Mayank Agrawal

mayank dot agrawal at princeton dot edu

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I study the computational foundations of human cognition. My research is largely interdisciplinary and uses the toolkit of cognitive (neuro)science, machine learning, and analytic philosophy to understand high-level cognitive functions such as learning, decision-making, memory, and control.

Specifically, my academic research programs can be summarized as:


Stress, Intertemporal Choice, and Mitigation Behavior During the COVID-19 Pandemic
Mayank Agrawal, Joshua C. Peterson, Jonathan D. Cohen, Thomas L. Griffiths
Journal of Experimental Psychology: General

A Computational Model of Unintentional Mind Wandering in Focused Attention Meditation
Isaac Christian and Mayank Agrawal
Proceedings of the 44th Annual Conference of the Cognitive Science Society

Using Large-Scale Experiments and Machine Learning to Discover Theories of Human Decision-Making
Joshua C. Peterson, David D. Bourgin, Mayank Agrawal, Daniel Reichman, Thomas L. Griffiths

The Temporal Dynamics of Opportunity Costs: A Normative Account of Cognitive Fatigue and Boredom
Mayank Agrawal, Marcelo G. Mattar, Jonathan D. Cohen, Nathaniel D. Daw
Psychological Review

Scaling up Psychology via Scientific Regret Minimization
Mayank Agrawal, Joshua C. Peterson, Thomas L. Griffiths
Proceedings of the National Academy of Sciences

Pyglmnet: Python Implementation of Elastic-net Regularized Generalized Linear Models
Mainak Jas, Titipat Achakulvisut, Aid Idrizović, Daniel Acuna, Matthew Antalek, Vinicius Marques, Tommy Odland, Ravi Garg, Mayank Agrawal, Yu Umegaki, Peter Foley, Hugo Fernandes, Drew Harris, Beibin Li, Olivier Pieters, Scott Otterson, Giovanni De Toni, Chris Rodgers, Eva Dyer, Matti Hamalainen, Konrad Kording, Pavan Ramkumar
Journal of Open Source Software

Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning
Mayank Agrawal, Joshua C. Peterson, Thomas L. Griffiths
Proceedings of the 41st Annual Conference of the Cognitive Science Society

Predicting Beta Bursts From Local Field Potentials to Improve Closed-Loop DBS Paradigms in Parkinson's Patients
Eduardo M. Moraud, Gerd Tinkhauser, Mayank Agrawal, Peter Brown, Rafal Bogacz
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

working papers

Maxim Consequentialism for Bounded Agents
Mayank Agrawal and David Danks

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