Giuseppe GALLO

I am a researcher in Experimental and Applied Physics with strong expertise in the design, implementation, and characterization of innovative experimental systems. My work includes the modeling and simulation of detector responses through Monte Carlo techniques, with a particular focus on the interaction of prototypes with charged particles. I have extensive experience in the development and characterization of scintillation detectors and optical sensors, complemented by a solid background in signal processing and electronics acquired during detector R&D projects.

Over the years, I have developed advanced skills in numerical computing, with extensive use of MATLAB, and I possess excellent programming capabilities in C/C++. My proficiency in Python has grown significantly, particularly through recent projects involving machine learning (ML) applications. In this context, I have worked on developing and optimizing deep generative models such as variational autoencoders (VAEs) for super-resolution tasks, applied to Monte Carlo simulation outputs. 

Additionally, I am gaining increasing experience in High Performance Computing (HPC), particularly in the context of ML model optimization and large-scale simulation workflows. My work includes adapting pipelines for execution on national HPC infrastructures, with an emphasis on modular code development, reproducibility, and computational efficiency.

My research trajectory includes long-standing involvement in secondary cosmic muon tracking applications—such as volcano muography and structural stability monitoring—since my Ph.D. years. Earlier, during my master’s thesis, I worked on a detector system based on scintillating optical fibers and SiPMs for hadron therapy, addressing beam monitoring, residual range measurement, and charged particle radiography.