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-Language and Multimodal Foundation Models Uncertainty-Aware Prediction Memory and Temporal Context Action-Conditioned Future Prediction Human-Aware Planning Socially Intelligent Human-Robot Interaction
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language models and continuous wearable data now make genuinely personalised, context-aware coaching feasible for the first time, while raising real questions about safety, equity, engagement, and cultural
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aims to improve efficiency and privacy of federated learning for mobile health sensing data by proposing a multi-level (mobile-edge-cloud continuum) federated learning architecture and develop context
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must support causal queries about what would happen under intervention, generalise reliably to deployment contexts not present in training data, and expose its reasoning chain to inspection so that risk
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from research into how spatial awareness and context-specific memory function in mixed reality (MR) data analytics environments[3]. Expected outcomes The anticipated results of this doctoral research