Research: Analysis of Behavioral Patterns in Cooperative and Non-Cooperative Collective Dynamics Using Physics-Informed Neural Networks
Here is the revised English version of your descriptive CV:
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**Raoul Vetere** is an expert in the application of advanced technologies for the space sector, currently serving as **CAIO** at **Involve Space**, where he previously held the role of **CTO**. At Involve, Raoul has implemented sophisticated **Physics-Informed Neural Networks (PINNs)**, applying them to control stratospheric balloons in stochastic environments. Using these networks, he has been able to optimize control within complex physical contexts by integrating data-driven predictions with the physical laws governing the behavior of the stratospheric environment.
His primary interests lie in **mathematical analysis applied to optimal control**. Specifically, he focuses on studying the conditions for the existence and uniqueness of solutions for both cooperative and non-cooperative differential games, along with developing numerical algorithms to solve them. Given his background in neural networks, he is also interested in **developing physics-informed neural networks** to generalize the concept of classical (and even viscosity) solutions of Hamilton-Jacobi-Isaac equations using deep neural networks.
His education includes a second **Master’s Degree in Computational Sciences** from the University of Roma Tre, where he developed strong expertise in PINNs applied to physical and optimal control problems—a skill set he successfully brought into Involve.
He also collaborated with **Thales Alenia Space** as an intern, contributing to the development of neural networks for advanced aerospace applications, enhancing his machine learning capabilities applied to space sciences. His academic background is further strengthened by a **Master’s Degree in Pure and Applied Mathematics** and a **Master’s Degree in Space Sciences and Technology** from the University of Tor Vergata, with a focus on challenges related to space exploration.