On September 5th, the "Masters Lecture", organized by the Teacher Development Center and sponsored by the School of Information and Communication Engineering, hosted Dusit Niyato, IEEE Fellow and Professor from Nanyang Technological University, to deliver an exciting academic lecture titled "Diffusion Models in Generative AI Enabled Network Optimization" for the faculty and students of the university. The lecture was moderated by Professor Gang SUN.
Professor Dusit Niyato expressed that Generative Diffusion Models (GDMs) have gained prominence in the field of Generative Artificial Intelligence (GAI), showcasing their versatility and effectiveness in various applications. GDMs can model complex data distributions and generate high-quality samples, demonstrating exceptional performance in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, involving a series of noise injection and denoising steps, represents a powerful and distinctive approach in learning and generating data.
In his presentation, Professor Dusit Niyato provided an overview of the foundational research on Generative Diffusion Models and delved into their characteristics and advantages, highlighting their broad applicability across different domains. He introduced the fundamental background of applying GDMs in network optimization and presented specific case studies of applying GDMs in various network optimization tasks. These case studies showcased the integration of Generative Diffusion Models with Deep Reinforcement Learning (DRL), Semantic Communications (SemCom), and Internet of Vehicles (IoV) networks, emphasizing the practicality and efficiency of GDMs in real-world scenarios, shedding light on network optimization and design..
During the interactive session, Professor Dusit Niyato engaged in lively discussions with students and faculty, addressing topics such as the characteristics of GDMs, case studies on speech generation based on GDMs, and the time complexity of applying GDMs. Drawing from questions raised by the audience, Professor Dusit Niyato analyzed the advantages of Generative Diffusion Models in learning and generating data, providing valuable insights for students on how to apply GDMs in network optimization.
The "MastersLecture" event was organized by the Teacher Development Center andsponsoredby the School of Information and Communication Engineering.
Related Links:
Professor Dusit Niyato, an IEEE Fellow, is currently a professor at the School of Computer Science and Engineering at Nanyang Technological University in Singapore. His research focuses on wireless and mobile networks as well as distributed computing. He has received the IEEE Communications Society Asia-Pacific Best Young Researcher Award and the 2011 IEEE Communications Society Fred W. Ellersick Paper Award. Professor Dusit Niyato serves as the editor-in-chief of the IEEE Communications Surveys & Tutorials journal, with an impact factor of 25.249, ranking it as the top international review journal in the field of communication. Additionally, he serves as the editor for the IEEE Transactions on Wireless Communications journal and as associate editor for IEEE Internet of Things Journal,IEEE Transactions on Mobile Computing,IEEE Transactions on Vehicular Technology,IEEE Wireless CommunicationsandIEEE Network, serving as a guest editor for the IEEE Journal on Selected Areas in Communications.He has been recognized as the IEEE Communications Society Distinguished Lecturer for the years 2016-2017 and has been listed as a highly cited researcher in the field of computer science from 2017 to 2021.
