I am interested in Graph Neural Networks: with my collaborators, we are investigating their applications to time series. We are also working on applications of Sheaf Theory and Geometry to Machine Learning and AI. We combine these techniques and theoretical ideas with Deep Learning and other standard Machine learning techniques (regression, SVM, clustering algos, random forests, etc.).

Projects I am working on:

• Blood pressure regression and forecasting from Photoplethysmogram and ECG data.

• Quality Recognition of biological signals.

• Covid-19 severity prediction from genetic data.

• Kolmogorov-Arnold Convolutional Network models for supervised quality recognition of PPG signals, A. Mehrab, M. Lapenna, F. Zanchetta, A. Simonetti, G. Faglioni, A. Malagoli, R. Fioresi, Entropy, 2025

• Graph Neural Networks and Time Series as Directed Graphs for Quality Recognition, A. Simonetti, F. Zanchetta. Preprint,  arXiv:2310.02774, 2023

• A Geometric deep learning approach to blood pressure regression, F. Zanchetta, A. Simonetti, G. Faglioni, A. Malagoli and R. Fioresi. Extended abstract accepted to GeoMedIA workshop 2022. Link