Akshay K. Jagadish is a Peretsman-Scully Postdoctoral Fellow at the Princeton AI Lab. His research draws on the latest advancements in machine learning and artificial intelligence to:
- Characterize determinants of human behavior using meta-learning[1][2][3].
- Discover mechanisms underlying human behavior using behavior-conditioned program synthesis[1][2].
- Uncover universal laws of behavior from large-scale behavioral datasets[1][2] using agentic AI.
Before joining Princeton, he spent six wonderful years in Germany, where he earned a Ph.D. in Computer Science and an M.Sc. in Computational Neuroscience at the University of Tübingen under the mentorship of Eric Schulz and Marcel Binz. His research has been featured in popular press, including The New York Times[1][2], Fortune[3], Tagesspiegel[4], and Science Daily[5].
Key Publications
Jagadish, A. K., Witte, K., Mathony, M., Binz, M., & Schulz, E. (2026). Toward an Automated Science of the Mind. Neuron.
Jagadish, A. K.*, Strittmatter, Y.*, Jacoby, N., Kachergis, G., Schulz, E., Daw, N., Chandramouli, S. H., & Griffiths, T. L. (2026). Closing the Loop to Discover Psychological Theories with an Automated Cognitive Scientist. Preprint.
Rmus, M.*, Jagadish, A. K.*, Mathony, M., & Schulz, E. (2025). Generating Computational Cognitive Models using Large Language Models. Advances in Neural Information Processing Systems (NeurIPS), San Diego, USA.
Jagadish, A. K., Thalmann, M., Coda-Forno, J., Binz, M., & Schulz, E. (2025). Meta-learning Ecological Priors from Large Language Models explains Human Learning and Decision making. Under review.
Strittmatter, Y., Griffiths, T. L., & Jagadish, A. K. (2026). Pipeline for Systematic Curation of Human Experiments. Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci).