Minho University - Portugal
Author's Profile
Summary
Professor José C. Matos is a prominent Portuguese civil engineer, academic, and scientific leader, known for his expertise in infrastructure asset management, structural reliability, and risk analysis. With a career that blends teaching, advanced research, and international collaboration, he currently serves as an Assistant Professor with Habilitation at the University of Minho, Portugal. His contributions span multiple domains, including sustainable infrastructure systems, critical asset monitoring, and decision-making under uncertainty. He is recognized for fostering innovation and cross-border collaboration in civil engineering and for leading several national and European-level infrastructure initiatives.
Educational Details
Professor Matos earned his Ph.D. in Civil Engineering from the University of Minho between 2003 and 2007, with a specialization in safety and reliability analysis. His doctoral studies included a research exchange at the University of Girona, Spain. Prior to that, he obtained his Bachelor's Degree in Civil Engineering from the University of Porto in 2002, where he graduated among the top 10% of his class, earning recognition from the university for academic excellence.
Professional Experience
His academic career began in 2002 as a Junior Teaching Assistant at the University of Porto and later at the University of Minho. He progressed through various academic roles, becoming an Assistant Professor with Habilitation in 2013 at the Department of Civil Engineering, University of Minho. In addition to his teaching and research, he has worked as a Structural Engineer at GEG – Engineering Consulting. Professor Matos has held leadership roles in several influential bodies, including Vice President of the International Association for Bridge and Structural Engineering (IABSE), Director of the TMOB Mobility and Transportation HUB, and Head of the Risk and Asset Management on Civil Infrastructures Cluster (RAmCI). He is also an active board member of organizations such as APEE, OERN, and ANJE.
Research Interests
Professor Matos’s research spans a wide range of civil engineering domains, focusing particularly on asset management, lifecycle cost analysis, risk-based decision-making, and structural safety. He is a pioneer in applying probabilistic and data-driven methods to evaluate the performance and resilience of infrastructures. His work also includes developing tools for structural health monitoring, optimization of maintenance strategies, and improving the robustness and sustainability of transport and civil infrastructure systems.
Author Metrics
An accomplished scholar, Professor Matos has authored or co-authored more than 82 peer-reviewed journal articles indexed in ISI and Scopus and over 160 international conference papers. His research has gained wide recognition, with many of his works being highly cited, including top papers in Structural Safety, Engineering Structures, and Advances in Civil Engineering. He has delivered over 100 keynote speeches at international conferences and has lectured extensively worldwide. He maintains active research profiles on platforms such as ORCID (0000-0002-1536-2149), Scopus (36848395500), and Web of Science (ResearcherID: F-1917-2015), with consistent citation metrics reflecting his impact in the field.
Awards and Honors
Professor Matos has received numerous prestigious awards for his academic and scientific achievements. These include the Senior Scientist Award at the EUROSTRUCT Conference in 2021 and two Outstanding Scientific Article Awards from IABSE in 2022. He was honored with the European Union Merit Award in 2021 by the Organization of Young Entrepreneurs of the EU and AJEPC. The University of Minho awarded him Diplomas of Merit for Scientific Publication in both 2022 and 2023. His academic excellence was also recognized early in his career with a Top 10% Graduate Award from the University of Porto in 2002.
Publication Top Notes
1. Bridge Deterioration Prediction Models Using Artificial Intelligence in a Missing Data Scenario
Authors: CAF Souza, JMF de Carvalho, MHF Ribeiro, ACP Martins, FG Bellon, JC Matos
Published in: Structures, Volume 77, Article 109112, 2025
Summary:
This study presents innovative AI-driven models to predict bridge deterioration even when key inspection data is missing. The approach enhances the reliability of maintenance planning by leveraging machine learning and data imputation techniques to fill information gaps commonly found in infrastructure monitoring systems.
2. Drive-By Detection of Scour in a Railway Bridge
Authors: S Tola, E O’Brien, D Cantero, J Tinoco, JC Matos, T Bose, J Berkers
Published in: Journal of Bridge Engineering, Volume 30, Issue 7, Article 04025043, 2025
Summary:
This paper explores a non-invasive "drive-by" method for detecting scour in railway bridges using data collected from sensors on moving vehicles. The method significantly reduces inspection costs and time, while improving detection accuracy for early-stage scour-induced damage.
3. Scour-Induced Stability Risks of the Zogu Bridge: Preservation Challenges and Policy Recommendations for a Threatened European Heritage
Authors: E Periku, O Korini, E Luga, E Baron, JC Matos, A Kuriqi
Published in: Innovative Infrastructure Solutions, Volume 10, Issue 6, Pages 1–15, 2025
Summary:
Focusing on the historic Zogu Bridge, this study evaluates the scour-related stability risks threatening its structural integrity. The paper also discusses broader implications for heritage preservation, offering technical and policy recommendations for mitigating risks to aging European infrastructure assets.
4. Automating Inspection Data from Bridge Management System into Bridge Information Model
Authors: C Santos, F Luleci, J Amado, JC Matos, FN Catbas
Published in: Automation in Construction, Volume 174, Article 106128, 2025
Summary:
This research integrates bridge inspection data from Bridge Management Systems (BMS) into Building Information Modeling (BIM) platforms. The automation facilitates data-driven decision-making and supports predictive maintenance strategies, improving digital asset management for infrastructure operators.
5. Evaluating the Influence of Wind on UAV Path Planning for Bridge Inspections
Authors: E Aldao, G Fontenla-Carrera, F Veiga-López, H González-Jorge, JC Matos, et al.
Presented at: 2025 International Conference on Unmanned Aircraft Systems (ICUAS), Pages 236–242
Summary:
This conference paper analyzes how wind conditions affect UAV (drone) flight planning during bridge inspections. The research contributes to optimizing UAV navigation algorithms for accurate and safe data acquisition, especially in challenging environmental conditions often encountered during field inspections.
Conclusion
In conclusion, Professor José C. Matos is an outstanding candidate for the Distinguished Scientist Award. His blend of academic rigor, applied innovation, leadership, and international engagement has made significant contributions to the field of civil and structural engineering. His work on AI-based bridge assessment, infrastructure resilience, and digital asset management reflects both scholarly depth and practical relevance.