People

Joseph Austerweil

Professor & Academic Director, School of Design & Science

As a computational cognitive psychologist, my research program explores questions at the intersection of perception and higher-level cognition. I use recent advances in statistics and computer science to formulate ideal learner models to see how they solve these problems and then test the model predictions using traditional behavioral experimentation. Ideal learner models help us understand the knowledge people use to solve problems because such knowledge must be made explicit for the ideal learner model to successfully produce human behavior. This method yields novel machine learning methods and leads to the discovery of new psychological principles.

Zhuolun Zhong

Research Scientist

Shohei Yoshida

Master's Student

Jie Ren

Visiting Instructor, Brown University; Visiting Professor, McGovern Institute for Brain Research at Beijing Normal University

​Jie's​ research is concerned with the biology and neurology of infant speech ​learning​. The research methods used in ​her​ research include behavioral measures of infant speech perception, functional neuroimaging (fNIRS) and computational modeling with ​machine-learning techniques.

Boyoung Kim

Graduate Student at Brown University

Boyoung collaborates on modeling how people learn social norms..

Babak Hemmatian

Graduate Student at Brown University

I am a Ph.D. student of cognitive science, with a background in psychology, but a new-found love for computational modeling. I am most interested in integrating the computational models offered for different kinds of reasoning (inductive, causal, deductive, etc.), offering new such models (with an emphasis on causal reasoning) and comparing the proposals with regards to how well they capture the qualitative and quantitative aspects of human reasoning.