Weiming Li earned his Bachelor of Engineering degree in hydrology and water resource engineering from Wuhan University, China, in June 2015. He then pursued a Master of Science degree in psychology at National Cheng Kung University (NCKU), Taiwan, graduating in June 2018. During his master's studies, his research centered on investigating the effects of EEG alpha neurofeedback on the self-reference processing and self-related memory.
From September 2018 to November 2020, Weiming worked as a research assistant at the Institute of Neuroscience, Chinese Academy of Sciences. In this role, he employed decoding methods to explore how participants process and maintain sequential information during working memory task.
In December 2020, Weiming transitioned to industry to expand his expertise in machine learning and brain-computer interface (BCI) technologies, working as an algorithm engineer until July 2024.
In October 2024, Weiming began his PhD studies in Neurosciences and Cognition at Université Claude Bernard Lyon 1 and the Lyon Neuroscience Research Center (CRNL), under the supervision of Professors Nadine Ravel and Nicolas Fourcaud-Trocmé. His PhD research focuses on investigating the neural mechanisms underlying episodic memory in rats, specifically using linear and non-linear cross-frequency coupling methods to study how different neural oscillations interact to support memory encoding and recall.
Publications
Li W, Gao J. 2023. Automatic sleep staging by a hybrid model based on deep 1D-ResNet-SE and LSTM with single-channel raw EEG signals. PeerJ Computer Science 9:e1561 https://doi.org/10.7717/peerj-cs.1561
