报告主题：Machine Learning in Digital Twin Edge Networks

报 告 人：张彦

报告时间：2023年7月8日 10：00-11：30

报告地点：计A518

报告摘要：

In this talk, we mainly introduce our proposed new research direction:  Digital Twin Edge Networks (DITEN). We first present the concept and model related to Digital Twin (DT) and DITEN. Then, we focus on new research challenges and results when machine learning is exploited in DITEN, including federated learing, deep reinforcement learning and transfer learning. Edge association and DT mobility, as unique research questions, will be defined and analyzed. We are also expecting that the talk will help the audience understand the future development of edge computing, e.g., digital twin edge networks in the context of Metaverse.

报告人简介：

张彦，现任挪威奥斯陆大学信息工程学院教授，IEEE Fellow, IET Fellow。 入选欧洲科学院院士，挪威皇家科学院院士，挪威工程院院士，2018-2022连续五年全球“高被引科学家”，近期主要研究方向为新一代无线通信网络和智能安全物联网。在相关领域研究成果被引用38000+次，H因子为100。现任多个IEEE Transactions/Magazine期刊编委，包括IEEE TWC, TII, TVT, TSUSC, TGCN,TNSE, NETWORK, IoT, VTM 及 Systems Journal。并现任国内多个核心期刊编委，包括中国通信，计算机科学，物联网学报, 网络与信息安全学报，及数字通信与网络。