My main research area consists in the development of Machine and Deep Learning solutions characterized by a "privacy-preserving" approach. The main tool used for this goal is Homomorphic Encryption (HE), a novel and complex family of encryption schemes which enables the processing of encrypted data (i.e., without the need to decrypt data before the processing happens).

Among the others, I focus in particular on the application of HE-DL to time-series analysis, forecasting, etc.


Other research activities

Teaching activities



Master Thesis

I am co-relator of 10+ Master thesis (Computer Science and Engineering).

Reviewer activity