Tommaso Botarelli

I hold a Master’s degree in Computer Engineering from the University of Florence. My academic journey has been marked by strong results, graduating with 108/110 in my Bachelor’s and achieving Summa Cum Laude (110L/110) in my Master’s degree.

During my Bachelor’s studies, I developed a deep passion for Software Engineering and a strong interest in Deep Learning applications. My thesis, titled “Analysis of Physics-Informed Neural Networks and their application in simulating curing processes of materials in industrial autoclaves,” allowed me to explore the practical application of PINNs within industrial contexts.

While pursuing my Master’s degree, I worked alongside my studies at the DISIT Lab. There, I focused on applying PINNs to generate fluid dynamic simulations, a project that culminated in the publication of the paper: “Using Physics-Informed neural networks for solving Navier-Stokes equations in fluid dynamic complex scenarios.”

However, my focus expanded towards system architecture for my final thesis. I investigated a “model-based” method for resource provisioning in microservices architectures, which gave me the opportunity to dive deep into Kubernetes and the world of distributed systems.

Following my graduation, I began my Ph.D. at the STLab (University of Florence). Currently, my research focuses on resource optimization in microservices architectures.