Smart Internet Lab Seminar: When Machine Learning Meets Wireless Communications
Speaker: Shuping Dang
Talk Title: When Machine Learning Meets Wireless Communications
Abstract: To realize ever-increasing demands on various performance metrics and resolve new security challenges in wireless communications, machine learning has been regarded as an imperative tool to improve wireless communications in the pre-6G era. By learning through a large number of data samples, machine learning can produce a well-trained neural network model. Such a model is able to adapt a set of system parameters of wireless systems and/or assign wireless resources in an efficient manner to achieve better performance. In this talk, the basics of machine learning and two specific applications of machine learning for wireless communications, i.e., resource allocation and detection, will be introduced. Following these, related research challenges and future directions will also be shared and discussed.
Shuping Dang received B.Eng (Hons) in Electrical and Electronic Engineering from the University of Manchester (with first class honors) and B.Eng in Electrical Engineering and Automation from Beijing Jiaotong University in 2014 via a joint ‘2+2’ dual-degree program. He also received D.Phil in Engineering Science from University of Oxford in 2018. Dr. Dang joined in the R&D Center, Huanan Communication Co., Ltd. after graduating from University of Oxford and then worked as a Postdoctoral Fellow with the Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST). He is currently a Lecturer with Department of Electrical and Electronic Engineering, University of Bristol. The research interests of Dr. Dang include 6G communications, wireless communications, wireless security, and machine learning for communications.
Please contact Rebecca Layland, Smart Internet Lab Project Coordinator - firstname.lastname@example.org for more information about this talk