Researchers at The University of Texas at Austin received a $643,719 research award announced on October 23, 2026, to develop an AI-driven movement language model.
Project Details and Goals
Sinclair Emoghene of UT Austin’s Department of Theatre and Dance and Lillian Chin of the Chandra Family Department of Electrical and Computer Engineering received a $643,719 research award. The project explores how AI can learn from human movement and interaction.
The research utilizes sensor technology developed by Chin’s lab to capture movement, touch, force, and pressure data from recordings of dancers. The team has processed 155 dance recordings from 33 countries and plans to grow their collection to 500-plus recordings from more than 40 countries.
Interdisciplinary Collaboration
Emoghene and Chin met at a UT Austin new faculty orientation event and discovered a shared interest in movement and technology. Working alongside students in both the arts and engineering, the pair used custom-built sensors to capture dancers' movements.
The research demonstrates how interdisciplinary collaboration can spark new approaches to both AI development and the study of dance, cultures, and histories.
Key facts and where they come from
- Researchers received a $643,719 research award to develop an AI-driven movement language model.
received a $643,719 research award to develop an AI-driven movement language model.
- The team has already processed 155 dance recordings from 33 countries.
The team has already processed 155 dance recordings from 33 countries.
- The researchers plan to expand their collection to 500-plus recordings from more than 40 countries.
They plan to grow their collection to 500-plus recordings from more than 40 countries.
