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 Work
Capturing the complexity of human strategic decision-making with machine learning
Zhu Jian-Qiao, Joshua Peterson, Benjamin Enke, Thomas Griffiths (2025)
Nature Human Behavior
PDFA foundation model to predict and capture human cognition
Marcel Binz, ..., Joshua Peterson, [full author list] (2025)
Nature
PDFPredicting Human Decisions with Behavioral Theories and Machine Learning
Ori Plonsky, ..., Joshua Peterson, [full author list] (2025)
Nature Human Behavior
PDFLarge language models assume people are more rational than we really are
Ryan Liu, Jiayi Geng, Joshua Peterson, Ilia Sucholutsky, and Thomas Griffiths (2025)
ICLR
PDFOn the informativeness of supervision signals
Ilia Sucholutsky, Ruairidh Battleday, Katherine Collins, Raja Marjieh, Joshua Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, and Thomas Griffiths (2023)
UAI
PDFDeep models of superficial face judgments
Joshua Peterson, Stefan Uddenberg, Thomas Griffiths, Alexander Todorov, Jordan Suchow (2022)
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)
PNAS
PDF DATASETHuman uncertainty makes classification more robust
Joshua Peterson*, Ruairidh Battleday*, Thomas Griffiths, Olga Russakovsky (2019)
ICCV
PDF DATASET* equal contribution
Cognitive model priors for predicting human decisions
David Bourgin*, Joshua Peterson*, Daniel Reichman, Thomas Griffiths, Stuart Russell (2019)
ICML
PDF DATASET* equal contribution
Other Work
Machine learning for modeling human decisions
Daniel Reichman, Joshua Peterson, and Thomas Griffiths (2024)
Decision
PDFThe Universal Law of Generalization holds for naturalistic stimuli (APA's Editor's Choice)
Raja Marjieh, Nori Jacoby, Joshua Peterson, and Thomas Griffiths (2024)
JEP: General
PDFStress, intertemporal choice, and mitigation behavior during the COVID-19 pandemic
Mayank Agrawal, Joshua Peterson, Jonathan D. Cohen, and Thomas Griffiths (2023)
JEP: General
PDFFrom convolutional neural networks to models of higher-level cognition (and back again)
Ruairidh Battleday*, Joshua Peterson*, Thomas Griffiths (2021)
Annals of the New York Academy of Sciences
BibTeX PDF* equal contribution