Lorenzo Sani

I am supervised by Prof. Nicholas D. Lane, the head of the CaMLSys group at the Computer Laboratory. My research interests are in the areas of federated learning and edge computing. I am interested in designing privacy-preserving machine learning algorithms to edge devices, particularly federated learning. My current research focuses on optimizing the efficiency of large-scale federated learning settings.

I received my Bachelor's Degree in Physics from the University of Bologna in 2019 with a thesis on the fine structure of hydrogen-like atoms. Then, I received my Master's Degree in Applied Physics from the University of Bologna in 2021 with a thesis titled "Unsupervised clustering of MDS data using federated learning" under the supervision of Prof. Enrico Giampieri and the co-supervision of Prof. Gastone Castellani. During my Master's Degree, I was involved in the GenoMed4All project to redact Deliverable 6.2 - "Preliminary conclusions about Federated Learning applied to clinical data". During my Master's Degree, I also collaborated with the CaMLSys group at the University of Cambridge on the Flower Framework project, see the paper.