School of Computer Science and Statistics
This project will investigate whether multiple NVIDIA Jetson edge devices can collaboratively train and improve an AI occupancy-detection model without transferring raw video or image data between sites. The student will build and evaluate a federated learning setup in which devices train locally and contribute model updates to a shared global model, while accounting for … Read more
With the great capability of learning high-level representational features of unstructured data automatically, deep learning is acknowledged as a powerful machine learning algorithm for radio signal processing in future networks and communications (6G and beyond). For example, convolutional neural networks (CNNs) are leveraged to develop automatic modulation classification frameworks in [1]-[3]. CNN and its combination … Read more
Federated learning is a paradigm breakthrough shift in AI for data privacy preservation. Unlike conventional AI techniques, federated learning does not require the users to share the data, but only the AI model parameters. As such, federated learning has found notable successes in numerous applications (e.g., Google keyboard, localization, security, and data sharing) and various disciplines … Read more