Imraul Emmaka
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Biography and Research Information
OverviewAI-generated summary
Imraul Emmaka's research focuses on developing and evaluating cryptographic protocols for secure data aggregation in Internet of Things (IoT) environments, particularly within federated learning frameworks. His work addresses privacy concerns in distributed machine learning applications. Emmaka also investigates the resource-performance trade-offs of different neural network architectures, such as Convolutional Neural Networks (CNNs) and Transformers, for analyzing medical imaging data, specifically lung CT scans. His recent publications include studies on one-shot secure aggregation protocols for private federated learning and an analysis of the utility of 3D data processing for CNNs and Transformers in medical imaging contexts.
Metrics
- h-index: 1
- Publications: 3
- Citations: 1
Selected Publications
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One-Shot Secure Aggregation: A Hybrid Cryptographic Protocol for Private Federated Learning in IoT (2025)
Collaboration Network
Top Collaborators
- One-Shot Secure Aggregation: A Hybrid Cryptographic Protocol for Private Federated Learning in IoT
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