I received my BA in Mathematics & Physics from UC Berkeley. I went on to pursue my PhD in Cognitive Psychology at Stanford, where I was advised by Jay McClelland. In the dissertation work I will describe in this talk, I focused on how models could flexibly adapt to new tasks, based on their relationship to prior tasks. During my PhD, I also explored other topics, including the role of embodiment and environmental factors in learning and generalization, memory and integration of knowledge, and theory of learning and generalization dynamics. I am currently a Research Scientist at DeepMind, where my research continues to focus on flexibility, memory, and generalization.