[DB Seminar] Fall 2016: Prof. Shenghua Liu

With mobile and web-based techniques to create highly interactive platforms, social media becomes prevalent  in our daily life. It sees the interaction among people in which they create, share, discuss, or exchange ideas in virtual communities and networks. In this talk, he will introduce a series of his previous research work related to social media. They range from understanding short text, opinions, users’ influences, and network structures. Among those topics there is one principle philosophy undergoing them, which is learning features from data itself, i.e. text, propagation cascades, and connectiveness of networks. He would like to share the success of feature/representation learning, expecting that it can bring benefits to the projects you are working on, and the potential cooperation in the related or other research areas.

Bio:
Shenghua Liu is an associate professor at Institute of Computing Technology(ICT), Chinese Academic of Sciences (CAS). He is now spending his one-year visit at Computer Science Department, Carnegie Mellon University(CMU) as a research scholar, working with Professor Christos Faloutsos. He received his Ph.D. degree from Tsinghua University in 2010, and visited University of California, Los Angeles (UCLA) for more than a year as a Ph.D. student. His current research interests are solving the real data mining and machine learning problems, related to computation and optimization of big graphs and series.