Andrew Lampinen is a research scientist at DeepMind. His research focuses on cognitive flexibility and generalization. 

Andrew’s PhD thesis is titled "A Computational Framework for Learning and Transforming Task Representations", which he completed in 2020 at Stanford University.

We talk about cognitive flexibility in brains and machines, centered around his work in the thesis on meta-mapping. We cover a lot of interesting ground, including complementary learning systems and memory, compositionality and systematicity, and the role of symbols in machine learning.

- Episode notes: https://cs.nyu.edu/~welleck/episode38.html

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[38] Andrew Lampinen - A Computational Framework for Learning and Transforming Task Representations

Each episode of The Thesis Review is a conversation centered around a researcher's PhD thesis, giving insight into their history, revisiting older ideas, and providing a valuable perspective on how their research has evolved (or stayed the same) since.