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We introduce a framework for the channel selection problem, mathematically formulate the minimum-cost channel selection (MCCS), and propose two novel algorithms to solve the MCCS problem.

We propose a personalized hydration monitoring system with wearable and machine learning.

We propose a self-supervised learning (SSL) approach for cognitive workload classification using wavelet-based augmentations of EEG signals.