My main interest is to understand how linguistic information forms in the brain and its influences on human daily behaviors. I began my academic journey in psychology, where I developed a strong interest in human cognition and behavior. From 2003 to 2010, my research focused on visual word recognition in Chinese, specifically the cognitive mechanisms involved in processing Chinese characters. However, around 2008, I began to realize that there were broader questions beyond single-word reading—particularly how syntactic structure and prosody shape language comprehension. That same year, I had the opportunity to collaborate with researchers grounded in formal linguistic theory, and I found myself deeply drawn to the systematic elegance and explanatory power of formalism.

Since 2010, my work has shifted toward neurolinguistics, where I investigate how morphological structures and phonological inventories influence language perception, sentence comprehension, and word learning. My current research aims to understand how these linguistic components are acquired, represented, and dynamically processed in the brain—linking cognitive science, neuroscience, and theoretical linguistics in an integrative approach to studying human language.

In the Brain and Language Laboratory, we investigate the neural and cognitive mechanisms underlying human language. Our research integrates a variety of neuroimaging and behavioral techniques—including magnetoencephalography (MEG), electroencephalography (EEG), and eye-tracking—to study how language is processed in real time. Most of our participants are typically developing adults, but with the collaboration of language pathologists, we also work with children, including those with typical development, ADHD, and language developmental disorders.

Our overarching goal is to bridge theoretical linguistics and cognitive neuroscience with real-world applications in clinical, educational, and developmental contexts. We aim to translate scientific findings into hospital-based diagnostics, school-based language interventions, and early childhood support strategies.

In addition to empirical experiments, we embrace the principles of open science and frequently leverage open-access datasets. We also develop computational models using neural and behavioral data to test and refine our hypotheses, allowing us to explore the functional architecture of language in the brain through simulation and predictive modelingㄡ