Matt Nassar (PI)
Matt is interested in how the brain processes information to facilitate intelligent behavior in complex and dynamic environments. He did his PhD with Josh Gold and post-docs with Joe Kable and Michael Frank before joining the Department of Neuroscience at Brown in January 2019.
Linda Yu (Post-doc)
Linda studies how the brain creates, stores, and retrieves latent state representations to improve the efficiency of learning in the face of changing contexts. She did her PhD in neuroeconomics at the University of Pennsylvania with Joe Kable. She is a true believer when it comes to TIRG.
Tiantian Li (Lab Manager/Research Assistant)
Tiantian is a recent graduate of Boston University where she majored in Neuroscience and Economics. Her undergraduate research in the Cognition and Decision Lab attempted to build computational models of learning to delay gratification. Or, learning to not TIRG?
Aansh Shah (RA)
Aansh is a senior at Brown and is using machine learning approaches to understand changes in brain dynamics induced by pharmacological manipulations.
Erin Bugbee (RA)
Erin is a junior at Brown and is using reinforcement learning models to understand how place field remapping might be used to improve learning in changing environments.
Charlene Wang (RA)
Charlene is a junior at Brown and is developing computationally efficient methods for inference in dynamic and repeating contexts.
Martin Contreras Carrera (RA)
Martin is a sophomore at Brown and is examining how learning and perceptual regularization are regulated according to the recent statistical context of the environment.
Harrison Ritz (Graduate student/honorary lab member)
Harrison is a graduate student in CLPS with Amitai Shenhav and Michael Frank working on control theoretic models of behavioral regulation.