Roberto Sacile

Roberto Sacile received a Laurea degree in electronic engineering from the University of Genova, Italy, in 1990 and the Ph.D. degree from Milan Polytechnic, Italy, in 1994. He is with University of Genova since 2000. He has been visiting scientist at Université de Technologie Compiègne (UTC), France, in 2013 and 2014. His main research interests are related to decision support methodologies and optimal control techniques with specific applications to energy, environmental and transport systems....See more

Roberto Sacile received a Laurea degree in electronic engineering from the University of Genova, Italy, in 1990 and the Ph.D. degree from Milan Polytechnic, Italy, in 1994. He is with University of Genova since 2000. He has been visiting scientist at Université de Technologie Compiègne (UTC), France, in 2013 and 2014. His main research interests are related to decision support methodologies and optimal control techniques with specific applications to energy, environmental and transport systems. During the last ten years of research, the scientific and scholarly work of Roberto Sacile has been devoted to the modelling of human activities on territorial systems, with specific reference to decision support systems (DSS) coupled with optimization and control techniques in different domains all related to risk management, system sustainability and sustainable development. The concept at the basis of his research is that a DSS must support decision makers (DM) filling the gap between the complexity of data which can be acquired by a proper "sensor? field, and the practical decisions which should be taken at strategic, tactical and operational level. His work focuses on practical current problems of nowadays society, with applications widening in different domains under a common matrix of risk management, sustainable land use and development. His current research idea is that risk management and sustainable development requires the support of a system of systems modelling approach where the different multidisciplinary aspects of the problem interact among themselves and are supported by specific measurable indicators. See less