Research Topic 1
Digital Twins are conceived to mirror some incredibly intricate phenomena, including turbulence, physiological responses in organisms, and traffic flow in urban transportation networks. These phenomena fall under the broad category of complex systems—collections of interconnected elements whose interactions yield global behaviors and properties beyond the understanding of individual components alone.
To understand and predict the behavior of a complex system, scientists rely on a mathematical model—a set of equations that encapsulate the physical laws governing the system: solving the equations of a mathematical model corresponds to deciphering the physics underlying the complex system.
Since this task is often long and cumbersome, researchers optimize their work by utilizing a numerical computation algorithm: instead of carrying out calculations by hand, they provide a set of step-by-step instructions to a computer, which can solve a problem using only numbers and logical-mathematical operations. Numerical algorithms are the essence of Digital Twins and enable the real-time simulation of a complex system. Unfortunately, using them requires introducing some approximations in the calculations, which translate into small errors in the final results.
Today, numerical algorithms have reached a very high level of effectiveness thanks to Artificial Intelligence (AI) and, in particular, Machine Learning (ML)—a subset of AI algorithms that enable computers to perform tasks without explicit programming instructions. Equipped with a ML algorithm, a machine becomes a sort of virtual apprentice that learns from data and experience, identifying patterns and making decisions or predictions based on that information.
The potential of ML in developing DTs is immense; to fully unleash it, every aspect has to be examined. This is where Research Topic 1 (RT1) of Spoke 9 comes into play: its goal is to study ML algorithms in depth to harvest crucial insights for crafting robust Digital Twins, paving the way for real-world applications.
Coordination
The International School for Advanced Studies (SISSA), the University of Padua (UniPD), and the University of Trieste (UniTS) are involved in Research Topic 1.
The coordinator of RT1 is Prof. Mario Putti from the University of Padua.
