Michele Urbani is a researcher in the Hydrogen Technologies and Resilient Energy Unit of the Centre for Sustainable Energy. With a PhD in Operations Research, he is passionate about using optimisation and machine learning to support smarter decision-making and improve the performance of complex simulations.

Since 2018, I’ve been working on workforce routing and maintenance planning, applying both single- and multi-objective optimisation techniques. At Fondazione Bruno Kessler, I’ve contributed to the development of multi-objective optimisation solutions for energy systems.

With strong programming skills in Python (and basic C and Docker), I also build reduced-order models powered by machine learning to optimise simulations of dynamic systems.

More recently, I’ve expanded my focus to Research Data Management and the development of tools aligned with the Functional Mockup Interface (FMI) standard.

Michele holds a double doctoral degree in Operations Research at the University of Trento (Italy) and Economics and Business Administration at LUT University (Finland).