时间

2019年11月20号 9:30-11:00

 

地点

北京大学王选所106会议室

 

介绍

Graph data are key parts of Big Data and widely used for modelling complex structured data with a broad spectrum of applications. Over the last decade, tremendous research efforts have been devoted to many fundamental problems in managing and analysing graph data. In this talk, I will focus on the three key problem, 1) efficiently computing subgraph mappings over large-scale graphs, 2) mining cohesive subgraphs, and 3) determining the resilience of graphs. I will cover applications and recent advantages.

 

简历

Xuemin Lin is a UNSW distinguished Professor - Scientia Professor, and the head of database and knowledge research group in the school of computer science and engineering at UNSW. Xuemin is a visiting Chair Professor at Fudan University. He is a fellow of IEEE. Xuemin's research interests lie in databases, data mining, algorithms, and complexities. Specifically, he is working in the areas of scalable processing and mining of large-scale data, including graph, spatial-temporal, streaming, text and uncertain data.

Xuemin currently serves as the editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (Jan 2017 - now). He was an associate editor of ACM Transactions Database Systems (2008-2014) and IEEE Transactions on Knowledge and Data Engineering (Feb 2013- Jan 2015), and an associate editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2015-2016), respectively.  He has been regularly serving as a PC member and area chairs/SPC in SIGMOD, VLDB, ICDE, ICDM, KDD, CIKM, and EDBT. He is a PC co-chair of ICDE2019 and VLDB2022.