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
Capturing the Complexity of Human Strategic Decision-Making with Machine Learning
Zhu Jian-Qiao, Joshua Peterson, Benjamin Enke, Thomas Griffiths (In Revision)
PDFDeep models of superficial face judgments
Joshua Peterson, Stefan Uddenberg, Thomas Griffiths, Alexander Todorov, Jordan Suchow (2022)
Proceedings of the National Academy of Sciences (PNAS)
PDF DATASETUsing 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
PDF DATASETCapturing human categorization of natural images by combining deep networks and cognitive models
Ruairidh Battleday*, Joshua Peterson*, Thomas Griffiths (2020)
Nature Communications
PDF DATASET* equal contribution
Scaling up psychology via Scientific Regret Minimization
Mayank Agrawal, Joshua Peterson, Thomas Griffiths (2020)
Proceedings of the National Academy of Sciences (PNAS)
PDF DATASETFeatured Conference Papers
Human uncertainty makes classification more robust
Joshua Peterson*, Ruairidh Battleday*, Thomas Griffiths (2019)
IEEE International Conference on Computer Vision (ICCV)
PDF DATASET* 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)
PDF DATASET* equal contribution