We reveal the geometric signatures of natural and artificial intelligence.
We are physicists, neuroscientists, statisticians, mathematicians and computer scientists who develop methods to understand intelligence in human and artificial neural networks.
We use tools from geometry, topology, computer vision, machine learning and deep learning to reveal the structures of intelligence. Our findings inspire us to build next–generation intelligent systems: Geometric AI.
By creating geometric computational representations of human and artificial brains at different scales, we aim to transform theoretical, computational and clinical brain sciences. For the latter, we work with clinicians to advance medical knowledge and AI-assisted medical practice for brain sciences.
Geometric Intelligence Research
Geometry
The concepts of geometry and shapes are very intuitive to the human eye. How can we express and quantify geometries and shapes mathematically and in a computer? Learn more.
Artificial Intelligence
We research foundations of geometric deep learning and topological deep learning and ask: what is the geometry of a deep learning model? Can we build a geometric model of the (artificial) mind? Learn more.
Natural Intelligence
We explore the neural manifold hypothesis which postulates that the activity of (biological) neurons forms low-dimensional geometric subspaces -- the neural manifolds -- that reflect the structure of the outside world. Learn more.
Intelligence-Based Medicine
What are the geometric signatures of neurodegenerative diseases: what does a brain shape tell us about the progression of Alzheimer's disease? Why are women are twice at risk of Alzheimer's compared to men? Learn more.
Latest News
Watch Nina Miolane's Keynote at the CVPR Workshop on Deep Learning for Geometric Computing
Nina Miolane, PI of the Geometric Intelligence Lab, presented the work of our group at the workshop "Deep Learning for Geometric Computing". Watch the video here!
Read MoreWatch Nina Miolane's Keynote at the CVPR Workshop on Deep Learning for Geometric Computing
Nina Miolane Receives Regents' Junior Faculty Award
Nina Miolane, PI of the Geometric Intelligence Lab, receives the UC Regents' Junior Faculty Fellowship Award!
This award, presented by the UCSB Academic Personnel Office, supports outstanding junior faculty in their development of the substantial record in research and creative work necessary for advancement to tenure.
Read MoreNina Miolane Receives Regents' Junior Faculty Award
We Are Awarded the NSF SCALE MoDL Grant on Mathematical and Scientific Foundations of Deep Learning
We are excited and honored that our group was awarded the NSF SCALE MoDL Grant "Stimulating Collaborative Advances Leveraging Expertise in the Mathematical and Scientific Foundations of Deep Learning". We aim to provide a unified geometric and topological framework grounded in cell complex neural networks to explain and enhance deep learning architectures, with applications to biological shape analysis.
Read MoreWe Are Awarded the NSF SCALE MoDL Grant on Mathematical and Scientific Foundations of Deep Learning