Profiles

Sebastian Celis Sierra is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), where he develops advanced integral-equation solvers for the accurate simulation of electromagnetic metasurfaces. He holds an M.S. in Electrical Engineering (2018–2020) from KAUST and dual B.Eng. degrees in Electrical/Power Engineering and Electronics Engineering (2014–2018) from Universidad de los Andes, Bogotá.

Sebastian's research focuses on formulating and implementing surface and volume integral-equation methods in both the time and frequency domains to capture complex electromagnetic behavior in arbitrarily shaped metasurfaces. By coupling these formulations with generalized sheet transition conditions (GSTCs), he aims to achieve both numerical efficiency and physical fidelity. His work advances the theoretical foundations and practical computational tools necessary for the next generation of communication systems.

Research Scientist based in Cambridge (UK). Victor works at the Samsung AI Center, focusing on enhancing AI applications in creative and productivity domains. I earned my BSc and MSc in Electrical Engineering from Universidad del Norte, studying under the supervision of Ph.D Juan Carlos Niebles. Victor completed his PhD at KAUST under the mentorship of Prof. Bernard Ghanem, with a research focus on computer vision. My early career was marked by pioneering developments in efficient video and action understanding models. Once I joined industry, I am committed to developing advanced AI applications that empower human creativity and scale General AI, particularly in edge computing environments.

My research spans a wide array of AI disciplines, with a special focus on computer vision, efficient video understanding, and the development of AI agents with a strong interest for edge deployment. I am particularly passionate about build AI Agents to enhance human creativity and productivity. My ongoing projects aim to seamlessly integrate AI capabilities into user-centric applications, pushing the boundaries of what AI can achieve in real-world scenarios.

Vijith Varma Kotte is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He joined KAUST in 2020 under the supervision of Prof. Tareq Y. Al-Naffouri. He received his B.Tech. degree in Electronics and Communication Engineering from Amrita School of Engineering, Bengaluru, India, in 2015, and his M.Tech. degree from Indian Institute of Technology Delhi (IIT Delhi) in 2018.

Prior to joining KAUST, Vijith worked as a Research Engineer at the Centre for Development of Telematics (C-DOT) in New Delhi from 2018 to 2019.

His research interests span signal and image processing, deep learning, and wireless communications, with a particular focus on radar signal processing for biomedical and automotive applications.

• MIMO Radar signal processing.
• Wireless communications..
• Deep Learning.

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.

Yiyang Yu is a Ph.D. Candidate at Integrated Microwaves Packaging Antennas & Circuit Technology Research Group under the supervision of Professor Atif Shamim at King Abdullah University of Science and Technology (KAUST). His current research interests include on-chip antenna design and artificial magnetic conduction design for 6G mm-wave applications.

Yiyang's research interests include ​Electrically Small Antenna 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.

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.