معرفی
Daniel Ramage is a researcher at Google focused on privacy-preserving machine learning and federated learning. His work bridges artificial intelligence and data privacy, with particular emphasis on decentralized data systems, secure model training, and privacy-aware NLP. He has published extensively on topics including local differential privacy, attack resilience in federated systems, and collaborative model development for mobile applications.
- Key Research Areas:
- Federated Learning Architectures
- Privacy-Preserving AI
- Language Model Security
- Collaborative Machine Learning
- Recent Publication Trends:
- 2025: Trustworthy inference mechanisms
- 2024: Error correction in mobile LLMs
- 2023: Production-scale federated systems
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