Speaker: Prof. Liu Kai

Time: 2:30-3:30p.m., 17 May 2021 (Mon)

Venue: T2-202

Language: Chinese

Abstract：

The emerging networking paradigms such as software defined network (SDN) and edge computing, together with the recent breakthroughs in artificial intelligence, inspire us to envision a new era of Internet of Vehicles (IoV). Nevertheless, there are still significant challenges to realize and fulfill emerging intelligent transportation systems (ITSs), which impose stringent requirements on real-time processing, fast reaction, intensive computation and big data analytics. In this talk, we will discuss key technologies for enabling collaborative intelligence in IoV, considering its unique characteristics including high node mobility, dynamic network topology, uncertain vehicular connectivity, and heterogeneous network resources, etc. Then, we will present our recent research on service architectures and scheduling algorithms for cooperative data dissemination and task offloading in IoV. Finally, we will show system prototypes of typical ITS applications.

About the speaker:

Dr. Liu Kai is currently a Full Professor in the College of Computer Science, Chongqing University, China. He received his Ph.D. degree in Computer Science from City University of Hong Kong in 2011. From December 2010 to May 2011, he was a Visiting Scholar with the Department of Computer Science, University of Virginia, USA. From 2011 to 2014, he was a Postdoctoral Fellow with Nanyang Technological University, Singapore, City University of Hong Kong and Hong Kong Baptist University. His current research interests include Internet of Vehicles, Mobile Edge Computing, Pervasive Computing, Computation Intelligence and Intelligent Transportation Systems, etc. He has published over 110 prestigious peer-reviewed journals and conference proceedings. Among them, there are 49 journal papers ranking in Clarivate Journal Citation Reports (JCR) Q1, and 32 IEEE/ACM Transactions, including IEEE/ACM ToN, IEEE TMC, IEEE TVT, IEEE TITS, IEEE TII, etc. He has graduated 5 PhD students and 8 postgraduate students at CQU.