I am an Assistant Professor at UC Santa Barbara, where I direct the Geometric Intelligence Lab and co-direct the REAL AI for Science Initiative and the AI Core of the Bowers Women’s Brain Health Initiative. I earned degrees in mathematics and physics from École Polytechnique and Imperial College London, completed my Ph.D. at INRIA, and my postdoc at Stanford.

My research sits at the intersection of mathematics, artificial intelligence, and neuroscience. I use mathematics to unify the study of intelligence in brains and machines. In neuroscience, we still don’t know how large populations of neurons give rise to perception, memory, and learning. In AI/ML, we face significant challenges to understand systems of our own making, leaving them hard to control and trust. My hypothesis is that we lack appropriate mathematics that reveals the principles of intelligence in brains and machines. My research develops the missing framework, uses it to formalize a theory of intelligence across substrates, and builds it into novel artificial neural networks to deliver superior performance without necessarily scaling data, parameters, or compute.

At REAL AI for Science, I use our AI models to build digital twins of the brain—integrating imaging, cognition, and molecular data to forecast brain health, detect disease early, and support personalized care. With the Bowers Women’s Brain Health Initiative, I focus on women’s brains, building digital twins across pregnancy, menopause, and aging—to close long-standing gaps in women’s health research.

My work has been recognized by the Hellman Fellowship, the NSF CAREER, the UC Regent’s Junior Faculty Award, the TIME Best Invention of the Year, and the L’Oréal-Unesco Award for Women in Science. Breakthroughs from my research are regularly featured in the media.

Find me on: Github, LinkedIn, Twitter: @ninamiolane, Bluesky: @ninamiolane.bsky.social, Google Scholar, ORCID.

Contact: ninamiolane at ucsb.edu.