学　术

　　教师发展中心“名师讲堂”活动特别邀请IEEE Fellow、南洋理工大学Dusit Niyato教授来校作学术交流。具体安排如下，欢迎广大师生参加。

　　一、主　题：Diffusion Models in Generative AI Enabled Network Optimization

　　二、主讲人：IEEE Fellow、南洋理工大学Dusit Niyato教授

　　三、时　间：2023年10月26日（星期四）10:00-12:00

　　四、讲座形式：腾讯会议  会议号：230-455-006

　　五、主讲内容：

　　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 Internet of Vehicles (IoV) networks. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design.

　　六、主讲人简介：

　　Dusit Niyato，新加坡南洋理工大学教授，IEEE Fellow。研究方向包括无线和移动网络以及分布式计算，曾获IEEE通信学会亚太区最佳青年研究员奖，2011年IEEE通信学会Fred W. Ellersick论文奖，目前担任IEEE Communications Surveys & Tutorials期刊主编，该期刊影响因子为25.249，是通信领域期刊影响因子排名第一的国际顶级综述期刊，此外，也担任IEEE Transactions on Wireless Communications期刊编辑，担任IEEE Internet of Things Journal、IEEE Transactions on Mobile Computing、IEEE Transactions on Vehicular Technology、IEEE Wireless Communications和IEEE Network期刊副编辑，担任IEEE Journal on Selected Areas on Communications期刊的客座编辑，获誉2016-2017年度IEEE通信学会杰出讲师，2017-2021年度计算机科学领域高被引学者。

　　七、主办单位：教师发展中心

　　　　承办单位：信息与通信工程学院