Akshay K. Jagadish
Research Fellow, Princeton AI Lab
October 2026 "Toward an automated science of the mind" out in Neuron!
October 2026 Preprint out on "Measuring combinatorial creativity in large language models and humans"
September 2026 Preprint out on "CogGym: Towards Large-Scale Comparative Evaluation of Human and Machine Cognition"
September 2026 Gave a talk at the University of California, Berkeley (Cognitive Science Colloquium, Department of Psychology).
September 2026 Preprint out on "Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans"
September 2026 Preprint out on "Can We Automatize Scientific Discovery in the Cognitive Sciences?"
August 2026 Preprint out on "More accurate behavioral predictions with hybrid Bayesian-connectionist models"
July 2026 Gave a talk at the Cognitive Science Conference (CogSci) 2026 workshop on "Laying the foundations for foundation models of cognition".
June 2026 Preprint out on "Closing the Loop to Discover Psychological Theories with an Automated Cognitive Scientist"
June 2026 Preprint out on "Using Probabilistic Programs to Train Inductive Reasoning in Large Language Models"
June 2026 Selected for the National Geographic Storytellers Workshop!
June 2026 Preprint out on "Meta-learning ecological priors from large language models explains human learning and decision making"
May 2026 Preprint out on "Post-training Makes Large Language Models Less Human-like"
May 2026 "Think-Aloud Reshapes Automated Cognitive Model Discovery Beyond Behavior" accepted at CCN 2026!
May 2026 Gave a talk at Indiana University (Workshop on "Defining the Formal Foundations of Intelligences", Center for Possible Minds).
April 2026 "Automated Adversarial Collaboration for Advancing Theory Building in the Cognitive Sciences" accepted at CCN 2026!
April 2026 "Automated Discovery of Psychological Representations using Language Model Agents", "Pipeline for Systematic Curation of Human Experiments", and "Modeling individual differences in learning and memory using large language models" accepted to CogSci 2026!
April 2026 "Reinforcement learning: computational modeling of learning and decision-making" out in Proceedings of Machine Learning Research!
December 2025 Recognized as a Top 10% Reviewer (main track) for NeurIPS 2025.
November 2025 Gave a talk at New York University (ConCats talk series, Department of Psychology).
October 2025 Gave a talk at Princeton University (Natural and Artificial Minds talk series, Princeton AI Lab).
September 2025 Defended my Ph.D. in Computer Science with Magna cum Laude at the University of Tübingen.
September 2025 "Automated scientific minimization of regret for cognitive modeling" accepted at the AI4Science Workshop at NeurIPS 2025!
September 2025 "Generating computational cognitive models using large language models" accepted at NeurIPS 2025!
September 2025 Gave a talk at the University of Osnabrück (lab meeting, Laboratory for Automated Scientific Discovery of Mind and Brain).
August 2025 Awarded the Peretsman Scully Postdoctoral Fellowship to conduct independent research in the Natural and Artificial Minds program at the Princeton AI Lab.
July 2025 The New York Times featured our work on A foundation model to predict and capture human cognition in a piece titled "Scientists Use A.I. to Mimic the Mind, Warts and All".
April 2025 "Bounded ecologically rational meta-learned inference explains human category learning" accepted at CogSci 2025!
March 2025 The New York Times covered our work in "Digital Therapists Get Stressed Too, Study Finds".
March 2025 Fortune covered our work on "Chat-GPT on the Couch".
March 2025 ScienceDaily covered our work on "Chat-GPT on the Couch".
January 2025 "Sparse autoencoders reveal temporal difference learning in large language models" accepted at ICLR 2025!