Huan Liu

Title: The Good, the Bad and the Ugly: Uncovering Novel Opportunities of Data Science

Abstract:

Big data is ubiquitous and becomes bigger, and challenges traditional data mining and machine learning methods. Social media is a new source of data that is significantly different from conventional ones. Social media data is mostly user generated, and is big, linked, and heterogeneous. We present the good, the bad and the ugly associated with the multi-faceted social media data, exemplify the importance of data reduction and inferring invisible information with real-world examples, and illuminate new opportunities of developing novel algorithms and tools for data mining and machine learning. In our endeavor of taming the bad and the ugly with the help of the good, we deepen our understanding of ever growing and evolving data and generate innovative solutions with interdisciplinary, collaborative research.

Short bio:

Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He obtained his Ph.D. in Computer Science at University of Southern California and B.Eng. in Computer Science and Electrical Engineering at Shanghai JiaoTong University. Before he joined ASU, he worked at Telecom Australia Research Labs and was on the faculty at National University of Singapore. At Arizona State University, he was recognized for excellence in teaching and research in Computer Science and Engineering and received the 2014 President's Award for Innovation. His research interests are in data mining, machine learning, social computing, and artificial intelligence, investigating interdisciplinary problems that arise in many real-world, data-intensive applications with high-dimensional data of disparate forms such as social media. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He is a co-author of Social Media Mining: An Introduction by Cambridge University Press. He serves on journal editorial boards and numerous conference program committees, and is a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction. He is an IEEE Fellow. More information can be found here.