Honored to have received the Best Paper Award at EVACES 2025 (FEUP, Porto) on behalf of the first author, Leonardo Ferreira.
Leonardo Ferreira, Marcus Omori Yano, Laura Souza, Ionut Dragos Moldovan, Samuel da Silva, Rômulo Lopes, Carlos Cimini, joao weyl, Eloi Figueiredo (2025). Stochastic transfer learning strategy for monitoring twin concrete bridges. EVACES25, FEUP, Porto, Portugal.
We presented at the conference one of the most comprehensive scientific studies on structural health monitoring (SHM) that we are aware of, where a multidisciplinary team brought together:
- Stakeholder engagement (Brazilian bridge authority, DNIT),
- Operational modal analysis,
- Long-term monitoring using smartphone solutions (http://www.app4shm.com),
- Probabilistic finite element modeling through Bayesian Inference,
- Transfer learning for domain adaptation,
- Machine learning for damage detection.
A full version of this study was published at MSSP: https://doi.org/10.1016/j.ymssp.2025.112845
Grateful to the scientific committee and organizers (EVACES International Association, Maria Pina Limongelli, Álvaro Cunha) for this recognition and DEWEsoft (Rok Mesar) for sponsoring.
This work reflects the collaborative effort of a dedicated team committed to advancing SHM in bridge engineering!
Universidade Lusófona - Centro Universitário Lisboa (ULusófona), Universidade Estadual Paulista Ilha Solteira (UNESP), Universidade Federal do Pará Belém (UFPA), Universidade Federal de Minas Gerais (UFMG), FAPESP, CNPq, CAPES.
EVACES 2025: https://www.fe.up.pt/evaces2025/
RISE: https://rise.ulusofona.pt/
CERIS: https://ceris.pt/