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Anna Huang is an Associate Professor at the Massachusetts Institute of Technology (MIT) with a shared appointment in the Music & Theater Arts Section and the Department of Electrical Engineering and Computer Science (EECS). She spent eight years with the Magenta team at Google Brain, where she led initiatives in generative modeling and reinforcement learning to support human-AI partnerships in music-making. Huang is the creator of the Coconet model, which powered Google’s AI Doodle, producing over 55 million harmonized melodies. In 2018, she developed the Music Transformer, which revolutionized music generation through long-term structural generation, gaining recognition at the International Conference on Learning Representations (ICLR). She has also held the Canada CIFAR AI Chair at Mila – Québec AI Institute and has been an adjunct professor at Université de Montréal. Huang earned her PhD from Harvard University and received the NSF Graduate Research Fellowship. She holds a master’s degree from the MIT Media Lab and dual bachelor’s degrees from the University of Southern California in music composition and computer science. As a composer, her works have been performed by mixed chamber groups and orchestras, and she has received accolades for her compositions in competitions such as the San Francisco Choral Artists’ capella contest. Huang actively participates in the AI Song Contest and serves as a guest editor for ISMIR's journal.