演讲人：Lingjie Duan [SUTD]
时间：14:00-15:00, Nov 6, 2025 (Thu)
地点：FIT1-312
内容：
Existing AI methods (model-based optimization, deep reinforcement Learning) struggle with generalization and rapid adaptation in dynamic wireless networks. This work pioneers "LLM for Wireless," harnessing the general intelligence of Large Language Models (LLMs) to proactively optimize network infrastructure, moving beyond merely supporting LLM deployment (Wireless for LLM). We introduce novel, LLM-inspired solutions for two critical distributed system challenges: Distributed Network Learning Deficiency: Conventional load balancing in Mobile Edge Computing (MEC) ignores data heterogeneity, leading to poor server specialization and catastrophic forgetting. Our solution, the LLM-inspired Mixture of Experts (MoE) Architecture, uses a gating network to route tasks based on data characteristics to specialized MEC servers, dramatically enhancing network generalization and learning efficiency. Insufficient Adaptability in Dynamic Resource Allocation: Current strategies fail in dynamic environments; DRL requires costly retraining after environmental shifts. We introduce In-Context Learning (ICL)—the core LLM reasoning paradigm—for resource allocation. ICL generates optimal decisions instantly using contextual examples, eliminating the need for retraining and enabling rapid, low-latency adaptation in time-varying wireless networks.
个人简介:
Lingjie Duan is joining Hong Kong University of Science and Technology (Guangzhou) as a Professor in the Internet of Things Thrust. He earned his PhD from The Chinese University of Hong Kong in 2012. Following a Visiting Scholarship at the University of California, Berkeley, he joined the Singapore University of Technology and Design (SUTD), a collaboration with MIT. His research is distinctively interdisciplinary, covering human-centric AI, distributed machine learning, and computer networking. His editorial leadership is evident through his roles as an Editor for IEEE/ACM Transactions on Networking and an Associate Editor for IEEE Transactions on Mobile Computing. He previously contributed as an Editor for IEEE Transactions on Wireless Communications and a Guest Editor for IEEE Journal on Selected Areas in Communications, and notably served as General Chair for the 21st IEEE/IFIP WiOpt International Conference (2023) in Singapore. His contributions to interdisciplinary research “Network Economics” with publications in top electrical engineering, AI, and business venues have garnered significant acclaim. Since 2021, Stanford University has recognized him among the World’s Top 2% Scientists, and ScholarGPS named him a 2022 Highly Ranked Scholar. His awards include the First Prize Paper Award from the Computer Academy of Guangdong (2024) and the SUTD Excellence in Research Award. Earlier in his career, he was the Runner-up for the IEEE ComSoc Best Young Professionals Award (2016) and received the 10th Asia-Pacific Outstanding Young Researcher Award from the IEEE Communications Society (2015).
