Shaoqi Pan is a PhD student in Psychology at The Chinese University of Hong Kong. His work sits at the intersection of cognitive neuroscience, developmental psychology, language learning, knowledge representation, and computational modeling. His research examines how the brain encodes speech and structured linguistic information, from early neural speech encoding in infants to cognitive-map-like representations during language learning.

He currently uses EEG/sABR, sEEG, and computational approaches to study neural speech encoding, grammar learning, and predictive markers of language outcomes. Before beginning doctoral training, he completed an MA in Linguistics at CUHK and worked as a research assistant at the Brain and Mind Institute, where he analyzed large-scale EEG datasets and built machine-learning models for predicting language development. His earlier training in telecommunication engineering provides a quantitative foundation for signal processing, machine learning, and data-driven approaches to human language and cognition.