Eunice E. Santos (Illinois Institute of Technology, USA)
Title: Incorporating Social-Cultural Factors and Dynamic Information in Social Networks
Abstract: This talk focuses on computational social systems; specifically on how to systematically represent socio-cultural factors, their infusion into social network representations and models, a new paradigm for designing and analyzing the efficiency and efficacy of methodologies dealing with dynamic information, and application to real-world scenarios. Specifically we will present a framework which can infuse various forms of information within computational representations that allow for incomplete knowledge which leads to more effective and meaningful social networks analyses, and we will present methods for social networks analyses that deal with dynamically changing information. Lastly, we refer to such new network structures as Culturally-Infused Social Networks (CISN).
Bio: Eunice E. Santos is the Ron Hochsprung Endowed Chair and Professor at the Illinois Institute of Technology. She is also the Department Chair of Computer Science. She was a professor at Virginia Tech, Lehigh University, and UTEP, and was a Senior Research Fellow for the Department of Defense Center for Technology and National Security Policy. She has served as the Director of the National Center for Border Security and Immigration, Director of the Center for Defense Systems Research, and Founding Director of the Institute of Defense & Security at UTEP. She is a recipient of the IEEE Computer Society Technical Achievement Award (for pioneering work in Computational Social Systems). She has also received an NSF Career Award, the Robinson Faculty Award, the Spira Award for Excellence in Teaching, and other awards. She is a past member of the IDA/DARPA Defense Science Study Group. She is the Founding co-Editor-in-Chief of the new IEEE Transactions on Computational Social Systems. She received her PhD in Computer Science from the University of California, Berkeley. She also has BS and MS degrees in both Mathematics and Computer Science. She is a Fellow of AAAS.
My T. Thai (University of Florida, USA)
E-mail: mythai [a-t] cise.ufl.eduTitle: Viral Marketing: A Road to Billion-scale Networks
Abstract: One of the most fundamental problems in viral marketing is Influence Maximization (IM), which seeks to find a set of k initial seed users in a network so as to maximize the size of influenced users. Despite the huge amount of effort, IM in billion-sale networks such as Facebook, Twitter, and WWW has not been satisfactorily solved. In this talk, we will discuss a road to achieve a quasi-linear time algorithm while guaranteeing the best approximation ratio (1 - 1/e - ε) to the IM problem.
Bio: Dr. My T. Thai is a 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 100+ articles published in leading journals and conferences on networking and combinatorics.
Prof. Thai has engaged in many professional activities. She has been a TPC-chair for many IEEE conferences, has served as an associate editor for Journal of Combinatorial Optimization (JOCO), Optimization Letters, Journal of Discrete Mathematics, IEEE Transactions on Parallel and Distributed Systems, and a series editor of Springer Briefs in Optimization. Recently, she has co-founded and co-EiC of a Computational Social Networks journal. She has received many research awards including an UF Provosts Excellence Award for Assistant Professors, a Department of Defense (DoD) Young Investigator Award, and an NSF (National Science Foundation) CAREER Award.
