Hi. I'm Yayun Zhang.

I am a postdoc reseacher at the Language Development Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands. I received my Ph.D. degree in Developmental Psychology and Cognitive Science from Indiana University where I was supervised by Dr. Chen Yu .

I am interested in understanding how children learn language from the world around them. My work focuses on statistical language learning, and in particular understanding the cognitive and attentional processes that support language learning. In my research, I draw on a variety of methodologies, such as using head-mounted eye-trackers to collect learning input from the learners’ own view in order to understand how different everyday environments engage learning mechanisms and how learner’s own developing cognitive and attentional systems shape early language learning input.

Research Topics

Young children are skilled word learners; within their first two years of post-natal life, they make a strong start on their native language. However, word learning is not trivial for the young child because in principle there is an unlimited number of referents embedded in the learning moment. How do infants know which word label maps onto which object? This problem is termed “referential uncertainty” in the word learning literature and has been studied extensively in the past several decades. However, little is known about the underlying mechanism of how learning unfolds in real time from naturalistic learning environment. Therefore, my work focused on examining the learning input and machinery of early word learning using input data collected from the child’s perspective. Understanding how infants learn and how learning develops not only directly impact understanding the cognitive and neural processes underlying adult cognition, but also have broad impacts on cognitive science, education, and artificial intelligence.

Statistical Learning

Verb Learning

Visual Attention

Publications

Journal Articles

The Infant’s View Redefines the Problem of Referential Uncertainty in Early Word Learning

Chen Yu, Yayun Zhang, Lauren Slone, Linda Smith

PNAS (2021)

Cross‐situational Learning from Ambiguous Egocentric Input Is a Continuous Process: Evidence Using the Human Simulation Paradigm

Yayun Zhang, Daniel Yurovsky, Chen Yu

Cognitive Science (2021)

Mechanisms of Cross-situational Learning: Behavioral and Computational Evidence

Yayun Zhang, Chi-hsin Chen, Chen Yu

Advances in Child Development and Behavior (2019)

Gaze in action: Head-mounted eye tracking of children’s dynamic visual attention during naturalistic behavior

Lauren Slone, Drew Abney, Jeremy Borjon, Chi-hsin Chen, ...Yayun Zhang, Linda Smith, Chen Yu

Journal of Visualized Experiments (2018)

Learning Object Names at Different Hierarchical Levels Using Cross‐Situational Statistics

Chi-hsin Chen,Yayun Zhang, Chen Yu

Cognitive Science (2018)

Conference Proceedings

Why Some Verbs are Harder to Learn than Others – A Micro-Level Analysis of Everyday Learning Contexts for Early Verb Learning

Siyun Liu, Yayun Zhang, Chen Yu

Proceedings of the 42nd Annual Meeting of the Cognitive Science Society (2019)

How Misleading Cues Influemce Referential Uncertainty in Statitical Cross-situational Learning

Yayun Zhang, Chen Yu

Proceeding of the 41st annual Boston University Conference on Language Development (2017)

Global and Local Statistical Regularities Control Visual Attention to Object Sequence

Alexa Romberg, Yayun Zhang, Benjamin Newman, Jochen Triesch, Chen Yu

Proceedings of the 6th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (2016)

Examining Referential Uncertainty in Naturalistic Contexts from the Child’s View: Evidence from an Eye-Tracking Study with Infants

Yayun Zhang, Chen Yu

Proceedings of the 38th Annual Meeting of the Cognitive Science Society (2016)

Statistical Word Learning is a Continuous Process: Evidence from the Human Simulation Paradigm