Assess students' ability to create an original graduate‑level research proposal to design, implement, and ethically evaluate a privacy‑preserving federated learning system for real‑time infectious disease surveillance. The proposal must state clear research questions, articulate epidemiological data and modeling requirements, specify federated learning algorithms with differential privacy guarantees, define system architecture addressing latency, scalability, and fault tolerance, present an experimental and evaluation plan that balances model utility and privacy (including metrics and validation on simulated or real data), detail legal/regulatory compliance and risk mitigation, and propose stakeholder engagement and public‑trust strategies, timeline, resources, and anticipated public‑health impact.