Nina Miolane

Assistant Professor, Electrical and Computer Engineering, UC Santa Barbara

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Nina’s research focuses on developing AI and machine learning methods to understand the brain—both in its healthy and pathological states—across multiple scales, and to explore how these processes vary by sex and subpopulation. A key challenge in AI is its dependence on large datasets, which are often scarce in neuroimaging due to the significant financial and time demands of data acquisition. To address this limitation, Nina’s work centers on designing data-efficient learning algorithms. In recognition of her work, Nina received several awards including the NSF CAREER Award, Hellman Fellowship, and L’Oréal-UNESCO For Women in Science Award. Nina also serves as Co-Director of the AI Core for the Bowers Women’s Brain Health Initiative, a research center dedicated to studying women’s brains across key life transitions such as pregnancy and menopause.

Speaker, Datathon Committee