Anna Huang is a Research Scientist at Google Brain, working on the Magenta project. Her research focuses on designing generative models to make creating music more approachable. She is the creator of Music Transformer and also the ML model Coconet that powered Google’s first AI Doodle the Bach Doodle, in 2 days harmonizing 55 million melodies from users around the world.
She holds a PhD in computer science from Harvard University and was a recipient of the NSF Graduate Research Fellowship. She spent the later parts of her PhD as a visiting research student at the Montreal Institute of Learning Algorithms (MILA), where she also currently co-advises students. She publishes in machine learning, human-computer interaction, and music, at conferences such as ICLR, IUI, CHI, and ISMIR. She is currently an editor for the TISMIR journal’s special issue on AI and Music Creativity.
As a composer, she wrote for a cappella, chamber ensembles and orchestra, and also tape and live electronics that was performed on the 40-channel HYDRA loudspeaker orchestra. Recently, she was a judge for the AI Song Contest. She holds a master’s in media arts and sciences from the MIT Media Lab, and a dual bachelor’s degree in computer science and music composition from University of Southern California. She grew up in Hong Kong, where she learned to play the guzheng.
Education: PhD in computer science from Harvard University, B.S. in Computer Science and B.A. Music Composition from University of Southern California
Areas of Focus: Music, Machine Learning, AI
Back to Profiles