Brenden Lake

Brenden Lake is an AI researcher who uses ideas from cognitive science to study machine learning and human intelligence. He studied Symbolic Systems at Stanford and earned a Ph.D. in Cognitive Science at MIT. His work includes an AI program for one-shot handwritten-character learning, meta-learning for compositional generalization, and language learning from a child's recorded experience. He is an associate professor of computer science and psychology at Princeton, where he teaches Computational Models of Cognition in Fall 2026.

Now at: Princeton University
Works: 171
Citations: 8,324
h-index: 27

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

2009–2014

Stanford and MIT degrees

Lake earns B.S. and M.S. degrees in Symbolic Systems at Stanford in 2009 and completes a Ph.D. in Cognitive Science at MIT in 2014.
2014–2025

Fellow and professor at NYU

He serves as a postdoctoral Data Science Fellow at NYU from 2014 to 2017. He joins NYU's faculty in 2017 and serves there through 2025, most recently as an associate professor of psychology and data science.
2015

The Glushko dissertation prize

In 2015, the Cognitive Science Society awards him the Glushko Dissertation Prize for his 2014 MIT thesis, “Towards more human-like concept learning in machines: Compositionality, causality, and learning-to-learn.”
2018

Innovators Under 35

In 2018, MIT Technology Review names him to its Innovators Under 35 list. His AI program learns novel handwritten characters from a single example at human-level performance.
2023

Meta-learning for compositionality

In 2023, Lake and Marco Baroni introduce meta-learning for compositionality (MLC), a learning procedure that improves a neural network's compositional skills over a series of episodes. They test it on tasks with human participants.
2024

Language learning from child experience

In 2024, he and colleagues publish a Science study that trains a multimodal AI system on headcam recordings from one child, from six months through the second birthday. The model learns many words and concepts from slices of that child's everyday experience.
Since 2025

Associate professor at Princeton

He joins Princeton in 2025 as an associate professor of computer science and psychology and principal investigator of the Human & Machine Intelligence lab. His lab uses machine intelligence to understand human intelligence. In Fall 2026, he teaches Computational Models of Cognition.

Career

Since 2025Princeton UniversityAssociate Professor of Computer Science and Psychology, Principal Investigator
2014–2025New York UniversityPostdoctoral Data Science Fellow, Associate Professor of Psychology and Data Science