10/26/2026
Dance carries knowledge about how people live: their landscapes, communities and histories. Now a UT Austin team is working to teach AI to read it through motion-capture technologies to help preserve these traditions and uncover new knowledge.
Dance Assistant Professor Sinclair Emoghene and Engineering Assistant Professor Lillian Chin will lead the Movement Language Model, a project funded by a $643,719 grant from the Humanities and AI Virtual Institute at Schmidt Sciences. The team will analyze dance recordings from around the world to explore how geography and culture shape movement and to preserve the knowledge embedded these traditions hold as they evolve.
https://finearts.utexas.edu/news/dance-engineering-professors-team-build-ai-model-can-read-dance-movement