一、主讲题目：The Transformative Impact of Generative AI: Strategies, Applications, and Innovations
二、报告摘要：
This speech explores the transformative potential of Generative AI (GAI) across various domains. Firstly, we examine the use of Large Language Models (LLMs) in repeated games to develop practical strategies aligning with the folk theorem's equilibrium conditions, enhancing cooperative behavior through future payoff considerations. Secondly, we address low-light image enhancement in teleoperation using diffusion-based AI-generated content (AIGC) models. A Vision Language Model (VLM)-empowered contract theory framework optimizes AIGC task allocation and pricing under information asymmetry, improving resource management for teleoperators and edge servers. In the realm of autonomous driving, we integrate Federated Learning (FL) with Vision-language models (VLMs) in Graph Visual Question Answering (GVQA), highlighting advancements in privacy preservation, reduced communication costs, and maintained model performance. Lastly, an LLM-based semantic communication (SC) framework for underwater communication is presented, demonstrating efficient data transmission and resilience against noise and signal loss by performing semantic compression and prioritization of image data. These innovations collectively illustrate the broad impact of AI technologies, shaping strategies, and enhancing applications across various fields.
三、主讲人：Zhu Han
Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor at Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in the Electrical and Computer Engineering Department as well as the Computer Science Department at the University of Houston, Texas. Dr. Han is an NSF CAREER award recipient of 2010, and the winner of the 2021 IEEE Kiyo Tomiyasu Award. He has been an IEEE fellow since 2014, an AAAS fellow since 2020, ACM Fellow since 2024, an IEEE Distinguished Lecturer from 2015 to 2018, and an ACM Distinguished Speaker from 2022-2025. Dr. Han is also a 1% highly cited researcher since 2017.
四、时间：2024年12月2日 10:00-11:00
五、会议入口
#腾讯会议：397-574-553
https://meeting.tencent.com/dm/0d3AtdRGnOjt
会议通过腾讯会议线上平台进行，欢迎广大师生参与本次学术讲座。
