Imraul Emmaka
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Researcher
Graduate Student Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Imraul Emmaka's research focuses on optimizing computational models for medical imaging and secure data handling. Their work includes investigating the resource-performance trade-offs of Convolutional Neural Networks (CNNs) and Transformers for lung CT scans, exploring when three-dimensional analysis provides significant benefits. Emmaka also contributes to the field of private federated learning, particularly for Internet of Things (IoT) applications, by developing hybrid cryptographic protocols for secure aggregation. This research aims to enhance the efficiency and privacy of machine learning models used in healthcare and related technological domains.
Metrics
- Publications: 2
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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