Advancing Digital Engineering Through Research
At CAEmate, research is a strategic driver of innovation. Through collaborations with universities, research institutions, and international consortia, we develop advanced technologies that transform scientific knowledge into practical solutions for engineering, infrastructure monitoring, and digital asset management.
Over the years, our participation in European, national, and regional research projects has strengthened our expertise in Digital Twins, Structural Health Monitoring (SHM), numerical simulation, and Artificial Intelligence. These collaborations create a continuous innovation ecosystem that supports the development of next-generation engineering technologies.
Beyond technological advancement, research activities foster knowledge exchange, technology transfer, and the development of scientific expertise that directly benefits the engineering and infrastructure sectors.
Academic Partners
CAEmate collaborates with leading universities and research organizations to address complex engineering challenges and accelerate innovation in digital engineering technologies.
Our network includes:
Aberystwyth University (United Kingdom)
Technische Universität Dortmund (Germany)
University of Bolzano (Italy)
University College London (United Kingdom)
Eurac Research
University of Trento (Italy)
Together, these partnerships bring expertise in structural engineering, numerical modelling, materials science, geotechnics, and Artificial Intelligence, creating an international research environment focused on scientific excellence and real-world impact.
Research Areas
Our research activities focus on developing advanced digital technologies for civil, industrial, and infrastructure engineering.
Key research domains include:
Physics-Based Digital Twins
Developing digital replicas capable of accurately representing the behaviour of physical assets through simulation and real-world data integration.
Structural Health Monitoring (SHM)
Creating intelligent monitoring systems that support condition assessment, anomaly detection, and infrastructure safety.
Multi-Physics Numerical Simulation
Applying advanced computational models to analyse complex structural, thermal, and geotechnical phenomena.
IoT and Data Integration
Connecting sensor networks with computational models to create data-driven engineering workflows.
Artificial Intelligence and Physics-Informed AI
Combining machine learning with engineering principles to improve prediction accuracy and decision-making.
Digital Engineering Workflows
Enhancing engineering processes through digital platforms, simulation tools, and performance assessment methodologies.
Predictive Maintenance and Asset Management
Developing methodologies that support proactive maintenance strategies and lifecycle optimization.
European and National Research Projects
WeStatiX SHM – Digital Twins, Real-Time Monitoring and Physics-Informed AI
WeStatiX SHM represents CAEmate’s vision for the future of infrastructure monitoring.
The project combines Physics-Based Digital Twins, real-time sensor data, and Physics-Informed Artificial Intelligence to support structural assessment, anomaly detection, and predictive maintenance. Through advanced numerical modelling and automated model updating, WeStatiX SHM strengthens the connection between scientific research and industrial innovation.
GeoRisk-AID – Geomechanical Digital Twins for Risk Mitigation
Funded through the Italian National Recovery and Resilience Plan (PNRR), GeoRisk-AID focuses on developing geomechanical Digital Twins capable of monitoring and predicting geotechnical instability phenomena.
By integrating numerical simulation and Artificial Intelligence, the project supports innovative approaches to natural hazard assessment, risk management, and infrastructure resilience.
FAIR – Digital Technologies for Ventilated Façade Performance
The FAIR project develops digital methodologies for the verification, monitoring, and performance assessment of ventilated façade systems throughout their lifecycle.
The project demonstrates CAEmate’s commitment to applied research, digitalization, and advanced simulation technologies that improve building performance and reliability.
Horizon 2020 RE-FRACTURE2 – Computational Modelling for Advanced Materials
Within the Horizon 2020 framework, CAEmate contributes to the development of computational models for innovative refractory materials used in high-temperature industrial applications.
The project highlights our expertise in numerical simulation, predictive modelling, and software development while promoting more efficient and sustainable engineering solutions through international collaboration.
Research Impact
Continuous participation in collaborative research initiatives enables CAEmate to:
• Build and strengthen an international scientific network;
• Advance expertise in Digital Twins, Structural Health Monitoring, Artificial Intelligence, and numerical simulation;
• Develop innovative technologies for infrastructure monitoring and predictive analysis;
• Accelerate technology transfer between academia and industry;
• Foster multidisciplinary collaboration across engineering and research communities;
• Increase innovation capacity through continuous engagement with universities and research institutions.
Today, research remains a strategic asset that drives the development of our technologies and creates new opportunities for innovation, collaboration, and scientific advancement.
Scientific Dissemination and Knowledge Exchange
Research is inherently collaborative.
Through European, national, and regional research programmes, CAEmate actively contributes to scientific dissemination, technology transfer, and the development of innovative engineering methodologies. By working closely with universities, researchers, and industry partners, we help bridge the gap between academic excellence and practical application.
The knowledge generated through research activities continuously supports the evolution of Digital Twins, Structural Health Monitoring systems, Artificial Intelligence applications, and advanced engineering software.
For CAEmate, investing in research means investing in knowledge, technological excellence, and the future of digital engineering.
