Profiles

Wenbo Yan received the degree of Bachelor of Science in Material Science and Engineering in 2021 from South China University of Technology, Guangdong, China, and a master’s degree in Material Science and Engineering in 2022 from King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.He is now a Ph.D. student in the Photonics Laboratory at KAUST.

Photonics and optoelectronics, Solar energy

William He is a Ph.D. student at the Integrated Photonics Laboratory under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, William did his undergraduate study in University of California, Santa Barbara (UCSB), ranked in the top ~10%  and obtained Dean's Honors for his outstanding performance. William has actively participated in research since his second year in UCSB and has been a co-author of three high-quality journals. Besides academic research experiences, William has also been actively participating in several volunteer work, extracurricular activities, and one internship in Pacific Transformer Corporation in United States.

William's research interests include integrated Si photonics and its applications in data centers. 

His research interest is mainly in Bayesian and computational Statistics, currently working on Directional Statistics and applications with R-INLA. He is also interested in Deep/Machine Learning algorithms.

Xiangpeng Ou is a Ph.D. student at the Integrated Photonics Laboratory under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, Xiangpeng received a B.E. degree in Optoelectronic Information Science and Engineering from the University of Electronic Science and Technology of China (UESTC) in 2018 and a M.S.degree in Microelectronics and solid state electronics from the Institute of Microelectronics, Chinese Academy of Sciences (IMECAS) in 2022. Xiangpeng had three-year experience in Si photonics design and characterization, three-year hands-on fabrication and characterization experience in Si photonics on IMECAS’s 8-inch standard silicon photonics platform, strong and comprehensive research capability with 4 first-author SCI journals (OE) and 1 conference paper (SPIE/COS Photonics) published, 6 patents applied, and 1 SCI journal submitted. 

Xiangpeng's research interests are in Silicon Photonics and its applications, including LiDAR, biosensing, and quantum information processing.

Xiaochuan Gou is a Ph.D. candidate in the Computer Science program at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Di Wang and Prof. Xiangliang Zhang. His research focuses on spatio-temporal data mining, with an emphasis on explainability and efficiency in deep learning models for traffic forecasting and urban computing. He is the lead author of TraffiDent, an open-source multimodal traffic dataset that integrates incident information and supports explainable modeling, and has published multiple papers in top-tier international conferences such as CIKM, WSDM, Big Data, and SIGSPATIAL.

Xiaochuan's research interests include machine learning, data mining, and GIS. He aspires to build new machine learning models to resolve existing problems in public traffic planning, urban planning and social network related to the modern life.

Xiaofeng Xu is a Ph.D. candidate in the AMCS program at KAUST, under the supervision of Professor Jinchao Xu. His research lies at the intersection of traditional numerical methods for partial differential equations (PDEs) and modern machine learning approaches. He is particularly interested in developing efficient and provably convergent training algorithms for neural networks in numerical PDEs.

Xiaofeng received his Bachelor's degree in Mathematics and Computer Science with First Class Honors from the Hong Kong University of Science and Technology (HKUST), and his Master’s degree from the Pennsylvania State University.

Xiaofeng Xu research focuses on the intersection of traditional numerical methods for partial differential equations (PDEs) and modern machine learning approaches. He is particularly interested in developing efficient and provably convergent training algorithms for neural networks in numerical PDEs.

Xiaoyi Song received his Bachelor's degree in Electronic Science and Technology from the University of Electronic Science and Technology of China (UESTC) in 2022 and is currently pursuing a Master's degree at UESTC. Before joining KAUST, he engaged in research on magneto-optical integration and integrated photonics for three years. His research experience encompasses the deposition, design, and characterization of magneto-optical materials and photonic devices, including phase shifters and nonreciprocal components such as optical circulators. He has published a research paper in Photonics Research.

Xiaoyi’s research interests are in Silicon photonics and its applications, including on-chip light source, LiDAR, and nonreciprocal optical devices.

Xin Yao comes from the School of Gifted Young at the University of Science and Technology of China (USTC), which is designed for the most talented young students in China. Xin majored in Photoelectric Information Science and Engineering, during the past three years study, he won Silver Award for excellent students (Top~10％) and Freshmen Scholarship. Because of the experience in ‘Jiuzhang’ quantum computing laboratory, he is interested in the Si photonics and integrated optical circuits, which show promise for stable quantum computation. He started his MS/PhD study in IPL in the August 2023.

Silicon photonics, on-chip lasers, heterogeneous integration

I am a PhD student in computer science specializing in Riemannian geometry and flow visualization.
In my free time and during my bachelor stage,  I am working  in graphics engines and computer vision.

Research interest

He is interested in observer relative flow visualization,  extreme-scale data, visualization, computer graphics.

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

Xuhao Wu is a Ph.D. student at the Integrated Photonics Laboratory under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). He received his B.E degree in Optoelectronic Information Science and Engineering from Harbin Institute of Technology and M.S. degree in Photonics from Ghent University. After graduation from Ghent University, Xuhao joined a spin-off company of IMEC, Luceda Photonics, and worked as an application and PDK development engineer. During his time there, Xuhao honed his programming skills and provided exceptional customer support, assisting over 50 individuals with their design projects. Additionally, he conducted training sessions, including two workshops with 100 attendees each, and delivered lectures at universities, including Shanghai Jiaotong University and Zhejiang University. Xuhao's contributions also include building IPKISS PDK for various foundries on the SOI/SiN/SiON platform.

Xuhao’s research interests are in applications of integrated photonics for optical computing, LiDAR, and optical communication.

Yan Wang is a M.S./Ph.D. student in the Division of Computer, Electrical and Mathematical Sciences & Engineering (CEMSE) at King Abdullah University of Science and Technology (KAUST). She obtained her bachelor's degree of Communication Engineering from the University of Electronic, Science, and Technology of China (UESTC) in 2024.

Photonics and optoelectronics, Ultrawide bandgap semiconductor

Yara Banda is an M.S./Ph.D. student at the Photonics Lab in the Electrical and Computer Engineering Department (CEMSE) at King Abdullah University of Science and Technology (KAUST). She received her B.Sc. degree from King Abdulaziz University (Jeddah, Saudi Arabia) in 2021.

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.

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

Yousef Awad received his B.Sc. degree in Communication and Networks Engineering from Prince Sultan University, Riyadh, Saudi Arabia, in 2020, and his M.Sc. degree in Telecommunication Engineering from King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, in 2024. He is currently pursuing a Ph.D. in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

His research interests span various areas of wireless communication systems, including Integrated Sensing and Communications (ISAC), Unmanned Aerial Vehicle (UAV) detection, and applications of Reconfigurable Intelligent Surfaces (RISs). During his M.Sc. studies, he also worked as a Telecommunication Engineer at King Fahd International Airport (KFIA), Dammam, Saudi Arabia, with Enova by Veolia.

Yousef’s research interests span various topics in wireless communication systems, including Integrated Sensing and Communications (ISAC), Unmanned Aerial Vehicle (UAV) detection, and applications of Reconfigurable Intelligent Surfaces (RISs).