Graph Processing and Mining in the Era of Big Data
报告题目: Graph Processing and Mining in the Era of Big Data
报告人: Chengqi Zhang 教授
With the emergence and rapid proliferation of applications that deal with big graphs, such as web graphs (Google, Yahoo), social networks (Facebook, Twitter), e-commerce networks (Amazon, Ebay), and road networks, graph processing and mining has become increasingly prevalent and important in recent years. However, in the era of big data, the explosion and profusion of available graph data in a wide range of application domains rise up new challenges and opportunities in graph processing and mining.
Graph processing and mining is one of the research strengths in the centre for Quantum Computation and Intelligent Systems (QCIS) at the University of Technology, Sydney (UTS). In this talk, I will first investigate the new challenges for graph processing and mining in the era of big data. To tackle these challenges, I will introduce the recent research developments in QCIS in terms of new graph query semantics, new graph mining tasks, new query processing algorithms, new graph indexing techniques, and new computing paradigms. Finally, I will show our current achievements in building a general-purpose graph processing and mining system in QCIS centre, and discuss our potential future research directions.
Chengqi Zhang has been appointed as a Research Professor of Information Technology at The University of Technology Sydney (UTS) since December 2001. He has been the Director of the UTS Research Centre for Quantum Computation & Intelligent Systems (QCIS) since April 2008.
Chengqi Zhang obtained his PhD degree from the University of Queensland in 1991, followed by a Doctor of Science (DSc – Higher Doctorate) from Deakin University in 2002, all from computer science.
He had been appointed by University of New England (UNE) from 1990 to 1998 as Lecturer, Senior Lecturer, and Associate Professor, then Deakin University from 1999 to 2001 as Associate Professor, then UTS from 2002 till now as Research Professor.
Prof. Zhang’s key areas of research are Distributed Artificial Intelligence, Data Mining and its applications. He has published more than 200 refereed research papers, including a number of papers in the first-class international journals, such as Artificial Intelligence, IEEE and ACM Transactions. He has delivered 14 keynote/invited speeches at international conferences over the last eight years. He has attracted 12 ARC grants of $4.7M. He has supervised 30+ PhD students in completion. He received NSW State Science and Engineering Award in Engineer and ICT category in 2011 and also UTS Chancellor research excellence award in Research Leadership category in 2011.
Prof. Zhang is a Fellow of the Australian Computer Society (ACS) and a Senior Member of the IEEE Computer Society (IEEE). He had been serving ARC as an ARC College of Expert from 2012 to 2014. He has been the Chair of the Australian Computer Science National Committee on Artificial Intelligence from 2005 till now. He was General Co-Chair of PAKDD 2014, WI/IAT 2018, ICDM 2010, and KDD 2015. He is also Local Arrangements Chair of IJCAI 2017.