We use advanced mathematics to unify the study of intelligence in brains and machines.
We build efficient AI models that succeed where others fail. We deliver up to +66% higher accuracy or the same accuracy with 10× faster models, even when datasets are small, noisy, and complex —such as networks and 3D shapes.
We provide new perspectives in neuroscience, revealing the mathematics that let our brains explore the world, store memories, and master new skills.
Geometric Intelligence Research
Just as physicists uses geometry to build unification theories, we show that brain and machine intelligences can be studied under a common framework: geometric intelligence.
The idea is that data has structure and this structure has power. It helps us redesign the building blocks of AI models to improve their efficiency. It helps us understand how brains compute so effectively.
Geometric Intelligence in Machines
We study the properties of top-performing AI models and design mathematical approaches to improve them. Learn more.
Geometric Intelligence in Brains
We study patterns of neural activity across diverse cognitive functions—from navigation and memory to vision. Learn more.
Building Brain Digital Twins
We use AI models to build digital twins of the brain, simulating its function in both health and disease. Learn more.
Latest News
Adele Myers is Interviewed by the Machine Learning Street Talks Podcast @ NeurIPS
Adele Myers, Ph.D. student in the Geometric Intelligence Lab, is featured in the renowned Machine Learning Street Talks Podcast Series at NeurIPS 2022 for her work: "Regression-Based Elastic Metric Learning on Shape Spaces of Elastic Curves" with Nina Miolane. Watch her interview here!
Read MoreAdele Myers is Interviewed by the Machine Learning Street Talks Podcast @ NeurIPS
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