Privacy-Preserving Federated Learning for Graph-Structured Data

Prof. Alexandre Graell i Amat

 

Biography:

Alexandre Graell i Amat is a Professor at Chalmers University of Technology. His research interests span coding theory, particularly in emerging applications such as DNA storage, and artificial intelligence. Initially, he leveraged coding-theoretic concepts in AI but his work has since expanded to broader AI research. His current focus is on developing theoretically sound and practically viable methods to enhance AI security and safeguard user privacy. This includes privacy-preserving AI, adversarial robustness, and trustworthy AI, with a particular emphasis on graph-based learning methods and federated learning.