marco lorenzetti

I am a recent graduate with a Master’s degree in Physics of Data from the University of Padua, specializing in Deep Learning and Data Analysis. Throughout my studies, I collaborated with several companies, where I honed my skills in data management and cleaning, industrial process modeling, and the development of predictive algorithms. I am passionate about data and firmly believe in its potential to optimize business productivity and, more importantly, improve people’s lives. 

In my everyday life, I pursue many passions: I play music, paint, and engage in various sports. At work, I value interacting with others and building strong relationships to support one another. I firmly believe that the key to effective teamwork lies in communication and an open-minded approach to everyone’s ideas.

I am a data scientist and software developer with experience in advanced analytics for sports and medical sectors. At Wolico s.r.l., a football data analytics start-up, I implemented dimensionality reduction models (VAE and NMF) to represent playing styles through compact vectors, aiding clubs in strategic decision-making. Previously, at ImaginAlis, I developed C++ software to design Bowtie Filters for veterinary CT scans, optimizing filter size to improve contrast and safety for both patients and radiation sources.

At Wolico s.r.l., I spearheaded the development of advanced data analytics solutions in football by implementing cutting-edge dimensionality reduction techniques, specifically Variational Autoencoders (VAE) and Non-Negative Matrix Factorization (NMF). These models enabled the transformation of complex player performance data into compact, interpretable vectors, encapsulating tactical styles with high fidelity. This innovative representation provided actionable insights for player recruitment and strategic decision-making, directly empowering clubs to make data-driven choices with precision. My work not only advanced the analytics capabilities of the company but also demonstrated the potential of machine learning to revolutionize sports data interpretation.