Complex networks meet data science

PI: Justo Puerto Albandoz

Acronym: NetmeetData

Abstract: The main goal of this project is to integrate techniques available in mathematical programming, machine learning, artificial intelligence, combinatorial optimization, operations research and statistics, to address essential problems associated with the management and use of large scale complex networks and data science. The scientific analysis of problems arising in applied sciences, like operations management, finance, sociology and political sciences will lead us to select, define and code the most appropriate solution techniques, including specific algorithms to solve applied research problems. The achievement of this goal will imply to advance on the knowledge of some problems and models in data science and conversely moving ahead the frontiers on the sizes of instances and level of integration considered in the operational analysis of large scale complex network. This is our secondary goal. These two goals have to be addressed jointly and cannot be separated. Indeed, any advance done in data science models will have a direct implication on the operational aspects of many problems on network; and the analysis of the operational aspects of networks’ models will shed light on new models to be considered within the data science paradigm.