Keynote Speaker
Dr. Sheng-Lung Peng, Professor
Department of Creative Technologies and Product Design, National Taipei University of BusinessSpeech Title: Domination-like Problems with Propagation Property
Abstract: Influence maximization is an important problem in the fields of social networks and data mining. Propagation is one of the important properties of this problem. In graph theory, the power domination problem is one of the few problems with propagation properties. This study combines the concepts of influence maximization and power domination problems. We propose some problems with propagation properties. For example, in the k-influence optimization problem, our goal is to find a seed set with the smallest size such that they can spread and influence everyone on the graph through their influence. In the problem, a person is influenced if his/her k friends are influenced. In this research, we consider this propagation property on domination-like problems.
Biography: Sheng-Lung Peng is a Professor at the Department of Creative Technologies and Product Design, and the Dean of the College of Innovative Design and Management, National Taipei University of Business in Taiwan. He received the PhD degree from Computer Science Department of National Tsing Hua University in Taiwan. He is an honorary Professor at Beijing Information Science and Technology University and a visiting Professor at Ningxia Institute of Science and Technology in China. He is also an adjunct Professor at National Dong Hwa University in Taiwan and Kazi Nazrul University in India. In addition, he is also an honorary adjunct professor in School of Management of Sir Padampat Singhania University and in School of Computer Science and School of Business of ITM (SLS) Baroda University. Dr. Peng has edited several special issues at journals, such as Frontiers in Public Health, Journal of Internet Technology, IEEE Internet of Things Magazine, Computers and Electrical Engineering, Journal of Information Science and Engineering, and so on. His research interests are algorithm design in the fields of artificial intelligence, bioinformatics, combinatorics, data mining, and networking.