Leadership Team
Dean
Biography
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.
Research Interests
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.
Education
Associate Deans
Biography
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.
Research Interests
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.
Education
Biography
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.
Research Interests
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.
Education
Biography
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).
Research Interests
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.
Education
Dean's Adviser for Communications
Biography
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.
Research Interests
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.
Education
Academic Program Chairs
Biography
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.
Research Interests
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
Education
Biography
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.
Research Interests
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.
Education
Biography
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.
Research Interests
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.
Biography
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.
Research Interests
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.