AI Seminar sponsored by Apple

Gus Guangyu Xia -- Better Music Representation Learning Using Inductive Bias: Mind vs. Machine

Abstract: Gus works on music AI systems for intimate human-computer interaction and co-creation. In this talk, he will present two recent prototype systems: the multimodal flute tutor and the interpretable deep music composer. The former is a hyper instrument which guides human motion and makes music learning more efficient and enjoyable. The latter is a general framework for learning disentangled representation. We will see that for both human learning and machine learning, inductive bias plays an important role. At the end of the talk, Gus will show his vision on merging these two efforts for new music experiences.

Bio: Gus is an Assistant Professor in Computer Science at NYU Shanghai. He received his Ph.D. in the Machine Learning Department at Carnegie Mellon University in 2016 and was a Neukom Fellow at Dartmouth from 2016 to 2017. Gus is also a professional DI and XIAO (Chinese flute and vertical flute) player.