Giulia Delo

Dottoranda in Ingegneria Aerospaziale , 37o ciclo (2021-2024)
Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS)

Docente esterno e/o collaboratore didattico
Dipartimento di Ingegneria Strutturale, Edile e Geotecnica (DISEG)


Dottorato di ricerca


Interessi di ricerca

Machine learning
Population-based structural health monitoring
Structural dynamics
Structural health monitoring


Since starting my Civil Engineering studies at the Politecnico di Torino, I have become increasingly interested in the dynamic behaviour of structures. After my Master's Degree, I realised my passion for research and interest in exploring new, more challenging systems. Therefore, I applied for a PhD position in Aerospace Engineering, trying to exploit my previous knowledge and expertise in aircraft Structural Health Monitoring. The project objective is to reduce failures by developing a reliable Structural Health Monitoring technique using a population-based approach (PBSHM), for creating diagnostic systems across fleets of similar structures. In this framework, I focus on transferring data between so-called heterogeneous populations adopting transfer-learning and domain adaptation algorithms, and assessing structural similarity via graph-based approaches. In addition, my research program involves experimental activities on a heterogeneous population of small-scale aircraft models for validating the PBSHM approach. During these years, I had the chance to collaborate with the University of Sheffield as a visiting PhD student, which has been very valuable and has allowed me to broaden my vision and knowledge.



Goal 9: Industry, Innovation, and Infrastructure
Goal 11: Sustainable cities and communities

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