Reliability and resilience analysis of engineeering systems, networks and crytical infrastructure and related uncertianty quantification and analyses.

Reliability and resilience analysis of engineeering systems, networks and crytical infrastructure and related uncertianty quantification and analyses.

I work in the department of mathematics and computer science, and industrial statistics at TU/Eindhoven, the Netherlands. I hold a Ph.D. in reliability engineering and an MRes in decision-making under risk and uncertainty from the University of Liverpool. I collaborated in serval projects linking academia and industry and focused on combining traditional concepts from reliability engineering and system safety with tools and approaches for smart energy grids management and analyses. I have a broad knowledge of statistical learning theory, data-driven machine learning algorithms and (more in general) data-driven optimization methods. My research generates a high impact, especially in the stability and reliability engineering communities. I consider my profile highly multidisciplinary, and this facilitates the cross-fertilisation of ideas that can generate interesting synergies between partners finally supporting knowledge transfer and development of new ideas.