报告题目：Foundation Models for Wireless Communications: From WirelessLLM to World Models
报 告 人：张军 教授
主 持 人：芮赟 研究员
时 间：12月26日14:00开始
地 点：信息楼133会议室
Abstract
Foundation models, such as large language models (LLMs), deep generative models, and vision-language models, have emerged as powerful tools for various applications. In this talk, we will explore the exciting potential of foundation models in revolutionizing wireless communications and networking. Starting with a brief overview of recent developments in foundation models, we will present key requirements and methodologies to develop large language models for wireless communications. Then we will introduce WirelessLLM as a new framework to apply LLMs to wireless communications, illustrated with use cases including spectrum sensing, power control, and protocol understanding. Extensions to LLM agents for wireless networks and world models based on multi-modality models will also be discussed.
Bio:
Jun Zhang received his Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin. He is an IEEE Fellow and an IEEE ComSoc Distinguished Lecturer. He is an AssociateProfessor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology. His research interests include wireless communications and networking, mobile edge computing and edge AI, and cooperative AI. He is a co-recipient of several best paper awards, including the 2021 Best Survey Paper Award of IEEE Communications Society, the 2019 IEEE Communications Society & Information Theory Society Joint Paper Award, and the 2016 Marconi Prize Paper Award in Wireless Communications. He also received the 2016 IEEE ComSoc Asia-Pacific Best Young Researcher Award.