Tom Griffiths, Lab Director

(webpage)

Anne Hsu

I am interested in human statistical learning using computational modelling and web-based experiments. In particular I've been investigating language learning and models of categorization. I've also been examining how people learn omission exceptions to general rules in cognitive domains.

Joe Austerweil

(webpage) My research explores the interconnection between human and statistical solutions to inductive problems. In particular, I am interested in using statistical models to garner insight to how the human mind solves problems that plague philosophers and computer scientists. By looking at the assumptions behind these computational models, we better understand the prior assumptions people use to make surprisingly accurate inferences in the underconstrained problems of everyday life. Additionally, I explore infusing these assumptions into state-of-the-art machine learning techniques. I hope to improve their performance on everyday tasks (where people, with surprisingly less data, easily outperform them).

Daphna Buchsbaum

I'm interested in how children and adults understand and learn from other people's behavior, and ultimately developing intelligent computer programs with some of these same social learning abilities. Currently, my research is focused on the problem of action segmentation: when faced with a continuous stream of behavior, how do we identify individual, meaningful actions? How do we decide what the effects of these action sequences are? I'm exploring how both preschoolers and adults use causal structure and statistical patterns in human motion to help understand other's behavior, as well as using Bayesian computational approaches to try and model human action understanding.

Kevin Canini

(webpage) I'm interested in statistical machine learning and (probabilistic) models of human cognition. My long-term goal is to build intelligent computer programs that are inspired by human neurobiology and psychology.

Chris Lucas

I'm interested in how and to what extent the abstract knowledge that constrains human induction is acquired. My current research focuses on causal induction, but I'm also interested in categorization, language, and the neural machinery behind human induction.

Lei Shi

I'm interested in using Bayesian methods to model human cognitive processes. My current project is making connections between exemplar models and Monte Carlo sampling methods. When I have time, I also wonder how Bayes' rule is implemented in the brain.

Joseph Jay Williams

(webpage) I'm interested in understanding the role that explanation plays in learning, by drawing on computational modeling, verbal-conceptual theories, and empirical research.

Jing Xu

I'm interested in understanding the connection between people's lower level behavior, such as movement control, and people's higher level cognition, such as cognitive switching, category learning and memory. Particularly, at this interface, how the prior knowledge/constraints in people's mind influence people's behavior. I'm using computational and mathematical approaches to model behavioral and neural empirical data.

Jason Martin

(webpage)I am interested in using probabilistic models to investigate the structure of natural categories. In my current research, I apply various subject based sampling techniques with the aim of improving the way classification algorithms explore psychological spaces. Specifically, I use a variation of MCMC to gather information about how people represent highly dimensional category structures such as facial affect.

Naomi Feldman

My interests are in speech perception and language acquisition. I'm using computational and behavioral methods to look at how people organize speech sounds into categories and how those categories affect their ability to perceive differences between sounds.

Sharon Goldwater

My research interests include language acquisition, computational linguistics, phonology, and morphology.

Florencia Reali

(webpage) My research combines behavioral experiments and probabilistic models to study various aspects of language learning and processing. I am also interested in exploring some theoretical aspects of language evolution, including the interaction between cultural transmission, biological adaptation and individual learning.

Adam Sanborn

I am interested in how perceptual categories are built and structured and how people use these categories to make decisions. Using Bayesian methods and behavioral experiments, I am developing methods for efficiently learning about natural categories, as well as exploring rational models of categorization and intuitive dynamics.

Frank Wood

My research effort is directed towards both contributing models and algorithms to the field of statistical machine learning and figuring out how the brain works.