AI and data-driven infrastructures for workflow automation and integration in advanced research and industrial applications

The use of AI and data-driven technologies and infrastructures for innovation and development of advanced research and industrial applications requires a strong degree of integration across a broad range of tools, disciplines and competences. In spite of a huge disruptive potential, the role of AI for research and development in the context of industrial applications is often hampered by the lack of consolidated and shared practices for transforming domain-specific processes for generating knowledge into added value. These issues are particularly striking for small-medium enterprises (SMEs), which must adopt clear and effective policies for implementing successful technology transfer paths for innovation. The activities of the DAIMON Lab of the CNR-ISMN focus on the design, development, implementation and application of integrated modelling, data-driven and AI methods and infrastructures for innovation in hi-tech applications. Our approach is based on the development of horizontal platforms, which can be applied to a broad range of vertical use-cases. Namely, we target the realisation of high-throughput workflows, related to specific domains and use cases, which are able to collect and process simulations and/or physical data and information. The implementation of an interoperable integration framework is a prerequisite for further application of AI tools for predictivity and automation. With a strong focus on the development of key enabling technologies (KETs), such as advanced materials, the approach pursued is extended to a broad range of application fields and scenarios of interest in industry, including electronic and ICT, advanced and sustainable manufacturing, energy, mobility