Álvaro Sicilia

Partner

La Salle-URL

Álvaro Sicilia is a researcher of the ARC Engineering and Architecture La Salle research group. He holds a PhD in Computer Science from Ramon Llull University and is a professor of the databases course at La Salle engineering school. With active participation in numerous national and European projects such as INTUBE, REPENER, SEMANCO, OPTIMUS, ENERSI, OPTEEMAL, TIMEPAC, and ACCORD, Álvaro has gained extensive experience in the management and analysis of energy-related data for buildings, particularly utilising Semantic Web technologies. He currently co-coordinates the national research project Retabit, while actively participating in the TIMEPAC and ACCORD projects.

Σχετικές εκπαιδευτικές δραστηριότητες

14 Mar. 2024

Webinar 4. Combining EPC databases with other sources for holistic assessment of the building stock
Περισσότερα

Session

Quality assessment of the EPC database contents

Session

Advanced analysis of EPC data as a support tool for local, regional and national energy planning

20 Mar. 2024

Webinar 5. Exploitation of EPC for local, regional and national energy planning
Περισσότερα

Session

Identification and collection of relevant data from EPC databases to map the energy status of the building stock

29 Feb. 2024

Webinar 1. EPC data collection, validation and exploitation
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Session

Data extraction from the multiple sources

05 Mar. 2024

Webinar 2. Advanced methods and tools for holistic energy renovation of buildings
Περισσότερα

Session

Generating enhanced EPC with BIM data

07-09 May. 2024

Combining EPC databases with other sources for holistic assessment of the building stock
Περισσότερα

Session

Quality assessment of EPC databases

Session

EPC data combination for multi-dimensional analysis of the building stock

Session

Advanced analysis of EPC data to create building renovation plans

23-30 May. 2024

Advanced methods and tools for energy rehabilitation of buildings from a holistic perspective
Περισσότερα

Session

Generating enhanced EPC with BIM data

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