Making Sense of the Brain
Eva Dyer is at the forefront of the surge in computational neuroscience research at Georgia Tech
When someone asks Eva Dyer what she does for a living, she has a short and simple answer: “I try to teach machines how to understand the brain.”
As the principal investigator of the Neural Data Science Lab — or NerDS Lab — at the Georgia Institute of Technology she leads a diverse team of researchers in developing machine learning approaches to analyze and interpret massive, complex neural datasets. At the same time, they are designing better machines, inspired by the organization and function of biological brains.
The work they’re presenting — about a new set of tools in self-supervised learning, a method of machine learning that more closely imitates how humans classify objects — is the NerDS Lab’s latest contribution in addressing one of the biggest challenges in neuroscience: finding simplified representations of neural activity that allow for greater insights into the link between the brain and behavior.