Profiles

• Robotics
• Self-Assembly
• Control
• 3D Printing
• Modeling

Aoun’s research focuses on improving how power systems operate and plan under high shares of variable renewables. At KAUST he is developing advanced unit commitment methods that explicitly consider renewable uncertainty and system stability while searching for algorithmic speed-ups and new formulations using quantum computation. Earlier work includes stochastic AC optimal power flow solved with machine learning surrogates, and course projects on grid-following and grid-forming inverter modeling for wind farms plus HVDC design for bulk power transfer.

During his master’s degree (fully funded) at Skoltech, Moscow (2022-2024), Aoun worked on a modified frequency control strategy for solar PV inverters using a virtual synchronous generator approach. His bachelor’s degree in Electrical Engineering (COMSATS University Islamabad, 2017-2021) included an ERASMUS+ semester at Sehir University Istanbul, in 2019. For his final-year project he developed an AI-based automatic meter reading framework that used deep neural networks for digit detection and recognition. He graduated as the silver medalist of his class.

Aoun has industrial experience from internships with LESCO in Pakistan and Shakarganj Mills Limited, and he worked as a Management Trainee Engineer at Shakarganj Mills Limited from 2021 to 2022. He programs primarily in MATLAB and Python and is actively developing skills in quantum software stacks such as PennyLane and Qiskit to apply quantum techniques to optimization problems in power systems.

• Unit commitment and scheduling for systems with high renewable penetration
• Quantum and hybrid quantum-classical algorithms for power-system optimization
• Stochastic AC optimal power flow and machine-learning-based surrogates
• Grid-forming and grid-following inverter modeling and control for wind farms
• HVDC system design and power transfer studies

Arturo is a Ph.D. candidate in Electrical and Computer Engineering at the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division of King Abdullah University of Science and Technology (KAUST). Following his participation in the KAUST's 2017 Photonics Summer Camp, he started his graduate studies at KAUST in August 2018. Prior to his graduate studies he earned B.Sc. in Engineering Physics from Instituto Tecnológico y de Estudios Superiores de Monterrey (Mexico) in 2017, and conducted a research intership in the Nuclear Sciences Institute (ICN) of the Universidad Nacional Autónoma de México in 2016.

Arturo is the co-founder of Pixeltra Inc., a startup company specializing in multidimensional imaging solutions through metasurfaces. He actively serves as a reviewer for Nature Communications, and has authored ten publications in high-impact factor journals during his Ph.D. He received the Academic Excellence award from KAUST in 2022 and 2023, and was awarded 2nd place at the 2019 Falling Walls international pitching competition.

Arturo's research focuses on the design and fabrication of optical metasurfaces, emphasizing practical applications in remote sensing and hyperspectral imaging.

Atiya Arshad is an M.S. student in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, where she conducts research under the supervision of Prof. Xiaohang Li. She earned her bachelor’s degree in Electronics and Communication Engineering from Jamia Millia Islamia, New Delhi, India.

Atiya’s research interests include wide-bandgap semiconductors, power devices, and β-Ga₂O₃-based electronics. Her research focuses on high-voltage devices based on ultra-wide-bandgap semiconductors. Her work spans device design, fabrication, and characterization, with a particular emphasis on β-Ga₂O₃ devices for power electronics applications.

Aznaur obtained his bachelor's degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology in 2023. He joined KAUST in 2024 to pursue his MS and PhD degrees.

Deep Learning, Computer Vision, Reinforcement Learning.

Bilal Maassarani is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). He holds a B.S. in Mechatronics Engineering (2014) and an M.S. in Electrical Engineering (2017) from the University of Waterloo. His bachelor’s program included six co-op internships in roles spanning verification engineering, computational research, ASIC verification, hardware design, and radio modeling at companies including IDT, Natural Resources Canada, Ciena, General Motors, BlackBerry, and Broadcom. After completing his master’s degree, he worked as an FPGA developer at Ericsson.

Bilal joined KAUST initially under the supervision of Prof. Jeff Shamma and is currently advised by Prof. Eric Feron. His research focuses on mechatronic systems, particularly taking engineering problems from concept to functional prototypes. During his master’s studies he developed a dynamic check-weighing machine, and his Ph.D. work centers on the design and control of a novel hybrid-flight-mode unmanned aerial system.

Alongside his academic work, Bilal has contributed to several early-stage start-ups involving smart luggage, agricultural automation, and palm-tree-harvesting tools.

Bilal is interested in finding mechatronic solutions and taking them from problem to a functional proof-of-concept. He developed a dynamic weighing machine during his master's and currently a novel hybrid-flight mode unmanned aerial system as a Ph.D. Candidate.

Bumin K. Yildirim received his B.Sc. degree in Electrical and Electronics Engineering from TED University, Ankara, Türkiye, in 2020, and his M.Sc. degree in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST), Saudi Arabia, in 2023. He is currently pursuing a Ph.D. in the Communications and Computing Systems Laboratory (CCSL) at KAUST.

Bumin's research focuses on exploring generative artificial intelligence-based solutions to address the challenges of future wireless communication networks.

Danish Raja is a PhD candidate in the Advanced Semiconductor Laboratory (ASL) at King Abdullah University of Science and Technology (KAUST).

He received his Master's degree from the Indian Institute of Technology (IIT) Jodhpur and his Bachelor's degree in Electronics and Communication Engineering from the Islamic University of Science and Technology (IUST) Kashmir.

Danish’s research experience includes ferroelectric and negative-capacitance devices for energy-efficient computing and memory applications, as well as machine-learning-based semiconductor device modeling.

His current research focuses AI hardware, with an emphasis on the Compute-in-Memory paradigm, energy-efficient device and architecture design, and high-performance computing systems.

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, in-memory computing using beyond CMOS devices, and hardware security primitives.

Elham is currently a PhD candidate at the Communications and Computing Systems Laboratory (CCSL). She received M.Sc. degree in Software Systems Engineering from the Department of Computer Science at University College London (UCL), U.K., in 2018. She recieved B.Sc. degree in Computer Science from Imam Abdulrahman University, Alkhobar, KSA, in 2012. 

Elham's research focuses on AI-driven traffic scene understanding at urban intersections, combining advanced sensing technologies with graph representations to downstream intelligent transportation system applications, including real-time traffic monitoring, risk assessment, behavior analysis, flow prediction, and adaptive traffic control. 

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: 

• Optimal control for a class of nonlinear systems
• Estimation and observer design methods in nonlinear systems 
• Reinforcement learning and dynamics programming
• Computer vision
• Machine learning

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).

Ganesh Mainali is a Ph.D. candidate in Electrical and Computer Engineering at KAUST, where he conducts research in the Advanced Semiconductor Laboratory under the supervision of Prof. Xiaohang Li. Before joining KAUST, he earned an M.S. in Electronic Engineering from Kwangwoon University, South Korea, in 2021.

Ganesh's research focuses on ultrawide-bandgap β-Ga2O3 devices and circuits for monolithic power integration. His work includes monolithic gate-driver ICs, a pseudo-source-gated MOSFET with record intrinsic gain, on-chip thermocouples for junction-temperature sensing, and vertical Schottky barrier diodes designed for high-temperature operation.

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.

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.

• Power electronics
• Power systems
• Anomaly detection
• Artificial intelligence

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).

Hang Lu is a final-year Ph.D. student in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), working in the Photonics Laboratory under the supervision of Prof. Boon S. Ooi. Hang has published in Light: Science & Applications, npj Nanophotonics, and APL Photonics, with her work featured as a cover article in the IEEE Journal of Selected Topics in Quantum Electronics. She also has experience in designing augmented-reality (AR) display systems and is broadly interested in advanced photonic integration and device–application co-design.

Hang's research focuses on engineering optoelectronic devices and photonic integration circuits for applications in optical communication, illumination, and hardware security. She has hands-on experience in optical design and modeling, nanofabrication, and experimental device prototyping, and has led the development of integrated optoelectronic devices and chips for secure and scalable photonic applications.

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