Nicole Tye received her B.Eng. degree from Northwestern Polytechnical University, Xi’an, in 2022 and her M.Eng degree in Control Science and Engineering from the same university in 2025. In March 2026, she joined CenBRAIN Neurotech Center of Excellence as a Research Assistant. She contributed to publish a paper in the Journal of Neural Engineering.

Nicole’s research interests include EEG-based brain-computer interfaces, neural signal processing, multimodal EEG and fNIRS analysis, and edge AI applications. Her previous research investigated real-time motor imagery EEG systems for cursor control, with a focus on accuracy, low latency, and efficient deployment. She is currently contributing to projects within the Neural Signals and Images team, including adapting pre-trained generalized EEG foundation models for edge applications and analyzing EEG and fNIRS data from mental health studies to support practical neurotechnology solutions.

[1] Muhammad Ahmed Abbasi, Hafza Faiza Abbasi, Xiaojun Yu*, Muhammad Zulkifal Aziz, Nicole Tye June Yih, and Zeming Fan. E-SAT: An extreme learning machine based self-attention approach for decoding motor imagery EEG in subject-specific tasks. Journal of Neural Engineering, 21(5): 056033, 2024. (Q3 Journal)