Valentina Giglioni | Learning Structures: How Artificial Intelligence is redefining Structural Health Monitoring

​The Center for Urban Science + Progress (CUSP) at NYU Tandon welcomes you to attend the lecture "Learning Structures: How Artificial Intelligence is redefining Structural Health Monitoring" by Valentina Giglioni, a visiting postdoctoral researcher at NYU Tandon. This event will be held in the Brooklyn Conference Room, located on the 13th Floor of 370 Jay Street.

​​​​​About the Lecture

​This talk will focus on Structural Health Monitoring (SHM) of bridges, starting from the scale of a single asset and progressively expanding to network-level monitoring strategies. At the individual bridge level, key challenges related to damage detection and classification will be discussed, with particular emphasis on the use of artificial intelligence algorithms and the extraction of damage-sensitive features. The presentation will then move toward large-scale monitoring frameworks, highlighting approaches for managing and analyzing bridge networks through knowledge transfer strategies. These methods enable the efficient use of data across multiple structures, improving the scalability and robustness of SHM systems. Real-world case studies will be presented, including both laboratory-controlled experiments and full-scale bridges. These examples will showcase ongoing monitoring campaigns and demonstrate the practical implementation of SHM techniques, with the main challenges associated.

​​About the Speaker 

​Valentina Giglioni is a Civil Engineer specialized in Structural Engineering. She graduated cum laude in 2020 and obtained her PhD in 2024, both from the University of Perugia, Italy. Her research focuses on the development of knowledge-based Structural Health Monitoring (SHM) strategies, with particular attention to damage detection and classification. Her work involves the analysis of both dynamic and static structural response signals, aiming to extract meaningful information for assessing structural integrity. A key aspect of her research is the integration of artificial intelligence techniques to enhance monitoring performance and data interpretation.

​​​​​Visitor Information

​​​​​This event will be held in the Brooklyn Conference Room, located on the 13th Floor of 370 Jay Street. Please visit the NYU Tandon website for directions and a campus map. Advance registration through Luma is required for campus access at NYU for external guests.