Areas of Focus
- Language acquisition in infants and adults
- Statistical learning in language
Work Experience
- 2018-2022 - University of Nevada - Assistant Professor
- 2022-Present - Nanjing Normal University - Professor
Academic Background & Achievements
- 2012 - Bachelor's Degree: Wesleyan University
- 2016 - Ph.D.: University of Southern California
- Postdoctoral Training: University of Pennsylvania
- Member: Society for the Cognitive Science
- Member: Society for Language Development
Publications
- Perceptual intake explains variability in statistical word segmentation, Wang, F. H., Luo, M., & Wang, S., 2023
- Statistical word segmentation succeeds given the minimal amount of exposure, Wang, F. H., Luo, M., & Wang, S., 2023
- Four‐and six‐year‐old children track a single meaning with both familiar and unfamiliar referents when the referent is clear: More evidence for propose‐but‐verify, Wang, F. H., Wang, F. H., Luo, M., & Li, N., 2023
- Linguistic Priming and Learning Adjacent and Non-Adjacent Dependencies in Serial Reaction Time Tasks, Wang, F. H., & Kaiser, E., 2022
- Being Suspicious of Suspicious Coincidences: The Case of Learning Subordinate Word Meanings, Wang, F. H. & Trueswell, J. C., 2022
- Explicit and implicit memory representations in cross-situational word learning, Wang, F. H., 2020
- Top-down grouping affects adjacent dependency learning, Wang, F. H., Zevin, J. D., Trueswell, J. C., & Mintz, T. H., 2020
- Spotting Dalmatians: Children’s ability to discover subordinate-level word meanings cross-situationally, Wang, F. H., & Trueswell, J. C., 2019
- Successfully learning non-adjacent dependencies in a continuous artificial language stream, Wang, F. H., Zevin, J., & Mintz, T. H., 2019
- Statistical Learning of Unfamiliar Sounds as Trajectories Through a Perceptual Similarity Space, Wang, F. H., Hutton, E. A., & Zevin, J. D., 2019
- The role of reference in cross-situational word learning, Wang, F. H., & Mintz, T. H., 2018
- Learning non-adjacent dependencies embedded in sentences of an artificial language: When learning breaks down, Wang, F. H., & Mintz, T. H., 2018
- Top-down structure influences learning of nonadjacent dependencies in an artificial language, Wang, F. H., Zevin, J. D., & Mintz, T. H., 2017
- Language acquisition is model-based rather than model-free, Wang, F. H. & Mintz, T. H., 2016
- Word categorization from distributional information: Frames confer more than the sum of their (Bigram) parts, Mintz, T. H., Wang, F. H., & Li, J., 2014