Chris Donahue

Chris Donahue

Dannenberg Assistant Professor

Computer Science Department, Carnegie Mellon University

About

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I am an Assistant Professor in the Computer Science Department at Carnegie Mellon University, and also a Research Scientist at Google DeepMind on the Magenta team (part-time).

My research goal is to develop and responsibly deploy generative AI for music and creativity, thereby unlocking and augmenting human creative potential. To this end, my work involves (1) improving machine learning methods for controllable generative modeling for music, audio, and other sequential data, and (2) deploying real-world interactive systems that allow a broader audience—inclusive of non-musicians—to harness generative music AI through intuitive controls.

I am particularly drawn to research ideas with direct real-world applications, and my work often involves building systems for real users to be evaluated in-the-wild. For example, my work on Piano Genie was used in a live performance by The Flaming Lips, and my work on Dance Dance Convolution powers Beat Sage, a live service used by thousands of users a day to create multimodal music game content.

Previously, I was a postdoc at Stanford CS advised by Percy Liang. Before that, I completed a PhD at UCSD co-advised by Miller Puckette and Julian McAuley.

News

G-CLef

Our group's logo, a mashup of a treble clef (G-Clef) and CMU's mascot Scotty created with DALL-E 2.

I lead the Generative Creativity Lab (G-CLef) at CMU. Our mission is to empower and enrich human creativity and productivity with generative AI. We focus primarily on the intersection of music and AI, though we also work on other applications such as programming, gaming, and natural language. Please visit this page to learn more about our research interests and to apply.

Mentees

Irmak Bukey CSD PhD student
Irmak Bukey
CSD PhD student

Wayne Chi CSD PhD student Coadvised w/ Ameet T.
Wayne Chi
CSD PhD student
Coadvised w/ Ameet T.
Yewon Kim CSD PhD student
Yewon Kim
CSD PhD student

Nathan Pruyne CSD PhD student
Nathan Pruyne
CSD PhD student

Alumni

Alexander Wang Music Tech MS student Now PhD @ CMU HCII (incoming)
Alexander Wang
Music Tech MS student
Now PhD @ CMU HCII (incoming)
Yichen (William) Huang Visiting researcher
Yichen (William) Huang
Visiting researcher

Xun (Rick) Zhou CS MS studentNow Quant @ Minhong
Xun (Rick) Zhou
CS MS student
Now Quant @ Minhong
Shih-Lun Wu LTI MS student Now PhD @ MIT EECS
Shih-Lun Wu
LTI MS student
Now PhD @ MIT EECS

Recent Papers

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Yewon Kim, Sung-Ju Lee, Chris Donahue (2024). Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations. In CHI 2025.

arXiv PDF BibTeX Sound 🔊

Satvik Dixit, Laurie M. Heller, Chris Donahue (2024). Vision Language Models Are Few-Shot Audio Spectrogram Classifiers. In NeurIPS Audio Imagination Workshop 2024.

arXiv PDF BibTeX

Xun Zhou, Charlie Ruan, Zihe Zhao, Tianqi Chen, Chris Donahue (2024). Local Deployment of Large-Scale Music AI Models on Commodity Hardware. In ISMIR LBD 2024.

arXiv PDF BibTeX 🕹️ Demo

Irmak Bukey, Michael Feffer, Chris Donahue (2024). Just Label the Repeats for In-The-Wild Audio-to-Score Alignment. In ISMIR 2024.

arXiv PDF BibTeX Code Video Examples

Chris Donahue, Shih-Lun Wu, Yewon Kim, Dave Carlton, Ryan Miyakawa, John Thickstun (2024). Hookpad Aria: A Copilot for Songwriters. In ISMIR LBD 2024.

arXiv PDF BibTeX Project Page

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