NOVA LINCS Group: Intelligent Systems Research Topics: Information systems; Business Intelligence; Databases; Ciber-Physical Systems Google Scholar: https://scholar.google.com/citations?user=WK0v0WEAAAAJ&hl=pt-PT&oi=ao José BARATEIRO is an expert in computer science, specializing in information systems. He holds the position of Professor at Universidade do Algarve, conducts research at Nova LINCS, and serves as an invited Professor at ISCTE - Instituto Universitário de Lisboa, where he teaches courses on decision support systems and data warehousing. He earned his Doctorate (Ph.D.) in Computer Science and Engineering from Instituto Superior Técnico - Universidade de Lisboa, focusing his research on information systems to support holistic risk management across multiple scenarios. He also holds a Master's degree in Computer Science and Engineering from the same institution, specializing in data quality and decision support systems. Previously, José served as the head of the Portuguese National Laboratory for Civil Engineering (LNEC) Research Unit on Information Technologies. He held key roles in various projects, including LNEC scientific coordination of the TIMBUS FP7 project and serving as Co-PI of the iLU project, which focused on Data Science and Artificial Intelligence in Public Administration, funded by FCT. Additionally, he contributed as a task/work package leader in several ICT research projects with EU and National funding. From a professional perspective, José coordinated the development and implementation of multiple information systems, particularly technical systems applied to civil engineering at a national level in Portugal. He also coordinated initiatives to design and/or develop national-level information systems in external countries such as Brazil and Mozambique. José has supervised/co-supervised 1 Ph.D thesis, 19 Master's theses and is currently co-supervising 3 Ph.D. theses and 9 Master's theses. From his publication record, which includes over 80 peer-reviewed publications, he received the best paper award at iPRES 2014, best student paper award at ICADL 2008 and a best paper nomination at HICSS-45. Selected publications: Antunes, A.L.; Barateiro, J.; Juan Mata; Tavares de Castro, A.; Caçador, F.;Cardoso, E. Machine learning applied to sensor data. Predictive methods used for dam behaviour interpretation. Lisboa: LNEC (2023). ISBN: 978-972-49-2324-6 Antunes, A.L.; Barateiro, J.; Mata, J.; Tavares de Castro, A.; Cardoso, E. Automatic outlier detection in sensor data used for structural health monitoring. Lisboa, Portugal: LNEC (2023) ISBN: 978-972-49-2325-3 Antunes, A.L.; Cardoso, E.; Barateiro, J. "Incorporation of Ontologies in Data Warehouse/Business Intelligence Systems - A Systematic Literature Review". International Journal of Information Management Data Insights vol 2 2 (2022) Mata, J.; Salazar, F.; Barateiro, J.; Antunes. A.L. "Validation of Machine Learning Models for Structural Dam Behaviour Interpretation and Prediction". Water vol 13 19 (2021) Rico, J.; Barateiro, J.; Mata, J., Antunes, A.L.; Cardoso, E. "Applying Advanced Data Analytics and Machine Learning to Enhance the Safety Control of Dams". In Learning and Analytics in Intelligent Systems, vol 1 315-350. Springer International Publishing (2019)