Profiles

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.

Education Profile
Bachelor's degree in Electrical Engineering from the University of Hail and is currently pursuing his Master's degree in Electrical and Computer Engineering at KAUST. 

• Localization.
• Machine Learning.
• GNSS
• Riemannian Optimization

• Wireless communication.
• Signal processing.
• Biomedical signal processing.
• Indoor localization .
• Machine learning 

• Python.
• Machine Learning.
• Data Analysis.
• Artificial Intelligence.

• Wireless Communication.
• Signal Processing.
• Optimization.
• Machine Learning

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.