Profiles

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).

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.

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.

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.

José Maria earned his Bachelor of Engineering in Electronic Engineering, with a minor in Telecommunications, from Universidad Peruana de Ciencias Aplicadas (UPC) in Lima, Peru, in 2018. During his undergraduate studies, he was awarded a partially funded scholarship in 2013. In 2018, he received funding for a research project through the VII Annual Research Incentive Competition at UPC, which led to the publication of a paper and a presentation at the XXII Symposium on Image, Signal Processing, and Artificial Vision (STSIVA) in 2019.

José Maria began his career with internships at IBM Peru, first as a Computer Specialist and later as a Software Developer. His interest in the Internet of Things (IoT) grew, leading him to become a speaker at various universities, where he taught IoT and Machine Learning. He focused on using single-board computers to connect multiple devices and leverage environmental data. José Maria has worked on several research projects at UPC, including a notable Digital Image Processing project aimed at developing a reliable method for diagnosing health issues in coffee plants using machine learning in Python, providing early diagnosis tools for cultivators.

José Maria is proficient in Python, Java, and machine learning technologies. His research interests lie in leveraging machine learning to enhance communication methods, with a focus on coding and modulation, Smart Grid technologies, and satellite networks. He is passionate about the Internet of Things (IoT) and has shared his knowledge as a speaker at various universities, teaching IoT and Machine Learning. His sessions emphasize the use of single-board computers for data-driven device connectivity, showcasing practical applications of these technologies.

Juan M. Marin is a Doctoral Candidate in Electrical Engineering at King Abdullah University of Science and Technology (KAUST). He received his B.S. degree in Electrical Engineering from the National University of Colombia in 2021. He is currently a postgraduate researcher with KAUST Photonics Laboratory.

His research focuses on the development of Integrated Sensing and Communications (ISAC) as a fundamental asset for the next generation of fiber-based telecommunication networks, endowing optical fibers with multi-parameter sensing and pattern recognition capabilities enabled by machine learning algorithms. In addition to this, his work envisions incorporating fiber optics into the Internet of Things (IoT) by enabling simultaneous power delivery and energy harvesting in fiber-optic networks.

Fiber-optic sensors; Optical Networks; Applied Machine learning; Signal Processing

Karim is a graduate from Bauman Moscow State Technical University. He received a specialist degree in a field of electrical engineering (2014 – 2020), with a focus on radars and wireless communications. He worked at part-time job as embedded systems and DSP engineer for 2.5 years. After that he had internship in summer of 2019 at Huawei Russian Research Institute (RRI) and after graduating from university, he worked at Huawei RRI for 1 year. During his job he improved receiver’s sensitivity applying some convex and non-convex optimization approaches and provide some dimensionality reduction approaches for system identification.

Nowadays Karim works in topics related to Joint Sensing And Communication (JSAC), quantum computing and communications over unlicensed spectrum.

Adaptive algorithms in wireless communications, Radar signal processing and machine learning. Quantum computing.

Li Zhang received the B.S. degree in microelectronic science and engineering from University of Electronic Science and Technology of China, China, 2018 and the M.S. degree in electrical engineering from King Abdullah University of Science and Technology, Saudi Arabia, 2019.

Li Zhang is interested in quantized neural networks, neural network accelerator and software/hardware co-design.

Lucas graduated in Electrical Engineering at the Federal University of Rio Grande do Norte (UFRN), Natal, Brazil, on December 2019. From January to July 2019, he was a visiting student at the Information Systems Lab/KAUST, when he worked on indoor localization systems using acoustic waves. In the following year, he joined KAUST as a MSc. student under the supervision of Dr. Tareq Al-Naffouri. He successfully obtained his MSc. degree in December 2021. His Master's thesis is titled A Bayesian Approach to D2D Proximity Estimation using Radio CSI Measurements, and the continuation of this work led to a journal publication at the IEEE Open Journal of the Communications Society. He is currently a Ph.D. student at the Distributed Systems and Autonomy Group/KAUST, under the supervision of Dr. Shinkyu Park.

Lucas' research interests are multi-agent systems, robotics, and deep learning (especially Multi-Agent Reinforcement Learning).

Luis Vazquez obtained a Bachelor Degree on Robotics and Telecommunication from Universidad de las Americas Puebla, his final thesis work was a review on autonomous control and Natural Language Processing for the Robotics human-machine collaboration and interconnection between digital and physical components.

My research is focused on the effects of physical attacks to a robot sensor in the digital processing of the autonomous process more focused on Autonomous control algorithms for 2D vehicles and drones.