Untitled Algorithmic Dance

Algorithms are driving our lives. How can we harness algorithms for art and use them within a digital performance practice? When can machine learning be used to expand and explore a creative process? By working with the machine learning algorithm, t-SNE, data can become performed through live coding. Technically, the t-Distributed Stochastic Neighbor Embedding (t-SNE) is a technique for dimensionality reduction that is used for the visualization of high-dimensional datasets. It is used in research in the sciences for biomedical, computer security and other fields with large data sets. Within this dance, images of bodies in motion are feed into the algorithm, producing new possibilities for live performance and the creation of new choreographic scores. —

Previous Performances

  • Nov 2016, International Festival of Algorithmic and Mechanical Movement, Sheffield UK
  • May 2017, Brown University, Providence RI
  • May 2017, Creative Tech Week, New York City NY
  • Sept 2017, The Conference, Malmo Sweden