The student will help us:

• Design and develop privacy preserving AI federated learning solutions, that could be focused on mobile, edge, home platforms. 
• Implement state-of-the-art techniques such as differential privacy, secure aggregation, adversarial attacks on such models, etc.
• Collaborate with cross-functional teams to integrate federated learning solutions into existing systems.
• Conduct experiments and evaluations to assess the performance of federated learning solutions at the presence of adversarial attacks. 
• Stay up-to-date with industry trends and developments related to privacy preserving federated learning and make recommendations for future improvements.
• Write technical reports and documentation to communicate results to internal and external stakeholders.

Through the internship, the student will master all the tools involved, and learn new techniques and methodologies for experiments, measurements, etc.