Anna Huang

Anna Huang is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the PI Core/Dual program. Her research focuses on AI-driven music technologies, including human-AI collaboration, generative music models, and interactive creative tools. She specializes in developing frameworks for real-time music jamming, adaptive accompaniment systems, and novice-friendly AI co-creation platforms. Huang has contributed to projects like the Bach Doodle and the AI Song Contest, demonstrating scalable applications of machine learning in music composition.

Her work bridges computer science and musicology, with a particular emphasis on cross-cultural music generation (e.g., Hindustani classical music modeling) and expressive control mechanisms for generative systems. Key areas include MIDI signal processing, source separation algorithms, and the design of user interfaces that empower both professionals and novices to co-create with AI.

Huang’s publications emphasize interdisciplinary innovation, with trends spanning reinforcement learning for music performance, hierarchical generative modeling, and ethical considerations in AI-assisted creativity. Though no awards are explicitly listed, her impactful projects suggest recognition in computational music research.

Her research also involves dataset development (e.g., MAESTRO dataset) and open-source tools like Coconet, fostering reproducibility and community engagement in music technology.