IMDEA Networks Institute
Research Assistant, Madrid, Spain, 2020
- Apply Federated Learning in centralised training tasks, ensuring maintained accuracy.
- Design robust aggregation methods that take advantage of reputation models and superior voting elections to fight against poisoning attacks.
- Conduct various state-of-the-art Byzantine-robust aggregations and poisoning attacks in Federated Learning to evaluate and compare the performance of our algorithms.
- Implement the proposed method into a browser extension and validated its performance through real users’ tasks.
- Integrate the algorithms into Acuratio’s Multicloud Federated Learning Platform, enabling training on real user data within an industrial setting.