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.
Bayesian and computational Statistics.
Echo Ziyi Yang is a Ph.D. student at King Abdullah University of Science and Technology (KAUST), conducting research under the supervision of Professor Bernard Ghanem at the Image and Video Understanding Laboratory (IVUL) within the Center of Excellence for Generative AI. She obtained her Master’s and Bachelor’s degrees from Harbin Institute of Technology (HIT), China.
Her research interests focus on Generative AI, autonomous agents, machine learning, and reinforcement learning.
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.
Elnur Gasanov is a PhD candidate in the Optimization and Machine Learning Lab at the Center of Excellence for Generative AI (GenAI) at KAUST, where he is advised by Professor Peter Richtárik. His research focuses on distributed machine learning, stochastic optimization, and randomized linear algebra. Elnur holds a Master of Science in Computer Science from KAUST and a Bachelor's degree in Applied Mathematics and Physics from the Moscow Institute of Physics and Technology.
Optimization and machine learning.
Fahad Aljehani is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), where he is supervised by Professors Taous‑Meriem Laleg‑Kirati and Eric Feron. His research integrates classical control theory with modern AI and machine‑learning techniques to create advanced control and estimation frameworks for complex process systems, particularly optimal feeding in aquaculture and bacteria monitoring in wastewater treatment plants.
Aljehani earned his M.S. in Electrical Engineering from KAUST (2019), developing control strategies for distributed solar collectors and a virtual sensor for solar‑irradiance estimation. He holds a B.S. in Electrical Engineering from University of Dayton (2016).
Fahad's research focuses on designing advanced control algorithms and estimation techniques to optimize process control systems, specifically in aquaculture and wastewater treatment. He utilizes a multidisciplinary approach that combines classical control theory with cutting-edge artificial intelligence and machine learning methodologies to develop adaptive, efficient, and scalable models that enhance system performance, improve sustainability, and reduce operational costs.
Area of interests:
Fahad S. Alqurashi is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini. His research focuses on advanced wireless communication technologies for connecting underserved and remote regions, emphasizing cost-effective and high-capacity solutions. His work explores Free Space Optics (FSO), TV White Space (TVWS), and hybrid RF/mmWave systems to achieve point-to-point data rates exceeding 10 Gbps, with a particular interest in maritime and rural connectivity.
Fahad holds a Master of Science in Electrical Engineering from KAUST, where his thesis focused on modeling FSO communication channels for next-generation deployment scenarios. He completed his Bachelor of Science in Electrical Engineering (Electronics and Communication track) at Umm Al-Qura University in Makkah, Saudi Arabia.
Fahad has led strategic connectivity projects in collaboration with global technology leaders such as Google Taara, Meta, Cambium, and national operators like Zain and STC. He is currently spearheading national-scale initiatives with the Communication, Space and Technology Commission (CST), Red Sea Global, and Neom to deliver resilient, sustainable, and scalable wireless infrastructure—including projects connecting offshore islands and rural villages using hybrid FSO/RF links powered by solar systems.
His research has been presented at major international venues including IEEE ICC and the Optical Wireless Communication Conference, and he is an active member of IEEE and the Optical Wireless Communication community. Fahad’s interdisciplinary work supports Saudi Vision 2030 and reflects a strong commitment to impactful digital transformation through cutting-edge wireless innovation.
Alongside the Saudi Vision 2030, Fahad’s interest lies in supporting the future of 5G and 6G. Because of this, he focuses on wireless communication systems, especially in free space optical communication (FSO).
Fares Banjar received his B.S. in electrical engineering from King Fahd University of Petroleum and Minerals (KFUPM) in 2021 and his M.S. in electrical and computer engineering from King Abdullah University of Science and Technology (KAUST) in 2024. He is currently pursuing a Ph.D. in the Photonics Laboratory at KAUST. He also worked in the industry with Saudi Aramco for two years as an Electrical Engineer.
Power-over-fiber systems and fiber-optic-based sensing and communication networks.
Faris Alkhalifah is an MS Electrical and Computer Engineering student with the Integrated Telecommunication and Sensing Systems (ITASS) Research Group headed by Professor Abdulrahman Alhamed at King Abdullah University of Science and Technology (KAUST).
Glen Isaac Maciel García is a Ph.D. Candidate in Applied Physics at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, where he conducted research under the supervision of Prof. Xiaohang Li. He earned his bachelor’s degree in Nanotechnology from the National Autonomous University of Mexico (UNAM). Glen has co-authored 19 peer-reviewed publications, including two first-author papers that were featured as cover articles in Nano Letters and Advanced Electronic Materials.
Glen's research interests include optoelectronics, metamaterials, and nanofabrication. His research focuses on nanoscale devices based on ultra-wide bandgap semiconductors. His work spans device design, fabrication, and characterization, with a particular emphasis on unconventional architectures that extend the limits of traditional semiconductor functionality.
Gokul is an electrical engineering student who is currently doing research in core areas like power electronics, power systems and control systems. His research mainly focuses on grid design, modeling, control and development of modular power converters which helps in creating new solutions for sustainable energy generation, transmission, distribution and consumption.
He is experienced in Hardware-In-the-Loop (HIL) and Rapid Control Prototyping (RCP) systems like RTDS, Opal-RT, Speedgoat, Typhoon and dSPACE. He has great experience in MATLAB Simulink, NI Multisim, OrCAD Pspice and other ECAD tools which include Altium, Eagle and KiCAD.
The project he was involved in with KAUST as a visiting student was the development of a bi-directional multi-node Smart DC Grid for Autonomous Power Interchange Systems (APIS) which includes Energy Storage Systems (ESS). The system is designed in MATLAB Simulink and tested in real-time machines like Speedgoat and Opal-RT which links the software framework called Hyphae by Sony CSL, LF Energy.
He was involved in other research projects like control design of the 6-ph PMSM motor, Level - 3 Autonomous Vehicle, High Voltage Low Power Converter, Robust Steering Controller Design, Modelling of the University's Distribution Network etc...
Gokul's research focuses on power electronics, power systems, and control systems, with an emphasis on grid architecture, advanced modeling, control strategies and the development of modular power converters to optimize sustainable energy generation, transmission, distribution, and consumption. He has substantial expertise in Hardware-In-the-Loop (HIL) and Rapid Control Prototyping (RCP) platforms such as RTDS, Opal-RT, Speedgoat, Typhoon, and dSPACE. Skilled in MATLAB Simulink, NI Multisim, OrCAD Pspice, and ECAD tools including Altium, Eagle, and KiCAD.
PhD in Applied Mathematics and Computational Sciences Thuwal, Saudi Arabia, Advisor: Peter Richtarik
MS in Applied Mathematics and Computational Sciences Thuwal, Saudi Arabia
Advisor: Peter Richtarik
BS in Applied Mathematics and Physics Dolgoprudny, Russia, Advisor: Boris Polyak
Thesis: Averaged Heavy Ball Method
Stochastic Optimization, Distributed Optimization, Federated Learning, Machine Learning
As an Electrical Engineer, I have extensive knowledge in Power Electronics, Energy Conversion, Power Systems, and Energy Flexibility. Also, I have strong experience and love for Control Theory and Optimization. I am currently studying Machine Learning and its applications.
Hanan Alahmadi is a Ph.D. candidate in the Statistics program (CEMSE) at King Abdullah University of Science and Technology (KAUST), specializing in spatial methods for health surveillance in Saudi Arabia, with a focus on data integration and cluster detection under the supervision of Professor Paula Moraga. Her research combines satellite and health data to monitor disease and environmental risks and to develop GIS platforms that support data-driven decision-making. She holds a master’s degree in statistics from KAUST, where she was supervised by Professor Håvard Rue. Hanan is also a lecturer at King Saud University and the founder of Sorat Alardh, a space-tech startup that harnesses Earth observation data for environmental and health applications. Her work has been recognized with several honors, including a grant from the Communications, Space & Technology Commission (CST) and her selection as a finalist in the Falling Walls competition.
Hanan Albarqi obtained a master’s degree in Pure Mathematics from the University of Illinois at Urbana–Champaign in 2022 and a bachelor’s degree in Mathematics from King Khalid University in 2017.
Analysis and applied PDEs.
Hanchen Gan received the M.S. degree in microelectronics from the Institute of Microelectronics, Chinese Academy of Sciences (IMECAS), Beijing, China, in 2024, where he was affiliated with the National Key Laboratory of Integrated Circuit Manufacturing—3D Integration and System Packaging Laboratory.
From March to October 2024, he worked at Cadence as a Product Validation Engineer. He worked in the CPG Group, validating the Clarity 3D full-wave electromagnetic solver. From November 2024 to August 2025, he was a visiting student with the GBDTC Electromagnetic Informatics Lab at the University of Technology Sydney (UTs).
Hanchen’s research interests span antenna design (antenna-in-package (AiP), mmWave phased arrays, base-station antennas, transmissive metasurface antennas) and semiconductor advanced packaging (2.5D/3D packaging，signal and power integrity, die-to-die (D2D) interconnects for chiplets).
Optoelectronic devices and photonic integrated circuit (PIC)
Hani Al Majed has a Bachelor's degree in Electrical Engineering from the University of Illinois at Urbana-Champaign (2019–2023) and is currently pursuing a Master's in Electrical and Computer Engineering at KAUST (2023–2025) under the supervision of Professor Bernard Ghanem. His career includes internships at IBM, the National Center for Supercomputing Applications (NCSA), Discovery Partners Institute, and KAUST, where he worked on projects related to variational quantum models, 3D body reconstruction, sequence learning for epidemiological forecasting, and applications of physics-informed neural operators.
Hani's current research interests encompass machine learning workflow automation, physics-informed neural operators, AI for Science and chemistry.
Sep 2021 – Jun 2025
B.S. in Electronic Science and Technology,
Beijing University of Posts and Telecommunications (BUPT), Beijing, China
Sep 2025 – Present
MS/PhD Student in Electrical Engineering,
King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
Photonics and Optoelectronics
