Graduate Students

Sami Yousif
I am generally interested in understanding how we perceive, interact with, and represent the space around us. For example, imagine that you’re at the grocery picking out a box of strawberries, and you want to choose the one with more. How do you make that decision? My research reveals surprising, counter-intuitive ways that people solve problems like these. Beyond spatial perception and cognition, I also have an interest in various aspects of high-level decision-making. For example, how do we make choices when faced with highly polarized information (i.e., information from parties who strongly disagree)? And how do we understand what makes an explanation ‘good’? 
 
Sami can be reached at sami.yousif@yale.edu
 
 
Emory Richardson
The questions I’m most interested in have to do with information structure and learning. For example, how do we recognize that someone else must have more information than we do, without having access to everything they know? Do we expect some sorts of knowledge to be accessible only to multiple people working together? Why do some hard questions pique our curiosity and others turn us off? In what sorts of cases are we willing to “explain away” data that doesn’t fit our generalizations?
 
Emory can be reached at emory.richardson@yale.edu
 
 
Mandy McCarthy
My research focuses on how children and adults come to understand mechanism and causality as well as our subjective evaluations of what characterizes a good and useful explanation. Specifically, current studies investigate how cues such as jargon and pedagogical insight impact children’s and adults’ judgement of the usefulness of explanations. Other studies investigate how exposure to mechanistic explanations impacts our conceptions of the world. Specially, I am interested in how learning mechanism might make people more confident - and perhaps overconfident - in their willingness to challenge claims.
 
Mandy can be reached at amanda.mccarthy@yale.edu
 
Xiuyuan Flora Zhang

Flora is fascinated by how humans learn about the meanings of objects, relationships, actions, and concepts in their daily life in a seemingly effortless manner. She draws from computational modeling techniques to explore how humans form beliefs about the social and physical environment around them, update their beliefs, and make predictions in an information-and-noise-rich environment. In one of her ongoing projects, she is exploring how children and adults understand and evaluate diversity in information selection. Two questions of particular interest are: how do we leverage the competing pressures between wanting to maximize efficiency and wanting to maximize information gain? How do we resolve the tension between seeking diverse information and staying on topic?

Her other projects fall into domains of language learning, information processing, and learning social and conventional norms.

Flora can be reached at flora.zhang@yale.edu