Courses

Type: disciplinary and multidisciplinary training

Doctoral Credits: 5

Teaching hours: 24

Schedule: September 2025

Topics: The course introduces the students to basic principles to develop a monitoring infrastructure, ranging from sensors deployment to data acquisition and processing.

Type: seminar

Doctoral Credits: 1

Teaching hours: 4

Schedule: 23 and 25 January 2025

Topics: Introduction to the fundamental aspects of elastic wave propagation in periodic structures. Computational techniques to extract the band structures properties of continuos periodic systems will be presented. In particular, the course will focus on Finite Element based techniques for band structure calculation, as the Wave Finite Element method and the Bloch operator Finite Element method.

Type: disciplinary and multidisciplinary training

Doctoral Credits: 2

Teaching hours: 8

Schedule: 28 and 30 January 2025

Topics: Introduction to time-frequency representations (TFRs) including advanced Unitary operators such as the Warped Frequency Transform (WFT). Sparse representations of GW signals and compressive sensing for super-resolved representations.

Type: disciplinary and multidisciplinary training

Doctoral Credits: 3

Teaching hours: 15

Schedule: June 2025

Topics: The course introduces techniques and tools for the design of data analytics processes for IoT applications through the Python language. It reviews the main stages of an IoT data pipeline: i.e. data acquisition, data visualization, data pre-processing, knowledge extraction through Machine Learning (ML) algorithms. After a brief recap of basic Python programming concepts, it presents the most used libraries for the processing of tabular and vectorial data and for the 2D plotting. Then, it introduces selected data processing and learning techniques for IoT time-series classification/forecasting. Datasets and case studies related to IoT-based monitoring applications (SHM and smart agriculture) will be considered.

Type: disciplinary and multidisciplinary training

Doctoral Credits: 5

Teaching hours: 24

Schedule: July 2025

Topics: This course will cover fundamental methods for dynamic structural identification and vibration-based health monitoring. Specifically, it will explore how to use recorded structural responses (e.g., strains, deflections, accelerations) to identify structural features and assess structural conditions. Common strategies for anomaly detection and damage identification will be discussed. Theoretical lectures will be complemented by hands-on activities featuring real-world and numerical examples.