Long Feng Science Forum Seminar Series | Seminar #137
Dear All,
You are cordially invited to the 137th seminar of Long Feng Science Forum Seminar Series. It will be delivered by Prof. Dusit Niyato (Nanyang Technological University) at 3:00 pm on August 2 (Friday). This seminar will discuss "Generative AI Enabled Network Optimization".
Seminar Information
Time & Date: 3:00 – 4:00 pm on August 2, 2024 (Friday), Beijing Time
Venue: Room 202, Teaching Complex C
Speaker: Prof. Dusit Niyato, Nanyang Technological University
Abstract:
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a variety of applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This presentation gives an introduction on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains. The presentation first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), Semantic Communications (SemCom), and UAV networks. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design.
Biography
Dusit Niyato is currently a President's Chair Professor in the College of Computing & Data Science (CCDS), Nanyang Technological University, Singapore. He received B.E. from King Mongkuk’s Institute of Technology Ladkrabang (KMITL), Thailand in 1999 and Ph.D. in Electrical and Computer Engineering from the University of Manitoba, Canada in 2008. Dusit's research interests are in the areas of mobile generative AI, edge intelligence, quantum computing and networking, and incentive mechanism design. Dusit won the IEEE Vehicular Technology Society Stuart Meyer Memorial Award. Currently, Dusit is serving as Editor-in-Chief of IEEE Communications Surveys and Tutorials (impact factor of 34.4 for 2023) and will serve as the Editor-in-Chief of IEEE Transactions on Network Science and Engineering from 2025. He is also an area editor of IEEE Transactions on Vehicular Technology, editor of IEEE Transactions on Wireless Communications, associate editor of IEEE Internet of Things Journal, IEEE Transactions on Mobile Computing, IEEE Wireless Communications, IEEE Network, IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Cognitive Communications and Networking, IEEE Data Descriptions, IEEE Transactions on Services Computing, IEEE Communications Magazine, and ACM Computing Surveys. He was also a guest editor of IEEE Journal on Selected Areas on Communications. Dusit is the Members-at-Large to the Board of Governors of IEEE Communications Society for 2024-2026. He was named the 2017-2023 highly cited researcher in computer science. He is a Fellow of IEEE and a Fellow of IET.
About SSE MSc. CE
Master of Science in Communications Engineering (MSc.CE) is a two-year full-time master programme offered by CUHK-Shenzhen revolving around the area of communication engineering. The Programme aims to equip students with essential knowledge and skills that enable them to develop and implement solutions to harvesting, transmission, and processing of data and information, with a wide coverage of emerging technology such as 6G and beyond communications and networks, wireless communications, machine learning, Internet of Things, cloud computing, edge computing, big data, and analytic processing.
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