报告人简介：

Dr. My T. Thai is an 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 leading journals and conferences on networking and combinatorics.

报告简介：

With billions of active users, Online Social Networks (OSNs) have become critical platforms for marketing and advertising. At the same time, OSNs are also a fruitful soil for criminals to harvest billions of users’ personal information. With such a big and incomplete data, it becomes very challenging to mine the OSNs. In this talk, I address the above problems via two primary approaches: 1) Develop novel dynamic sampling techniques with the performance bound guarantee to exactly perform the big data mining in large-scale networks with billions nodes; and 2) Develop active learning methods via adaptive stochastic optimization to best enhance the incomplete network within budget constraints. To confirm the practical uses of these mathematical techniques, we apply them to solving many real-world problems, mainly focused on the network security such as social-bot detection, misinformation spreading, and privacy leakage.