Brain-Computer Interface (BCI) establishes a direct link between the brain and an external device (computer, robot, etc.). It is the ultimate means of human-computer interaction.

Our laboratory mainly studies non-invasive BCIs, particularly, signal processing and machine learning approaches to implement accurate, secure and privacy-preserving BCIs.

Machine learning is the core of artificial intelligence. Our laboratory mainly works on transfer learning, active learning, deep learning, ensemble learning, adversarial attacks, and fuzzy systems, and their applications in BCIs and smart healthcare.

On the Vulnerability of CNN Classifiers in EEG-Based BCIs

TNSRE 2019