We reveal the geometric signatures of natural and artificial intelligence.
Understanding the brain is one of greatest scientific challenges of our time. We still don't know how thoughts emerge from neural activity, how our memories are stored and retrieved, or how our brain so flexibly adapts to new situations.
Meanwhile, today, an equally profound challenge has arisen: understanding the artificial intelligence (AI) emerging in machines of our own making.
In our lab, we believe that these challenges are linked.
Geometric Intelligence Research
We are physicists, neuroscientists, mathematicians and computer scientists who study intelligence in biological and artificial neural networks and use our findings to build better AI models.
Just as physics unified forces through symmetry and geometry, we show mathematically and empirically that human and machine intelligence can be studied under a common framework: geometric intelligence.
Geometric Intelligence in Machines
We study the mathematical properties of top-performing AI models. Using these properties, we design novel AI that succeeds where most models fail—delivering up to +66% higher accuracy or the same accuracy with 10× faster models—even when datasets are small, noisy, or complex (e.g., networks, and 3D shapes). Learn more.
Geometric Intelligence in Brains
We study how geometric patterns of neural activity obey mathematical principles across diverse cognitive functions—from navigation and memory to vision. Learn more.
Building Brain Digital Twins
We leverage shared mathematical principles of intelligence in brains and machines to build multiscale digital twins of the brain, simulating its function in both health and disease. Learn more.
Latest News
Mathilde Papillon Receives the Best Paper Award at EAI ArtsIT
Mathilde Papillon, Ph.D. student in the Geometric Intelligence Lab, receives the prestigious Best Paper Award at the conference EAI ArtsIT for her work: "PirouNet: Creating Dance through Artist-Centric Deep Learning" with Mariel Pettee and Nina Miolane.
Read MoreMathilde Papillon Receives the Best Paper Award at EAI ArtsIT
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