AI in Brain-Computer Interface
Deep learning-based non-invasive BCI
Designing deep neural networks capturing temporal-spectral-spatial characteristics of EEG
Development of learning algorithms for paradigm-invariant BCI
Developing learning algorithms reflecting properties of various EEG paradigms
Zero-training BCI
Representing subject/session-invariant features to reduce variabilities of unseen EEG signals of zero-calibration