Rebecca Fiebrink


Dr. Rebecca Fiebrink is a Lecturer at Goldsmiths, University of London. In her research, she designs new ways for humans to interact with computers in creative practice. She is the developer of the Wekinator software for interactive machine learning, which has been downloaded over 7500 times, and she is the designer of the world’s first MOOC (massively open online course) about machine learning for creative practitioners. She has worked with companies including Microsoft Research, Reactable, ROLI, Sun Microsystems, Imagine Research, and Smule, where she helped to build the #1 iTunes app “I am T-Pain.” She holds a PhD in Computer Science from Princeton University. Prior to moving to Goldsmiths, she was an Assistant Professor at Princeton University, where she co-directed the Princeton Laptop Orchestra.

Sessions at NextM

“Machine Learning as Design Tool”

In this talk, I will show how machine learning can be used as a creative tool. By modelling data that captures how we move, play, and make art and music, machine learning algorithms can help computers understand these very human activities. Furthermore, by making these algorithms useful—and controllable—by artists and designers, we can augment human capabilities and enable people to realise new creative visions. This talk will include live demonstrations of machine learning used to make new musical instruments and interactive art.