Lead: CMU and INESC TEC

Start: August 2020

End: June 2022

Goal: The goal of this activity is to develop Federated Learning (FL) methods, either by adapting existing machine learning algorithms or by developing new ones to work on a FL framework. There are three lines of action, materialized in three tasks. 

The first task will provide a software framework with the necessary connections to the application side. 

The second task will focus on federated machine learning algorithms and their evaluation. 

The third task, held in parallel with the second, will focus on privacy, explainability in edge computing environments. 

In the end, a functional prototype will be available for integration and testing along with results from Activities 2 and 4. This activity will be led by CMU and INESC TEC will also participate in its coordination. This will ensure a successful collaboration between the USA and portuguese partners towards achieving the desired activity outputs.