Data analysis, learning and control for biology and medicine

We develop methodological tools, algorithms and software to analyze data and vital signals reflecting individual health and to exploit them with learning techniques to improve patient therapy, possibly creating real-time feedback mechanisms. Tools are personalized, adaptive, proactive and equipped with intelligent self-diagnostic functions. Models to predict and prevent the incidence of new diseases or medical complications are also investigated. Our main clinical application is the treatment of diabetes mellitus, but we are also involved in projects aimed at predicting the onset of cardiovascular and chronic respiratory diseases and in cognitive neuroscience investigations.

 

Group members

Giovanni Sparacino, Full professor

Andrea Facchinetti, Associate professor

Simone Del Favero, Assistant professor

Martina Vettoretti, Senior post-doc research fellow

Giacomo Cappon, Junior post-doc research fellow

Enrico Longato, Junior post-doc research fellow

Simone Faccioli, PhD student

Nunzio Camerlingo, PhD student

Giulia Noaro, PhD student

Jacopo Pavan, PhD student

Francesco Prendin, PhD student

Chiara Roversi, PhD student

Alessandro Guazzo, PhD student

Eleonora Manzoni, PhD student

Luca Cossu, Research collaborator

 

Former group members

Maria Rubega (PhD awarded in 2017)

Giada Acciaroli (PhD awarded in 2019)

Francesca Marturano (PhD candidate with dissertation defense planned in 2021)

Lorenzo Meneghetti (PhD candidate with dissertation defense planned in 2021)