Our lab aims to understand the ingredients of intelligence. We use advances in machine intelligence to better understand human intelligence, and use insights from human intelligence to develop more fruitful kinds of machine intelligence.

In our pursuits, we study human cognitive abilities that elude the best AI systems. While there are many to choose from, our current focus includes concept learning, compositional generalization, question asking, goal generation, and abstract reasoning. Our technical focus includes neuro-symbolic modeling and learning “through the eyes of a child” on developmentally-realistic datasets.

By studying distinctively human endeavors, there is opportunity to advance both cognitive science and AI. In cognitive science, if people have abilities beyond the reach of algorithms, then we do not fully understand how these abilities work. In AI, these abilities are important open problems with opportunities to reverse-engineer the human solutions.

Please see my main page for more information.