The 1st FOURIER Training School will take place from 3–5 February 2026 at Valentino Castle, part of the Faculty of Architecture of the Politecnico di Torino.
The event will bring together PhD candidates, academic researchers, and industry professionals for a three-day programme focused on learning, knowledge exchange, and professional development, supporting participants in their ongoing and future doctoral research.
During the Training School, participants will attend a series of lectures on AI infrastructure monitoring and resilience. In addition, DCs will present their doctoral research concepts, outlining their planned research approaches, expected outcomes, and future directions.
The programme will also include site visits to the Marchetti Viaduct in Pavone Canavese, a 250-meter-long steel, single-span tied-arch motorway bridge and to the Joint Research Centre (JRC) in Ispra, providing insights into real-world infrastructure and applied research environments.
Guest Lectures:
- Prof. Eleni Chatzi (ETH Zurich) – Adaptive Digital Twins for Resilient Infrastructure — From Models to Monitoring to Intelligent Decision Making. The lecture will explore how structure-aware learning and data reduction methods can enable scalable, interpretable infrastructure monitoring and support resilient decision-making using digital twins and multimodal data.
- Prof. Enzo Martinelli (Università di Salerno) – On the use of Genetic Algorithms for selecting the optimal seismic upgrading solution for existing RC structures. The lecture focuses on optimizing seismic retrofitting strategies for existing reinforced concrete buildings using genetic algorithms that balance structural performance with economic and environmental costs.
- Prof. Vincenzo Gattulli (Sapienza University of Rome) – Hybrid AI-Driven Digital Twins for Structural Health Monitoring: Physics-Informed Learning, Synthetic Data, and Uncertainty-Aware Deployment. The lecture presents a hybrid AI-driven Digital Twin framework for structural health monitoring that integrates physics-based models, synthetic data, and uncertainty-aware methods to support reliable, life-cycle decision-making for civil infrastructure and heritage assets.
- Xinzheng Lu (Tsinghua University) –“Knowledge-Mechanics” Integrated Generative-AI Design Method for Civil Infrastructures. This lecture introduces a knowledge-integrated generative AI approach for civil infrastructure design that combines engineering mechanics and design codes with AI to enable reliable, automated structural solutions across multiple application domains.
Consortium Lectures:
- Dr. Daniele Inaudi (Smartec) – Fiber Optic Sensor for Structural Health Monitoring. The lecture introduces fiber optic sensing technologies for structural health monitoring and demonstrates their real-world applications for monitoring and managing civil infrastructure.
- Prof. Andrea Bottino (Politecnico di Torino) – XR and AI for Procedure Learning: Adaptive, Immersive, and Intelligent Training Systems. The workshop is focused on how Extended Reality and Artificial Intelligence can be integrated to support effective, adaptive, and user-centered training for complex procedural tasks through immersive learning environments.
- Prof. Edoardo Patti (Politecnico di Torino) – Enabling technologies to Move from Digital Models to Digital Twin. The course introduces the key concepts and technologies for developing data-driven Digital Twins of complex systems, including co-simulation, model integration, and IoT-based real-time monitoring.
- Prof. Micaela Demichela (Politecnico di Torino) – Multi-Risk Assessment as a Decision-Support Tool for Infrastructure–Environment Systems. A multi-risk assessment framework is presented to support infrastructure management by integrating hazard interactions, structural monitoring, and AI-based models, enabling risk-informed decision-making for resilient and adaptive infrastructure–environment systems.
- Marta Serrano & Ian Lister (CLA – Politecnico di Torino) – Communicating Your Research Effectively: Writing for publication in the age of AI. The lecture examines how AI and Large Language Models can support research writing, emphasizing critical literacy, authorial agency, and effective communication for PhD candidates in the age of AI.
- Prof. José Palma (University of Lisbon, The Equator Company) – All Disasters Are Equal, but Some Are More Equal Than Others: Rethinking the Empirical Foundations of Community Resilience. The presentation examines methodologies for assessing resilience and vulnerability in communities and individuals, highlighting conceptual gaps and proposing research directions to improve the measurement of adaptive capacity in the face of disasters.
