Profiles

Dhanu Chettri is a Ph.D. candidate at the Advanced Semiconductor Laboratory (ASL) at King Abdullah University of Science and Technology (KAUST), under the mentorship of Prof. Xiaohang Li. His research focuses on ultra-wide bandgap semiconductors, particularly Gallium Oxide (Ga2O3) and Aluminum Nitride (AlN). Before joining KAUST, he served as a Senior Project Fellow at the Council of Scientific and Industrial Research–Central Electronics Engineering Research Institute (CSIR–CEERI).

Chettri’s research primarily involves material growth, device design, fabrication, and circuit implementation of advanced semiconductor devices such as MOSFETs and bidirectional switches. He has made significant contributions to the field, as evidenced by his publications. Notably, he achieved the first demonstration of a normally OFF β-Ga2O3 bidirectional switch, featured in Applied Physics Letters, AIP along with the first demonstration of an AlN MOSFET, published in the Journal of Physics D, IOP.

His research is particularly relevant for developing technologies suited to high-temperature and extreme environment applications, demonstrating the critical role and potential of ultra-wide bandgap semiconductors in modern electronics.

Dhanu's research interests include ultrawide bandgap semiconductor materials, specifically Ga2O3 and AlN. His work focuses on the fabrication and characterization of devices such as MOSFETs and FinFETs.

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.

Eman Kabbas earned a Bachelor of Science and Education in Mathematics from Imam Abdulrahman Bin Faisal University and a Master’s in Mathematics from the University of North Carolina at Charlotte. Her academic journey, marked by deep curiosity and dedication, led her to become a lecturer at Jubail Industrial College (JIC). Now, as a Ph.D. candidate in Applied Mathematics and Computational Sciences under the mentorship of Professor Håvard Rue, Eman delves into Bayesian and computational statistics, striving to bridge theoretical concepts with practical applications. Eman is dedicated to fostering a new way of teaching statistics and data science through her research experience.

Eman's research interests include: Bayesian Statistics Computational Statistics Applied Statistics Data Science Her work focuses on advancing the understanding and application of these areas, aiming to contribute significant insights and innovations.

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 is an M.S./Ph.D. student at Photonics Laboratory at King Abdullah University of Science and Technology (KAUST). He obtained a B.S. of science degree in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in 2021. He also worked in the industry in Saudi Aramco until 2023 as an Electrical Engineer.

Optical Fiber Communication Systems, Optical Wireless Communication Systems

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.

Hang Lu is a M.S./Ph.D. student at King Abdullah University of Science and Technology (KAUST).
She obtained bachelor degree of Electronic Engineering from University of Electronic Science and Technology of China (UESTC) in 2021.
She took part in the Visiting Student Research Program (VSRP) at KAUST during 2020/11-2021/02.

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.

Professional Profile

●       03/2023 - 09/2023, Research Intern, Stellantis & IMT Atlantique

●       05/2022-09/2022, R&D Intern, Invisensing

●       06/2021-08/2021, Research Intern, Institut Photovoltaïque d’Île-de-France

Education

● 01/2024 – Present, Ph.D. student in Photonics Lab, CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.

● 09/2022 – 12/2023, Second Master’s degree in Optical Networks and Photonics Systems, Université Paris-Saclay & Institut Polytechnique de Paris, Palaiseau, France.

●09/2020 – 12/2023, Engineering degree of Theoretical and Applied Optics, Institut d'Optique Graduate School - Université Paris-Saclay, Palaiseau, France.

●09/2017 – 06/2021, Bachelor of Science and Engineering in Photoelectric Information Science, Huazhong University of Science and Technology, Wuhan, China.

• Fiber Optic Sensing
• Optoeletronics
• Photonics

Haozheng HE is currently a MS/Ph.D. student at the Sensors Lab, in the CEMSE, King Abdullah University of Science and Technology (KAUST). He received the Bachelor of Engineering degree in Integrated Circuits and Systems from the University of Electronic Science and Technology of China, Chengdu, China, in 2023.

His research lies in Computer Architecture, Embedded Systems, Artificial Intelligence and FPGA

Heng Wang is a Ph.D. Candidate in Electrical and Computer Engineering of King Abdullah University of Science and Technology (KAUST), where he specializes in nanofabrication, lithography, and nanodevice processing. He earned his bachelor's degree in Microelectronic Science and Engineering from the University of Electronic Science and Technology of China (UESTC). During his academic career, he developed strong hands-on experience in cleanroom processes and supported collaborative research in advanced electronics and quantum devices.

My research focuses on the development of graphene-based geometric diodes for  terahertz (THz) rectennas, aiming to enable efficient high-frequency energy harvesting and detection. I specialize in nanofabrication techniques such as electron beam lithography  to realize ultra-small, high-performance devices. My work also integrates cleanroom process optimization and AI to advance next-generation nano devices.

Hongxian Yi is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). Hongxian obtained his thesis-based M.S. in Computer Science from KAUST in Dec 2020 and his B.S. in Computer Science and Technology from Shandong University in 2018. He has also studied at Beijing Institute of Technology and Chung-Ang University as an exchange student. Before coming to KAUST, he worked as a Solution Architect Intern at Amazon Web Services, Inc.

His research focuses on computer vision, robotics, and autonomous driving systems, with particular emphasis on 3D perception and efficient computing for embedded platforms.

Ibrahim Alsayoud is an M.S./Ph.D. student at King Abdullah University of Science and Technology (KAUST). He obtained the degree of Bachelor of Science in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in 2021.

Photonics and optoelectronics, Fiber-optic sensors

Jiahao Wei is a M.S./Ph.D. student at the Photonics Laboratory at King Abdullah University of Science and Technology (KAUST). He obtained his Bachelor of Optoelectronic Information Science and Engineering from Southern University of Science and Technology (SUSTech) in 2024. During his undergraduate studies, he primarily researched quantum dot light-emitting diodes (QLEDs). From Sept. to Dec. 2024, he conducted academic visiting at Hong Kong University of Science and Technology (Guangzhou).

Photonics, Optoelectronics

Jinane received her Bachelor's Degree in Computer and Communications Engineering from the American University of Beirut (AUB) in 2021, with High Distinction.

From June 2020 to June 2021, she was a visiting student at the Communication and Computing Systems Laboratory (CCSL) at KAUST, in collaboration with the University of California-Irvine (UCI).

Her research interests focus on in-memory computing for deep learning hardware acceleration to enhance the efficiency and performance of neural network computations.

In 2019, Jose Manuel Taboada completed his bachelor's degree in Nanofabrication and Microelectronics at the National Autonomous University of Mexico (UNAM). He then obtained a master's degree in Electrical Engineering from King Abdullah University of Science and Technology (KAUST) in 2022, where he is currently pursuing a Ph.D. His doctoral research focuses on the simulation, design, fabrication, and testing of gallium oxide (Ga₂O₃) based diodes.

Jose Manuel Taboada's research interests include advanced semiconductors, Nanometric fabrication, and characterization processes, and data analysis.