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.