Profiles

• Signal processing.
• Learning method over complex.
• Dynamic structures
• Low-complexity and energy-efficient VLSI signal processing system design.

I am currently pursuing a Ph.D. in Computer Science at King Abdullah University for Science and Technology (KAUST), under the supervision of Prof. Bernard Ghanem. My research focuses on applying machine learning to solve real-world challenges, with an emphasis on efficient training and inference of models. This includes improving data, training, and model efficiency to create more scalable and effective solutions. I hold an M.S. in Computer Science from KAUST and a B.S. in Electrical and Computer Engineering from Virginia Tech. I have over 7 years of experience in automation systems prior to starting my M.S. degree.

I am interested in exploring techniques for efficient training and inference of machine learning models, with a focus on improving data efficiency, training efficiency, and model efficiency.

She holds a Master’s Degree in Data Science from the University of Jeddah and a Bachelor's Degree in Computer Science with a specialization in Software Engineering from King Abdulaziz University. She began her career as a Digital Repository Coordinator at King Abdullah University for Science and Technology (KAUST), where she was responsible for developing data analysis algorithms and building data models. Later, she transitioned to the role of Data Science Coordinator and Teaching Assistant at the SDAIA-KAUST Center of Data Science & AI, where she focused on AI content development, automation, and machine learning training initiatives.

Her research interests focus on generative AI, vision/text multimodality, and deep learning

Yasmine's research interests include controller design, observer design, virtual sensors, scientific machine learning, UAV control in non-inertial frames.

Yiming Yang is a Ph.D. candidate at the KAUST Integrated Microwaves Packaging Antennas and Circuits Technology Research Group under the supervision of Professor Atif Shamim. Before joining KAUST, Yiming obtained a bachelor's degree in electronic science and technology from the University of Electronic Science and Technology of China (UESTC).

Yiming Yang‘s research interests include frequency selective surfaces, reconfigurable intelligent surfaces, and meta-surfaces in combination with additive manufacturing, time modulation, and other fabrication and reconfiguration methods.

Yingquan Li is an M.S./Ph.D. candidate in the KAUST Communication Theory Lab under the supervision of Professor Mohamed-Slim Alouini. Before joining KAUST, Yingquan earned a bachelor's degree in electrical engineering from the University of Electronic Science and Technology of China.

Yingquan's research interests include advanced signal detecting and processing, hardware implementation of key communication technology and underwater optical wireless communication. Li is focusing in the area of digital signal processing, wireless optical communication and circuit design.

Yongqiang Zhang received the B.Sc. degree in communication engineering from Southwest University, Chongqing, China, in 2019, and the M.S. degree in electrical and computer engineering from the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, in 2021, where he is currently pursuing the Ph.D. degree. 

His main research interests include the performance analysis and optimization of the integrated access and backhaul (IAB) networks.

• Nanofabrication of Semiconductors
• N/MEMS design and dynamics
• Control Theory
• Vibration
• Mechatronics

Yue Wang is a Ph.D. candidate at the Photonics Laboratory at King Abdullah University of Science and Technology (KAUST), under the mentorship of Prof. Boon S. Ooi. She earned her B.Eng. in Electronic Science and Technology from the University of Electronic Science and Technology of China (UESTC) in 2020. She received her master's degree in Electrical Engineering from KAUST in 2021.

Yue Wang's research focuses on semiconductor optoelectronics, high-speed color-converting luminescent devices, and optical wireless communication. She specializes in characterizing color-converting materials, designing and fabricating luminescent optoelectronic devices, and developing optical wireless communication systems.

Yue Wang has explored emerging luminescent materials such as perovskites, metal-organic frameworks (MOFs), and organic fluorophores, enabling Gb/s visible light communication and wavelength-division multiplexing with enhanced channel capacity. To relieve the stringent requirements of pointing, acquisition, and tracking in underwater optical wireless communication channels, she employed scintillating fibers and luminescent solar concentrators for wide field-of-view, high-speed photodetection. Her work also extends to optical amplification, where she has developed a high-gain visible-light amplifier based on perovskite quantum dots, potentially addressing the optical loss during long-distance optical data transmission.

• Optical wireless communication.
• Embedded systems.
• Hardware & software co-design.

Zahrah Alnasser obtained her bachelor's degree from Dammam College for Women and her master's degree in pure mathematics from the University of Illinois - Urbana-Champaign.

Real analysis and applied PDEs.

Bachelor's degree from Wuhan University.

Edge computing, federated learning, machine learning systems, and resilient computing.