Kim Stachenfeld.

Kim Stachenfeld

Staff research scientist, Google DeepMind
Adjunct assistant professor, Columbia University

Kim Stachenfeld is staff research scientist at Google DeepMind and adjunct assistant professor at Columbia University’s Center for Theoretical Neuroscience. Her research bridges neuroscience and artificial intelligence, focusing on AI-inspired models of neural computation and the use of AI tools to understand brain data.

Stachenfeld earned her Ph.D. in computational neuroscience from Princeton University in 2018 and a B.S. in chemical and biological engineering and B.A. in mathematics from Tufts University in 2013. Her work has been featured in The Atlantic, Quanta Magazine, Nautilus and MIT Technology Review. In 2019, she was recognized by MIT Technology Review as one of its Innovators Under 35 for her research on predictive representations in the hippocampus.

Explore more from The Transmitter

Illustration of waterfall inside a woman's brain.

Revisiting the neural correlates of consciousness

Life happens in real time, but experience may be composed in ragtime—like the music genre, full of offbeat notes and uneven rhythms. The assumption that waking life consists of a “stream” of conscious representations has inadvertently led consciousness science to its current impasse.

By Francis T. Fallon, Michael Pitts
28 September 2026 | 7 min read
Illustration of rolling dice.

Grant review needs reform. How about we add an element of chance?

A process that uses a lottery system saves time, reduces strategic resubmission and accepts that, above a quality threshold, luck has always played a part in science funding.

By Adrien Peyrache
25 September 2026 | 6 min read
Research diagram of gene expression.

Fly neurons carry molecular signatures of their origins

The pattern of transcription factors a Drosophila neuron expresses offers clues to its lineage and birth order—and ultimately how neural circuits emerge.

By Alissa de Chassey
25 September 2026 | 5 min read