Jie Ren


Jie_Ren@Brown.Edu


Jie Ren
Ph.D. Candidate,
Department of Cognitive, Linguistic and Psychological Sciences,
Mater of Art in Biostatistics,
Brown University, Providence, RI.

Jie_Ren@Brown.Edu

I am a developmental cognitive scientist. My research focuses on category perception and its developmental changes. I am specifically interested in testing the basic mechanisms for category competition in human cognition, and whether there is developmental continuity in such mechanisms. I use two approaches for my research. (a) I use recent advances in machine-learning to formulate ideal learner models, and then (b) test the model predictions with infants and adults by behavioral experiments. 

My PhD work is engaged in testing how input affects the perception of categories. Most of the published works on this question are in the domain of  infants' early speech perception. These experimental works are done with Dr. James Morgan, in the historical Metcalf Infant Research Lab

My theoretical works are focusing on modeling cognitive mechanisms of categorization using statistical learning methods.  My current work in computational modeling is under the framework of Non-parametric Bayesian inference using unsupervised learning algorithm (e.g. Hierarchical Dirichlet Processes). Most of my modeling works are completed in collaboration Dr. Jospeh Austerweil

In 2012, I received the "Open Graduate Education Award", with which I completed an En Route Master's Degree in Biostatistics in the Center of Statistical Science at Brown University. With this highly selective honor, I initiated my research in statistics, focusing on creating advanced statistical techniques in analyzing infant data. I am currently doing research in statistics in collaboration with Prof. Christopher Schmid. As a statistician, I am fluent in SAS and R programming. 

My future research direction will be focusing on the neuro-developmental, cognitive and behavioral status of highly risk infant population such as preterm infants and autistic infants. I will use machine-learning techniques to model their learning mechanism and then test the model predictions with empirical experiments. 

I am also a professional opera singer (soprano). Please click here for my nonacademic pages.


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