Dan Oved

Dan Oved is an artist and engineer whose work is a collaboration between human and machine intelligence, and crosses multiple disciplines, from interactive installation to performance to device. He explores themes of algorithmic decision making, real-time sensing machines, and the conflicting objectives between computers and the humans that created them.

He’s currently a research resident and adjunct at ITP, and works with the New York Times as a research engineer, investigating ways computer vision can be used to reveal information for journalism.  In collaboration with researchers at Google he open-sourced PoseNet and BodyPix, machine learning models that run in the browser and extrapolate the human form from images and video. Previously he worked with the Google Creative Lab and SYPartners.