Vitor Sousa is a Professor at ULisboa-IST and a research member at the CERIS research unit. He is a civil engineer (2001) who specializes in hydraulics and has an MSc in construction (2003) and a PhD in civil engineering (2012). He was a Fulbright Scholar at the University of California at Davis (2010) in the field of computer fluid dynamics and a Fundacion Carolina scholar at the Universitad Rey Juan Carlos (2019) in the field of life cycle assessment. His research involves mostly data and uncertainty modeling to improve/aid the management of physical assets, which encompasses various topics, such as degradation modeling, water and energy efficiency, the water–energy nexus, carbon reduction in construction materials and waste management. Artificial intelligence tools, such as artificial neural networks or support vector machines, are amongst the data modeling techniques used to promote/benefit from the digital transition in civil engineering.
Research Keywords & Expertise
Life Cycle Assessment
Water Efficiency
Data Minning
Water–energy nexus
Life cycle costing
Water consumption patt...
Alternative water sour...
Fingerprints
Water Efficiency
Water consumption patterns
Life Cycle Assessment
Water–energy nexus
Life cycle costing
Alternative water sources
Short Biography
Vitor Sousa is a Professor at ULisboa-IST and a research member at the CERIS research unit. He is a civil engineer (2001) who specializes in hydraulics and has an MSc in construction (2003) and a PhD in civil engineering (2012). He was a Fulbright Scholar at the University of California at Davis (2010) in the field of computer fluid dynamics and a Fundacion Carolina scholar at the Universitad Rey Juan Carlos (2019) in the field of life cycle assessment. His research involves mostly data and uncertainty modeling to improve/aid the management of physical assets, which encompasses various topics, such as degradation modeling, water and energy efficiency, the water–energy nexus, carbon reduction in construction materials and waste management. Artificial intelligence tools, such as artificial neural networks or support vector machines, are amongst the data modeling techniques used to promote/benefit from the digital transition in civil engineering.
