Interpretable EEG models of cognitive state
Robust and physiology-guided temporal representation learning for cognitive monitoring under stress, fatigue, and other subject-dependent conditions.
Related work ↗Projects
Ongoing work connecting neural-signal modelling, meditation and devotional-practice EEG, physiological interpretability, cross-subject robustness, and deployment-aware learning.
Robust and physiology-guided temporal representation learning for cognitive monitoring under stress, fatigue, and other subject-dependent conditions.
Related work ↗Characterising neural dynamics during Hare Krishna Mahamantra meditation and Kirtan-related devotional practice using multichannel EEG, spectral–temporal analysis, and data-driven modelling.
OBiGSEN preprint ↗Interpretable temporal models that connect automated sleep-stage decisions with meaningful physiological structure in EEG and multimodal recordings.
Related work ↗Efficient and privacy-aware learning for wearable neurophysiological sensing, with attention to deployment constraints, trust, and model auditing.
Related work ↗