Big Data in Complex and Social Networks

Dr. My T. Thai is a UF Research Foundation Professor and Associate Chair for Research in the Department of Computer and Information Sciences and Engineering at the University of Florida. She received her PhD degree in Computer Science from the University of Minnesota in 2005. Her current research interests include algorithms, cybersecurity, and optimization on network science and engineering, including communication networks, smart grids, social networks, and their interdependency. The results of her work have led to 5 books and 120+ articles published in various prestigious journals and conferences on networking and combinatorics. Dr. Weili Wu is a full professor in the Department of Computer Science, University of Texas at Dallas. She received her Ph.D. in 2002 and M.S. in 1998 from Department of Computer Science, University of Minnesota, Twin City. Her current research mainly deals with the general research area of data communication and data management. Her research focuses on the design and analysis of algorithms for optimization problems that occur in wireless networking environments and various database systems. She has published more than 200 research papers in various prestigious journals and conferences. Dr. Hui Xiong is currently a Full Professor of Management Science and Information Systems at Rutgers Business School and the Director of Rutgers Center for Information Assurance at Rutgers, the State University of New Jersey, where he received a two-year early promotion/tenure (2009), the Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence (2009), and the ICDM-2011 Best Research Paper Award (2011). Dr. Xiong is a prominent researcher in the areas of business intelligence, data mining, big data, and geographic information systems (GIS). For his outstanding contributions to these areas, he was elected an ACM Distinguished Scientist. He has a distinguished academic record that includes 200+ referred papers.

Introduction of Big Data. Big Data and prediction. Social networks and Big Data. Cloud computing and Big Data. Big Data and web intelligence. Visualization of Big Data. Mining Big Data. Security and privacy issues of Big Data. Programming models for Big Data. Big Data applications in social science, climate science, earth science and other science domains.