Federated Continual Learning with Differentially Private Data Sharing
- 2022
- NeurIPS 2022
Bio
Giulio's research interests focus on the security and robustness of machine learning. Recently, he has been working on adversarial machine learning with a focus verifiable methods and the security of Federated Learning.
He obtained his PhD from Imperial College London in 2021 which focuses on adversarial and robust machine learning. He joined IBM Research in 2021 and has continued his research in private and robust ML and contributing to open source projects such as ART (Adversarial Robustness Toolbox) and various Horizon Europe programmes.
Publications
Verifiable Federated Learning
- 2022
- NeurIPS 2022
Robust Learning Protocol for Federated Tumor Segmentation Challenge
- 2022
- MICCAI 2022
FAT: Federated Adversarial Training
- 2020
- NeurIPS 2020
Projects
Federated systems
- Adversarial Robustness and Privacy
- Data and AI Security
- Foundation Models
Top collaborators
AR
Ambrish Rawat
Staff Research Scientist, AI Security and Privacy, Master Inventor
SB
Stefano Braghin
Research Engineer and Technical Lead - Security and Privacy, Master Inventor
JE
Jonathan Epperlein
Research Scientist
ST
