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.

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.

Eman Kabbas is a Saudi researcher specializing in Bayesian statistics and modeling. She earned her Bachelor’s degree in Mathematics from Imam Abdulrahman bin Faisal University, then continued her studies in the United States through the King Abdullah Scholarship Program, obtaining a Master’s degree in Applied Mathematics from the University of North Carolina. Supported by scholarships from KAUST and the Royal Commission of Jubail and Yanbu, Eman is currently a PhD student in Applied Mathematics and Computational Science (AMCS) at King Abdullah University of Science and Technology (KAUST), supervised by Professor Håvard Rue. Beyond her research, Eman is a Mathematics and Statistics faculty member at Jubail Industrial College under the Royal Commission of Jubail and Yanbu, and co-founder of Sorat Alardh, a startup advancing environmental monitoring and climate analytics. She envisions combining theory and real-world application by transforming scientific research into practical tools that enhance environmental resilience and data-driven innovation in Saudi Arabia. Eman enjoys reading, learning new languages, playing the piano, and exploring strategic games like chess.

Eman Kabbas's research interests focus on developing and applying spline models in non-parametric regression. She addresses the limitations of splines in prediction tasks with insufficient data by proposing a spline model suitable for both regular and irregular observations, leverages Bayesian techniques to ensure efficient modeling and reliable predictions.

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

Firas Fatani is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), where he conducts his research in the Integrated Microwave Packaging Antennas & Circuits Technology (IMPACT) Lab under the supervision of Professor Atif Shamim. His research focuses on printed, flexible, and battery-free microwave biosensors for non-invasive health monitoring through sweat analysis. By combining RF and microwave engineering with electrochemical sensing and Internet of Things (IoT) integration, his work advances the development of next-generation wearable and wireless diagnostic platforms.

Throughout his doctoral studies, Firas has demonstrated strong leadership in interdisciplinary research, product innovation, and academic collaboration. He has authored several high-impact publications, including ACS Sensors—where his research was featured on the journal cover—IEEE Sensors Journal, and Scientific Reports. His conference contributions include presentations at IEEE Sensors 2024 (Kobe, Japan), IEEE Sensors 2025 (Vancouver, Canada), and the APS March Meeting. His ongoing projects explore multi-analyte sensing, data fusion, and AI-assisted signal interpretation for wireless biomedical systems.

Firas holds a Master of Science degree in Electrical Engineering from KAUST, specializing in IoT systems, and a Bachelor of Science degree in Electrical Engineering with High Honors from the Milwaukee School of Engineering (MSOE). MSOE is recognized by U.S. News & World Report as one of the nation’s leading engineering institutions—ranked #10 in undergraduate engineering programs and #2 among regional universities in the Midwest.

Before pursuing his Ph.D., Firas gained international industrial experience in the manufacturing and IoT sectors. He served as an Electrical and Controls Engineer at C&D Technologies Inc. in the United States, where he introduced process automation and quality improvements in large-scale battery manufacturing. In Saudi Arabia, he contributed to smart infrastructure initiatives as an IoT consultant at NEOM’s Food Sector Technology team and as a PLC Controls Engineer at Red Sea Farms, designing AI-assisted automation systems for sustainable agriculture.

Beyond academia, Firas co-founded FreshSense, a startup that developed patented smart flexible sensors for food safety and inventory optimization. The venture was a finalist in the TAQADDAM Innovation Accelerator and secured pilot implementation with Radwa Farms.

He is a recipient of the King Abdullah Scholarship Program for undergraduate study abroad and the KAUST Fellowship for both his master’s and doctoral research. Firas has represented KAUST in multiple national and international events and is an active IEEE member. His academic excellence, industrial insight, and entrepreneurial spirit position him at the intersection of research innovation and real-world technology translation.

Firas Fatani’s research focuses on advancing wireless sensing, flexible electronics, and intelligent systems for next-generation connectivity and health technologies. His work combines electromagnetics, materials engineering, and data science to create innovative, low-cost, and battery-free sensing platforms for real-world applications in healthcare, environmental monitoring, and smart infrastructure.

Specific research interests include:

• Wireless and battery-free sensing systems
• Printed and flexible electronics for wearable and environmental applications
• Additive manufacturing and hybrid fabrication for RF and sensor integration
• Data analysis and machine learning for intelligent sensing and signal interpretation
• Internet of Things (IoT) architectures for scalable sensor networks
• Electromagnetic modeling and RF component design
• System-level integration of sensors, materials, and data analytics
• Translational applications of wireless technologies across biomedical and industrial domains

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.

• King Abdullah University of Science and Technology (KAUST) December 2021 - Present

PhD in Applied Mathematics and Computational Sciences Thuwal, Saudi Arabia, Advisor: Peter Richtarik 

• King Abdullah University of Science and Technology (KAUST) August 2020 - December 2021

MS in Applied Mathematics and Computational Sciences Thuwal, Saudi Arabia
Advisor: Peter Richtarik 

• Moscow Institute of Physics and Technology (MIPT) September 2014 - July 2019

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.

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

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.

• Geospatial data analysis and health surveillance
• Spatio-temporal disease data
• Statistics and spatial epidemiology
• Geospatial modeling
• Disease mapping

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).

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.

Hanguang Liao received the B.E. degree in microelectronics from the University of Electronic Science and Technology of China (UESTC), Chengdu, China in 2019, and the M.S. degree in Electrical and Computer Engineering from the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, in 2021, where he is currently pursuing the Ph.D. degree with the IMPACT Laboratory, Electrical and Computer Engineering Program. 

Hanguang Liao was the First Place Winner of the 2022 IEEE AP-S Student Design Contest. He was also the Second Place Winner of the 2024 IEEE IMS Student Design Contest.

His research interests include electrically small antennas, antennas for the Internet of Things (IoT) applications, additive manufacturing, printed microwave component and mmWave components. He serves as reviewers for multiple IEEE journals of AP-S and MTT-S.

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.

Haoyang Li is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST) supervised by Prof. Xin Gao. His research focuses on developing AI-driven methods to integrate multimodal biomedical data, spanning spatial multi-omics, histopathology, and single-cell genomics, with the goal of decoding spatial heterogeneity in diseases and advancing diagnosis, prognosis, and biomarker discovery for personalized therapies. His research has been published in prestigious journals and conferences such as Nature Machine Intelligence, Nature Communications, Science Advances, Bioinformatics, IEEE TMI, and MICCAI. One of his first-authored papers in Nature Communications is recognized as Editor’s Highlight and the 50 best papers in 'Biotechnology and methods'. In addition, Haoyang had two internships at Yale University and Stanford University as visiting student researcher in 2023 and 2024. He has served as a teaching assistant and guest lecturer for the Ministry of Interior in Saudi Arabia, Saudi Aramco, and KAUST. Currently, he serves as an editorial board member and a guest editor for Molecular & Cellular Biomechanics and Biomedical Informatics.

Haoyang has a broad interest in developing AI models to address biological and healthcare problems. Recently, his research has focused on developing AI models for spatial biology, including spatial multi-omics, spatiotemporal omics, and pathological imaging, aimed at translational and clinical research.

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

He received his M.S. degree in Computer Science from Shenzhen University in 2022, where he was honored with the China National Scholarship and Outstanding Graduate Award. In 2022, he interned at Jarvis Lab, Tencent, and was a visiting student at Norwegian Biometrics Laboratory (NBL), Norwegian University of Science and Technology (NTNU). In 2024, he joined Meta AI as a research scientist internship. He has first-authored more than ten papers in top-tier journals and conferences. His work was recognized as the best paper in the NeurIPS 2023 workshop. He is the reviewer for CVPR, ICCV, ECCV, ICML, AAAI, and MICCAI. His recent research interests primarily focus on generative models, particularly their efficiency and security aspects. His long-term goal lies in making the learnable systems reliable, responsible, and explainable..

Deep Generative Models, XAI, Efficient AI and Responsible AI.

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