I obtained a Ph.D. in Linguistics from the University of Pennsylvania and am currently an Associate Professor at Chosun University in Korea. At my university, I am the principal investigator of the Child Language Lab, where we investigate young children's linguistic and cognitive development. I am also the founding director of the recently established Center for Data Science in Humanities. 

Within the global academic community, I serve as a member of the Governing Board at Manybabies, a global consortium of developmental researchers. Additionally, I hold the position of Associate Editor for the Journal of Child Language, and serve on the Editorial Boards of the Cambridge Elements in First Language Acquisition series and Infancy

My Ph.D. thesis focused on Korean prosody, driven by my early linguistic curiosity about the sound system of my native language. After completing my Ph.D., I had the opportunity to expand my research into child language acquisition at the Department of Cognitive and Linguistic Sciences at Brown University. Before joining my current institution, I worked at the University at Buffalo, SUNY, and Seoul National University.

My research employs various methodological approaches, including quantitative analyses of empirical data obtained from corpora of spontaneous speech or data elicited in a lab setting. When working with infants, I primarily use eye-tracking methods to observe how babies process visual and auditory input. We also use the LENA system to capture infants' everyday environments at home through day-long audio recordings.

My research topics include the following:

1. Nature and Function of Child-Directed Speech: I investigate the characteristics of child-directed speech (CDS), exploring how, why, and when mothers alter their speech characteristics over the course of child language development and whether these alterations systematically enhance specific aspects of CDS relevant to language learning (and to what extent these enhancements are side effects of other CDS features).

2. Computational Modeling of Language Acquisition: This research broadly investigates how infants achieve language acquisition through unsupervised learning, with a specific focus on the mechanisms of segmentation in infant word learning. This includes examining how infants utilize statistical distribution of phones, prosodic cues (stress/accent), phrasal boundary cues, and multimodal cues (such as touch). Moving forward, I also plan to explore computational modeling related to phoneme and word learning.

3. The Effects of Input and Family Context on Infants' Linguistic and Cognitive Development: This research investigates the impact of various forms of input—including reading, musical exposure, and child-directed speech (CDS)—on infants' word learning. Additionally, it examines the influence of family socio-economic status (SES) and maternal working status on child language outcomes, exploring the potential interplay between these family factors and the effects of input.

4. Developmental AI: To explore the reciprocal benefits of interdisciplinary collaboration between developmental science and artificial intelligence (AI) research, investigating how AI can enhance our understanding of infant learning and how infant learning mechanisms can inspire more efficient and adaptable AI systems.

5. Text-Setting in Korean Vocal Music: This research examines the interplay between linguistic structure and musical meter in Korean vocal music, specifically investigating the alignment of strong beats (metrical heads) in Western music with linguistic units (text-setting). Preliminary observations indicate a tendency for strong beats to align with the initial and final syllables of words, reflecting Korean's edge prominence in intonation. I aim to further investigate how this text-setting convention has been impacted by the adoption and adaptation of Western musical styles in Korea. 

Want to know more about my academic trajectory? Here is my CV.