Daniel L. Yamins

In order to reach the level of intelligence that humans possess, artificial agents need to be able to autonomously interact with other agents and humans and build rich models of how other minds work as a result of these interactions.

Dr. Daniel Bear propose to augment state-of-the-art neural networks with two biologically-inspired properties: the ability to represent the physical world as it changes over time and the ability to learn from self-created signals rather than explicit human instruction.

Investigating how the brain develops from infancy to adulthood across species, focusing on how the interplay between structural development, functional development, experience and affect brain computations and ultimately behavior.