Danny DE NOVI is a PhD student in Artificial Intelligence for Society, based administratively at the University of Pisa and operationally at the University of Messina.

He obtained his master’s degree in Data Science (LM-DATA) in 2025 from the University of Messina.

He was a scholarship holder in the Horizon Europe NEUROKIT2E project, conducting research on neural computations for low-energy consumption devices with reduced computational capacity, with a particular focus on model compression mechanisms (i.e., quantization and pruning).

His current research focuses on the development of forecasting, anomaly detection, and microservice scheduling models in the computing continuum, with the aim of optimizing dynamic resource allocation and improving the operational efficiency of distributed systems. At the same time, he studies techniques for certifying machine learning models and pipelines on blockchain, aimed at ensuring transparency, traceability, and verifiability in automated decision-making processes.