Memory and Decision Making Lab



Michael Lee

mathematical and computational models of stimulus representation, categorization, memory, decision-making, problem solving



Mark Steyvers

higher-order cognition, cognitive neuroscience, computational modeling, collective intelligence



Joachim Vandekerckhove from CIDLAB

response time modeling, model fitting, computational statistics, psychometrics, Bayesian statistics


Current Graduate Students

5th Year

Beth Baribault from CIDLAB

computational neuroscience (joint modeling of neural and behavioral data); cognitive modeling (developing new computational tools for psychological research in a bayesian framework by fusing traditionally disparate methods in modeling); bayesian statistics (overcoming biases in the research process through computational means)

Irina Danileiko

I do cognitive modeling of the processes governing categorization behavior as well as the processes of people’s ability to make probability judgments. I’m also interested in applying these cognitive models for getting better predictions of decision making problems using the wisdom of crowds approach.

CV. LinkedIn

Garren Gaut

Research interests include text processing, predicting cognitive intelligence from neural measures, and methods for statistics and machine learning.


Maime Guan

I’m interested in quantitative and computational models of risky decision making, Bayesian statistics, and methods for integrating psychometric models of individual differences with cognitive models. I am also interested in Bayesian approaches to detecting and mitigating some of the consequences resulting from current issues in psychological science (e.g. publication bias, fraud).

Website. LinkedIn

Percy Mistry

My research interests span human learning, causal reasoning, decision making, and meta-cognitive processes. I am especially interested in how these behavioral aspects respond to dynamic and changing environments, and the role of individual differences. I combine behavioral experiments with mathematical and computational modeling of cognition.

Website. LinkedIn.


4th Year

Stephen Bennett

higher-order cognition, metacognitive control, Bayesian cognitive modeling, wisdom of the crowd/collective intelligence, opting-in.


Colin Kupitz from CIDLAB

I’m interested broadly in human intelligence, although I particularly focus on A) how to accurately measure it and B) can it be improved. My research involves developing cognitive latent variable models to describe the cognitive processes involved in transfer-of-training studies, and I hope to use this CLVM approach to develop new standards of intelligence testing based on cognitive process models.


2nd Year

Alexander Etz from CIDLAB

Interested in Bayesian statistics, publication bias corrections for meta-analysis, open science, statistical cognition.

CV. Website.


1st Year

Arseny Moskvichev