AI-driven decoding of brain signals to enhance brain–computer interaction and cognition research.
We apply state-of-the-art AI methods to brain signal decoding, focusing on motor imagery classification, speech separation, and natural language understanding using EEG and fNIRS signals. Our work advances the capabilities of modern brain–computer interfaces (BCIs).
Projects:
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AI for Brain Signal Decoding
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Few-Shot Learning for BCI
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Target Speech Separation with AI + EEG
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Textual Decoding with Multimodal Brain Signals (LLMs)