Distinguished Lecturer Seminar: Rebecca Fiebrink - Creative uses of machine learning in music performance
Date and Time Wednesday, 19th October, at 3:00pm
Place BR 3.02, Bancroft Road Teaching Rooms, Peter Landin Building, Queen Mary University of London, Mile End Road, London E1 4NS. Information on how to access the school can be found at here.
Speaker Rebecca Fiebrink
Title Creative uses of machine learning in music performance
Abstract Dr. Rebecca Fiebrink will discuss some highlights from her work using machine learning techniques to enable composers and instrument builders to design new musical instruments and performances. She will discuss how machine learning techniques can be used as design tools to enable rapid prototyping, iterative refinement, and embodied engagement— all activities that are crucial in the design of new creative interactions. Dr. Rebecca Fiebrink will also mention some recent work from her lab, exploring new approaches to using data to enable latency-free networked performance and personalised audience experiences. She will also show a live demo of software that she has created to enable composers, students, and people with disabilities to easily build new musical interactions.
Bio Dr. Rebecca Fiebrink is a Lecturer at Goldsmiths, University of London. Her research focuses on designing new ways for humans to interact with computers in live music performance and other creative practice. She is the developer of the Wekinator software for interactive machine learning, and she recently taught the world’s first MOOC (“Massively open online course”) about machine learning for artists and musicians. She has worked with companies including Microsoft Research, Sun Microsystems Research Labs, 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 in 2011. Prior to moving to Goldsmiths, she was an Assistant Professor at Princeton University, where she co-directed the Princeton Laptop Orchestra.