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propagation models that incorporate the effects of fire effluents, validated through controlled experimentation. You will develop tomographic inversion methods and anomaly-detection algorithms capable
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-of-the-art deep learning algorithms (e.g., CNNs, RNNs) to identify characteristic signatures of early airway disease. This project is designed for real-world impact. Through established clinical and industry
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industries. Challenges include algorithmic bias, data privacy, and the erosion of trust in digital environments. Research questions include: How can design and creative methodologies foster transparency and
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