Federated learning (FL) and synthetic data generation are transforming healthcare AI by enabling secure and privacy-preserving access to medical data. The talk will highlight how these technologies support the European Health Data Space (EHDS) and its goal of fostering cross-border data collaboration while ensuring patient confidentiality.
We will explore how key European projects leverage federated learning to train AI models on decentralized health data and synthetic data generation to create privacy-safe datasets for research and innovation. Together, these technologies are driving secure, AI-powered advancements in healthcare across Europe.
Andrei Kazlouksi is a postdoctoral researcher at the University of Turku in Finland. His areas of interest include security, data privacy, healthcare technology, and AI. He graduated with a PhD degree from the Computer Science department at University of Crete, in 2023.
