Shui Yu

Shui Yu obtained his PhD from Deakin University, Australia, in 2004. He currently is a Professor of School of Computer Science, University of Technology Sydney, Australia.

Dr Yu’s research interest includes Big Data, Security and Privacy, Networking, and Mathematical Modelling. He has published four monographs and edited two books, more than 460 technical papers, including top journals and top conferences, such as IEEE TPDS, TC, TIFS, TMC, TKDE, TETC, ToN, and INFOCOM. His h-index is 61. Dr Yu initiated the research field of networking for big data in 2013, and his research outputs have been widely adopted by industrial systems, such as Amazon cloud security.

He is currently serving a number of prestigious editorial boards, including IEEE Communications Surveys and Tutorials (Area Editor), IEEE Communications Magazine, IEEE Internet of Things Journal, and so on. He was a Distinguished Lecturer of IEEE Communications Society (2018-2021).

He is an elected member of Board of Governor of IEEE Vehicular Technology Society, a voting member of IEEE ComSoc Educational Services Board, and a Distinguished Visitor of IEEE Computer Society.

Email: shui.yu@uts.edu.au

DVP term expires December 2024

Presentations

Cybersecurity and Privacy: State-of-Art, Challenges, and Opportunities

Cybersecurity and privacy are two hot topics in our society. However, both of them are mainly uncharted territories, and we have far more questions than answers from applications all the way to theories. In this talk, we review the state-of-art of the fields based on two research topics: distributed denial of service and big data privacy, respectively, aiming to present the audience an overview of the current battleground. We also discuss the problems and challenges that we are facing, and explore the possible promising directions in the fields.

Big Data Privacy: from Networking and Artificial Intelligence Perspectives

Big data is a revolution for our society. However, it also introduces a significant threat to our privacy. In this talk, we firstly present the essential issues of privacy preserving in the big data setting, then we review the current work of the field from two perspectives: networking and artificial intelligence. Then we discuss the challenges in the domain and possible promising directions. We humbly hope this talk will shed light for forthcoming researchers to explore the uncharted part of this promising land.