Michele develops software to study eating behavior. He uses AI and machine learning to automate the detection of bites, chews, swallows and sips from video recordings of adults and children. The manual annotation of meal video recordings is a time-consuming process that entails errors. In future eating behavior studies, Michele's project will assist researchers in analyzing the outcomes of their research faster and more reliably (thanks to the automated measurements).
After a bachelor's degree in Biotechnology at the University of Rome, La Sapienza, Michele obtained a master's degree in the top program of Biomolecular Sciences at the University of Groningen.
Working on genomics (RNA-Sequencing and GWAS) at the University of Groningen and during his internship at the Genome Institute of Singapore, he developed bioinformatics and computer programming skills. He matured an interest in nutrition at the University of Illinois at Chicago, where he studied the metabolic effects of Mediterranean and high-fat diets on psychiatric disorders.