Alexander Ku
I'm a PhD student in Psychology and Neuroscience at Princeton, where I work with
Tom Griffiths and
Jon Cohen,
and also a Research Scientist at Google DeepMind.
Before this, I received my BA and MS in Computer Science from UC Berkeley.
My research focuses on how neural systems balance flexibility and efficiency in adapting to complex, dynamic environments.
Central to this balance is the way information about the external world is internally represented.
This includes examining the computational costs associated with maintaining and processing different types of representations,
the mechanisms by which representations are transformed or consolidated over time,
and how these processes are optimized across multiple timescales.
The goal is to better understand how representational formats support adaptive cognition and behavior,
and to use these insights to guide the development of artificial systems that can adapt to continual change.
Keywords: Continual Learning, Meta-Learning, Cognitive Control, Automaticity
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