sciences (elected in January 2021) and has been the editor-in-chief of Portugaliae Mathematica since January 2022.

Professor Miguel Urbano is an expert on free boundary problems and regularity theory for nonlinear PDEs, particularly on the method of intrinsic scaling for singular or degenerate-type equations.

He has made several contributions leading to a better understanding of the local behaviour of weak solutions, e.g., the derivation of a quantitative modulus of continuity for weak solutions of the two-phase Stefan problem, which models a phase transition at a constant temperature or the proof of a long-standing conjecture on the optimal regularity for solutions of the p-Poisson equation in the plane.

Mikhail Moshkov is a professor of Applied Mathematics and Computational Science (AMCS) and an affiliated professor of Computer Science (CS) at KAUST. He is also the principal investigator of the Extensions of Dynamic Programming, Machine Learning, Discrete Optimization (TREES) research group.

Professor Moshkov holds an M.S. summa cum laude in 1977 from the University of Nizhni Novgorod, Russia. He obtained his Ph.D. in 1983 from the University of Saratov, Russia, and a Doctor of Science in 1999 from Moscow State University, Russia.

Before joining KAUST, he held professorships at the University of Nizhni Novgorod, Russia, and the University of Silesia, Poland.

Moshkov received the State Scientific Stipend in Mathematics for Outstanding Scientists from April 2000 to March 2003, awarded by the Presidium of the Russian Academy of Sciences. Additionally, he received the First Degree Research Prize, awarded by the rector of the University of Silesia, Poland, in 2006.

Professor Moshkov's research interests include: (i) The study of time complexity of algorithms in computational models such as decision trees, decision rule systems and acyclic programs with applications to combinatorial optimization, fault diagnosis, pattern recognition, machine learning, data mining, and analysis of Bayesian networks. (ii) The analysis and design of classifiers based on decision trees, reducts, decision rule systems, inhibitory rule systems, and lazy learning algorithms. (iii) Extensions of dynamic programming for sequential optimization relative to different cost functions and for study of relationships between two cost functions with applications to combinatorial optimization and data mining.

Mohamed Elhoseiny is an associate professor in the Computer Science Program at KAUST and the principal investigator of the KAUST Vision-CAIR Research Group. He joined the CEMSE Division at KAUST in 2019, bringing extensive experience from roles including a visiting faculty position at Baidu Research and a postdoctoral research stint at Facebook AI Research from 2016 to 2019. He also held research positions at Adobe Research from 2015 to 2016 and at SRI International in 2014.

Elhoseiny earned his Ph.D. in 2016 from Rutgers University, Canada, and his B.Sc. and M.Sc. in Computer Systems from Ain Shams University, Egypt, in 2006 and 2010, respectively.

His work has received numerous recognition, including the Best Paper Award at the 2018 European Conference on Computer Vision (ECCV) Workshop on Fashion, Art, and Design for his research "DesIGN: Design Inspiration from Generative Networks." He also received the Doctoral Consortium Award at the 2016 Conference on Computer Vision and Pattern Recognition (CVPR) and an NSF Fellowship for his "Write-a-Classifier Project" in 2014. His research on creative art generation has been featured in New Scientist Magazine and MIT Technology Review, which also highlighted his work on lifelong learning.

Professor Elhoseiny’s contributions extend to zero-shot learning, which was featured at the United Nations, and his creative AI work was highlighted in HBO’s Silicon Valley. He has served as an area chair at CVPR 2021 and the International Conference on Computer Vision (ICCV) 2021, and has organized workshops at ICCV in 2015, 2017, and 2019, and at CVPR in 2021.

He has been involved in several pioneering works in affective AI art creation and has authored or co-authored numerous award-winning papers.

Elhoseiny’s primary research interests are in computer vision—the intersection between natural language and vision and computational creativity—particularly efficient multimodal learning with limited data and vision and language. He is also interested in affective AI, especially understanding and generating novel visual content, such as art and fashion.

Nazek El-Atab is an assistant professor of Electrical and Computer Engineering (ECE) and the principal investigator of the Smart, Advanced Memory Devices and Applications (SAMA) Lab. El-Atab joined the University in October 2017, having obtained her B.Sc. in computer and communications engineering in 2012 from Hariri Canadian University, Lebanon, and her M.Sc. in microsystems engineering in 2014 and Ph.D. in interdisciplinary engineering in 2017 from the Masdar Institute of Science and Technology, UAE, under a cooperative program with MIT, and funded by the US Office of Naval Research.
 
At KAUST, El-Atab has worked on several high-impact research projects focusing on designing and fabricating futuristic electronics. Her current research interest focuses on the design and development of smart multifunctional devices including in-memory sensing and computing, 4D printing of actuators with self-sensing capability, among others.
 
El-Atab is a Senior IEEE Member and currently serves as the Chair of the Western Saudi Arabia IEEE Electron Device Society Chapter. She is an IEEE Electron Devices Society Distinguished Lecturer. She is an associate editor-in-chief at Applied Nanoscience (Springer Nature) and associate editor at the Nano Select by Wiley and Microelectronics Engineering by Elsevier. She has published over 100 papers in international peer-reviewed scientific journals and conference proceedings, authored two book chapters, two books and holds seven filed U.S. patents.
 
El-Atab has received several significant awards for her research, including the 2015 For Women in Science Middle East Fellowship by L’Oreal-UNESCO, the 2017 International Rising Talents Award by L’Oreal-UNESCO, and was portrayed among the 2019 “Remarkable Women in Technology” by UNESCO. Prof. El-Atab was also selected to participate in the 70th Lindau Nobel Laureate Meeting in Germany, was selected among the 2020 UC Berkeley EECS Rising Stars, among the 10 Innovators under 35 by MIT Technology Review Arabia in 2020, among the V60 Women in Sustainability by BCG, and as a “NEOM Changemaker” in 2021. 
 
Her research has been extensively covered in various international publications, including IEEE Spectrum, National Geographic, BBC, MIT Technology Review, and Sky News Arabia.

Professor El-Atab’s current research focuses on designing and developing innovative smart memory electronic devices for futuristic in-memory sensing and computing applications. El-Atab and her team aim to enhance an increasingly digitized world for emerging applications like artificial intelligence, IoT and augmented reality.