William Holmes

William Holmes

Associate Professor, Cognitive Science

All Publications


  • B.S. Engineering Physics, University of Tennessee, 2005
  • PhD Mathematics, Indiana University, 2010

Research interests

My research uses mathematical and computational modeling tools to better understand living processes. My interests span both computational biology (including the study of cellular and developmental processes) and cognitive science. With regard to the latter, my lab develops data-driven models and tools to study cognition. From a theoretical perspective, I construct probabilistic models of human decision making to facilitate the testing of theories of decision making. For example, how do changes in attention influence decisions. I have also recently begun coupling machine learning models with cognitive models to study decisions involving naturalistic information. As an example, we have coupled neural network models of image processing with decision models to study medical image based decisions. In order to test the theories encoded in these models, I develop high performance computational methods for fitting and comparing these complex models to experimental data. In all of these endeavors, the goal is to develop tools to extract as much information as possible from empirical data to better understand aspects of cognition.

Professional Experience

  • Lecturer, Department of Mathematics and Statistics, University of Melbourne, 2014-2015
  • Assistant Professor, Department of Physics, Vanderbilt University, 2015-2022
  • Associate Professor, Program in Cognitive Science, Indiana University, 2022-Present

Representative publications

Disentangling prevalence induced biases in medical image decision-making (2021)
Jennifer S. Trueblood, Quentin Eichbaum, Adam C. Seegmiller, Charles Stratton, Payton O'Daniels and William R.Holmes
Cognition, 212

A Bayesian approach to parameter inference for a wide class of binary evidence accumulation models (2022)
Matthew Murrow and William R Holmes

Urgency, leakage, and the relative nature of information processing in decision-making (2021)
Jennifer S. Trueblood, Andrew Heathcote, Nathan J. Evans and William R. Holmes
Psychological Review, 128 (1), 160-186

A Joint Deep Neural Network and Evidence Accumulation Modeling Approach to Human Decision-Making with Naturalistic Images (2020)
William R. Holmes, Payton O'Daniels and Jennifer S. Trueblood
Computational Brain and Behavior, 3 1-12

A practical guide to the Probability Density Approximation (PDA) with improved implementation and error characterization (2015)
William R. Holmes
Journal of Mathematical Pyschology, 68-69 13-24