sigmod会议日期（sigmod2021会议）

11月15日10:00-11:00

地点：清华大学电子工程馆9-208

无线机器学习：从语义通信到分布式学习与推断

Machine learning is poised to transform wireless communication technologies in the next decade, and seamless integration of AI technologies into 6G networks will be a transformative leap beyond previous generations. Towards this future, synergies between communications and machine learning are two-fold: data-driven methods coupled with established model driven solutions provide novel approaches and state-of-the art results to many long-standing challenges in communications, from coding to resource optimization. On the other hand, distributed learning and inference problems introduce new challenges imposing more stringent reliability and latency constraints on future communication networks. In this talk, I will touch upon both aspects, and present my group’s recent contributions spanning data compression, communications, and distributed learning and inference problems, bringing together tools from information and coding theories with recent advances in machine learning.  

Deniz Gündüz received his Ph.D. degree in electrical engineering from NYU Tandon School of Engineering in 2007. Currently, he is a Professor of Information Processing in the Electrical and Electronic Engineering Department at Imperial College London, UK, where he also serves as the deputy head of the Intelligent Systems and Networks Group. Dr. Gündüz is a Fellow of the IEEE, and an elected member of the IEEE Signal Processing for Communications and Networking (SPCOM) and Machine Learning for Signal Processing (MLSP) Technical Committees. He serves as an area editor for the IEEE Transactions on Information Theory. He is the recipient of the IEEE Communications Society - Communication Theory Technical Committee (CTTC) Early Achievement Award in 2017, Starting (2016), Consolidator (2022) and Proof-of-Concept (2023) Grants of the European Research Council (ERC), and has co-authored several award-winning papers, most recently the IEEE Communications Society - Young Author Best Paper Award (2022), and IEEE International Conference on Communications Best Paper Award (2023). He received the Imperial College London - President's Award for Excellence in Research Supervision in 2023.