About Me

I'm an Assistant Professor in the Faculty of Computing and Data Sciences at Boston University. Before starting at BU, I completed my PhD at UC Berkeley as a member of the Berkeley Artificial Intelligence Research Lab studying the intersection of machine learning and cognitive science. I continued this work as a postdoc at Princeton University in the Department of Computer Science. My recent work explores how machine learning can be used to automate the search for interpretable, high-precision models of human behavior.

Featured Publications

Deep models of superficial face judgments

Joshua Peterson, Stefan Uddenberg, Thomas, Griffiths, Alexander Todorov, Jordan Suchow (in press)

Proceedings of the National Academy of Sciences (PNAS)

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Using large-scale experiments and machine learning to discover theories of human decision-making

Joshua Peterson, David Bourgin, Mayank Agrawal, Daniel Reichman, Thomas Griffiths (2021)

Science

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Capturing human categorization of natural images by combining deep networks and cognitive models

Ruairidh Battleday*, Joshua Peterson*, Thomas Griffiths (2020)

Nature Communications

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* equal contribution

Scaling up psychology via Scientific Regret Minimization

Mayank Agrawal, Joshua Peterson, Thomas Griffiths (2020)

Proceedings of the National Academy of Sciences (PNAS)

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Featured Conference Papers

Human uncertainty makes classification more robust

Joshua Peterson*, Ruairidh Battleday*, Thomas Griffiths (2019)

IEEE International Conference on Computer Vision (ICCV)

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* equal contribution

Cognitive model priors for predicting human decisions

David Bourgin*, Joshua Peterson*, Daniel Reichman, Thomas Griffiths, Stuart Russell (2019)

International Conference on Machine Learning (ICML)

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* equal contribution