Profiles

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.

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

Hakim's research focuses on the following areas:

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

Aijaz H. Lone is a PhD candidate Integrated Intelligent Systems I2S group, under the guidance of Professor Gianluca Setti at King Abdullah University of Science and Technology (KAUST), I'm dedicated to pushing the boundaries of spintronic innovation. With a background in electrical and computer engineering from the Indian Institute of Technology (IIT-M), I've developed a passion for advancing spintronic devices for data storage and neuromorphic applications.

As a PhD candidate Integrated Intelligent Systems I2S group, under the guidance of Professor Gianluca Setti at King Abdullah University of Science and Technology (KAUST), I'm dedicated to pushing the boundaries of spintronic innovation. With a background in electrical and computer engineering from the Indian Institute of Technology (IIT-M), I've developed a passion for advancing spintronic devices for data storage and neuromorphic applications.

During my Ph.D., I focused on simulating and experimentally realizing spintronic devices tailored for neuromorphic (brain-inspired) computing. This includes advanced spintronic memories that emulate synapse and spiking neuron functionalities. By integrating these devices, I have explored their potential in implementing artificial neural networks (ANNs) and spiking neural networks (SNNs) at both circuit and system levels, aiming to improve the computational paradigms.

As a researcher, I bring expertise in modeling, simulations, and experimental realization to the table. My focus
lies in pioneering spintronic technologies like magnetic tunnel junctions (MTJs), domain wall devices, and
magnetic skyrmionic devices – all with the goal of revolutionizing AI and machine learning.

Through my research, I aim to bridge the gap between theoretical understanding and practical implementation, driving the development of novel spintronic-based solutions for AI.

Charalampos Antoniadis received a Diploma degree (Hons.) in Computer and Communication Engineering, an M.S. degree in Computer Science, and a Ph.D. in Electrical and Computer Engineering from the University of Thessaly, Volos, Greece, in 2011, 2014, and 2019, respectively. He is currently a Postdoctoral Fellow in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. Before joining KAUST, he served as an Adjunct Lecturer at the University of Thessaly for one year.

Dr. Antoniadis was awarded an M.Sc. study fellowship by the University of Thessaly and the Hellenic Foundation for Research and Innovation (HFRI) fellowship for his Ph.D. studies. Additionally, he led a student team that won the First Place Award in the ACM TAU 2020 and TAU2 2021 timing analysis contests.

Charalampos's research focuses on the following areas:

• Efficient AI
• Generative AI and LLMs
• Smart city applications
• Electronic Design Automation

Khalil obtained a bachelor of science degree in electromechanical engineering (with honor) in 2013 and a master of science in robotics in 2014 from the National Engineering School of Sfax (ENIS), Tunisia.

Khalil's Ph.D. research work is about "Miniaturized Drug Delivery Systems for Biomedical Applications" and his research interests include Drug Delivery Systems, Micropumps, Biomedical Devices, Bioengineering, and MEMS.

Meng Tang earned his bachelor’s degree in applied physics and his Ph.D. in physics from Tongji University. In December 2022, he joined the Physical Science and Engineering Division at King Abdullah University of Science and Technology (KAUST) as a postdoctoral fellow under the supervision of Professor Xixiang Zhang. In March 2024, he transitioned to the Computer, Electrical and Mathematical Sciences and Engineering Division at KAUST, where he now works as a postdoctoral fellow under the supervision of Professor Gianluca Setti.

Meng Tang's research interests include spin-orbit torque (SOT) effects and spin transport, SOT-driven magnetization switching, SOT-based MRAM, spintronics-based neuromorphic computing and hardware security primitives, and superconducting spintronics. His areas of expertise encompass thin film deposition techniques (such as magnetron sputtering and pulsed laser deposition), nanofabrication methods (including lithography and ion milling), vibrating sample magnetometer (VSM), electrical transport measurements, harmonic Hall voltage measurements for SOT, current-driven magnetization switching measurements, spin-torque ferromagnetic resonance (ST-FMR), magneto-optical Kerr effect (MOKE) microscopy, X-ray reflection (XRR), and X-ray diffraction (XRD). Additionally, he is proficient in LabVIEW programming for measurement automation.

Divyanshu is a Ph.D. candidate in the Electrical and Computer Engineering department at KAUST. He received his M.Tech degree in VLSI from the Indian Institute of Technology (IIT) Mandi, India. He has worked as a visiting student at the Innovative Technologies Lab and the Integrated Circuits and System Group at KAUST. 

His research interests include Spintronics devices and circuits, VLSI design for beyond CMOS devices, and Hardware security primitives.

Elham is currently a PhD student in Electrical and Computer Engineering program (ECE) at KAUST. She holds an MSc in Software Systems Engineering from UCL, London. She has experience in academia working as teaching assistant, then lecturer and department coordinator. She also worked in industry as a system analyst.

Elham's research interest lies under the field of smart mobility by addressing the current challenges faced by traffic control systems. Her current research focuses on design a sustainable AI-based models to mitigate the limitations of the current smart mobility solutions.

Aijaz H. Lone is a PhD candidate Integrated Intelligent Systems I2S group, under the guidance of Professor Gianluca Setti at King Abdullah University of Science and Technology (KAUST), I'm dedicated to pushing the boundaries of spintronic innovation. With a background in electrical and computer engineering from the Indian Institute of Technology (IIT-M), I've developed a passion for advancing spintronic devices for data storage and neuromorphic applications.

As a PhD candidate Integrated Intelligent Systems I2S group, under the guidance of Professor Gianluca Setti at King Abdullah University of Science and Technology (KAUST), I'm dedicated to pushing the boundaries of spintronic innovation. With a background in electrical and computer engineering from the Indian Institute of Technology (IIT-M), I've developed a passion for advancing spintronic devices for data storage and neuromorphic applications.

During my Ph.D., I focused on simulating and experimentally realizing spintronic devices tailored for neuromorphic (brain-inspired) computing. This includes advanced spintronic memories that emulate synapse and spiking neuron functionalities. By integrating these devices, I have explored their potential in implementing artificial neural networks (ANNs) and spiking neural networks (SNNs) at both circuit and system levels, aiming to improve the computational paradigms.

As a researcher, I bring expertise in modeling, simulations, and experimental realization to the table. My focus
lies in pioneering spintronic technologies like magnetic tunnel junctions (MTJs), domain wall devices, and
magnetic skyrmionic devices – all with the goal of revolutionizing AI and machine learning.

Through my research, I aim to bridge the gap between theoretical understanding and practical implementation, driving the development of novel spintronic-based solutions for AI.