Nicholas J. Bryan

Head of Music AI & Firefly Music
Adobe Research
San Francisco, CA

email: njb at ieee dot org

Nicholas J. Bryan
Research

Generative AI for music and audio, focused on controllable, fast models for human–AI co-creation.

About

I am Head of Music AI & Firefly Music and a Principal Scientist at Adobe Research, where I lead the team behind Adobe Firefly Generate Music and the Firefly Music Model. I received my PhD and MA from CCRMA, Stanford University and MS in Electrical Eng., also from Stanford. Before that, I received my Bachelor of Music and BS in Electrical Eng. with summa cum laude, general honors, and departmental honors at the U. of Miami-FL. I have received 2 best paper awards, 1 AES Graduate Design Gold award, 1 best reviewer award, and 1 best paper finalist acknowledgement. I was general co-chair of WASPAA 2023, a 2x elected member of the IEEE AASP TC, an IEEE Senior Member, and am an Adobe distinguished inventor. I've also been a musician since childhood, performed at Carnegie Hall, and have been on the front-page of the New York Times.


News

[05/2026] Invited Talk at Conversational AI Reading Group at Mila The Grand Design Challenge of Music GenAI
[05/2026] "V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation" arXiv
[05/2026] "Rethinking Music Captioning with Music Metadata LLMs" ICASSP 2026 arXiv
[05/2026] "A Generative-First Neural Audio Autoencoder" ICASSP 2026 arXiv
[05/2026] "Stemphonic: All-at-once Flexible Multi-stem Music Generation" ICASSP 2026 arXiv
[04/2026] Invited Talk Design@Large UCSD w/Orly Lobel and Shahrokh Yadegari, EventBrite Link!
[02/2026] "TAC: Timestamped Audio Captioning" arXiv arXiv
[10/2025] Adobe Firefly Generate Music Released! about the Firefly Music Model, web
[10/2025] TMLR journal paper! DRAGON: Distributional Rewards Optimize Diffusion Generative Models arXiv, web, video
[04/2025] "Beyond Text to Music" Keynote Talk at ICASSP 2025 GenDA Workshop. slides

Adobe Internships

For current students, I offer research internships at Adobe Research in San Francisco, CA. Internships are typically during the summer months and for graduate students studying audio/music signal processing, machine learning, or related field. If you are interested, please send me an email with your CV and research interests in October-December before the given summer. My Adobe webpage is here.


Publications

DITTO-2: Distilled Diffusion Inference-Time T-Optimization for Music Generation

"DITTO-2: Distilled Diffusion Inference-Time T-Optimization for Music Generation"

Z. Novack J. McAuley, T. Berg-Kirkpatrick, N. J. Bryan
arXiv, May, 2024.
International Society for Music Information Retrieval Conference (ISMIR), November, 2024.
(arXiv, web)

"Music ControlNet: Multiple Time-varying Controls for Music Generation"

S-L. Wu C. Donahue, S. Watanabe, N. J. Bryan
IEEE Transactions on Audio, Speech, and Language Processsing (TASLP), November, 2023.
(arXiv, web, video)

"Meta-AF: Meta-learning for Adaptive Filters."

J. Casebeer N. J. Bryan, P. Smaragdis
IEEE Transactions on Audio, Speech, and Language Processsing (TASLP), January, 2022.
Presented at IEEE International Conf. on Acoustics, Speech, and Signal Processing (ICASSP), June, 2023.
(TASLP, arXiv, web, code, video)

"Style Transfer of Audio Effects with Differentiable Signal Processing."

C. J. Steinmetz, N. J. Bryan, J. D. Reiss,
Journal of the Audio Engineering Society (JAES), September, 2022.
Presented at 154th AES Europe Convention, May, 2023.
(arXiv, code, demo)
Meta-learning for Adaptive Filters with Higher-order Frequency Dependencies.

"Meta-learning for Adaptive Filters with Higher-order Frequency Dependencies."

J. Wu, J. Casebeer N. J. Bryan, P. Smaragdis,
IEEE Workshop on Acoustic Signal Enhancement (IWAENC), September, 2022.
(arXiv, code, demo)
Don't Separate, Learn to Remix: End-to-End Neural Remixing with Joint Optimization.

"Don't Separate, Learn to Remix: End-to-End Neural Remixing with Joint Optimization."

H. Yang, S. Firodiya N. J. Bryan, M. Kim,
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.
(arXiv, paper code)
Emotion Embedding Spaces for Matching Music to Stories.

"Emotion Embedding Spaces for Matching Music to Stories."

M. Won, J. Salamon N. J. Bryan, G. J. Mysore, X. Serra
International Society for Music Information Retrieval Conference (ISMIR), 2021.
(code, paper)
ISMIR Best Student Paper Award Winner
Deep Embeddings and Section Fusion Improve Music Segmentation.

"Deep Embeddings and Section Fusion Improve Music Segmentation."

J. Salamon O. Nieto, N. J. Bryan,
International Society for Music Information Retrieval Conference (ISMIR), 2021.
(code, paper)
Metric Learning vs Classification for Disentangled Music Representation Learning.

"Metric Learning vs Classification for Disentangled Music Representation Learning."

J. Lee, N. J. Bryan, J. Salamon, Z. Jin J. Nam
International Society for Music Information Retrieval (ISMIR), 2020.
(paper | arXiv | web)

"Impulse Response Data Augmentation and Deep Neural Networks For Blind Room Acoustic Parameter Estimation."

N. J. Bryan
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.
(paper | ieee link | talk)

"Interactive Sound Source Separation."

N. J. Bryan.
Stanford University, Stanford, CA, USA. March, 2014.
(PhD Thesis)

* ISSE: An Interactive Source Separation Editor (talk 1) (talk 2)
* Software (link)
* C++ code (link)
* Matlab code (link)
* Demos (link)
* SiSEC results (link)
* Publications (link)
AES Graduate Student Design Gold Award
Source Separation of Polyphonic Music With Interactive User-Feedback on a Piano Roll Display.

"Source Separation of Polyphonic Music With Interactive User-Feedback on a Piano Roll Display."

N. J. Bryan, G. J. Mysore, G. Wang
International Society for Music Information Retrieval Conference (ISMIR), 2013.
(web | paper)
An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation.

"An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation."

N. J. Bryan, G. J. Mysore
International Conference on Machine Learning (ICML), 2013.
(web | paper | sisec | Adobe MAX | poster | slides)
Interactive Refinement of Supervised and Semi-Supervised Sound Source Separation Estimates.

"Interactive Refinement of Supervised and Semi-Supervised Sound Source Separation Estimates."

N. J. Bryan, G. J. Mysore
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013.
(web | pre-print | poster)
Interactive User-Feedback for Sound Source Separation.

"Interactive User-Feedback for Sound Source Separation."

N. J. Bryan, G. J. Mysore
International Conf. on Intelligent User-Interfaces, Workshop on Interative Machine Learning, 2013.
(web | abstract)
Musical Influence Network Analysis and Rank of Sampled-Based Music.

"Musical Influence Network Analysis and Rank of Sampled-Based Music."

N. J. Bryan, G. Wang
International Society for Music Information Retrieval Conference (ISMIR), 2011.
(paper | whosampled | slides)
Two Turntables and a Mobile Phone.

"Two Turntables and a Mobile Phone."

N. J. Bryan, G. Wang
International Conference on New Interfaces for Musical Expression (NIME), 2011.
(paper | slides | web)
Instinct-Based Mating in Genetic Algorithms Applied to the Tuning of 1-NN Classifiers.

"Instinct-Based Mating in Genetic Algorithms Applied to the Tuning of 1-NN Classifiers."

T. Quirino, M. Kubat, N. J. Bryan
IEEE Transactions on Knowledge and Data Engineering (TKDE), December, 2010.
(paper)
Methods For Extending Room Impulse Responses Beyond Their Noise Floor.

"Methods For Extending Room Impulse Responses Beyond Their Noise Floor."

N. J. Bryan, J. S. Abel
Audio Engineering Society Convention (AES), 2010.
(paper | slides | web)
Impulse Response Measurements in the Presence of Clock Drift.

"Impulse Response Measurements in the Presence of Clock Drift."

N. J. Bryan, M. A. Kolar, J. S. Abel
Audio Engineering Society Convention (AES), 2010.
(paper | slides | web)
Approximating Measured Reverberation Using A Hybrid Fixed/Switched Convolution Structure.

"Approximating Measured Reverberation Using A Hybrid Fixed/Switched Convolution Structure."

K. Lee, N. J. Bryan, J. S. Abel
International Conference on Digital Audio Effects (DAFX), 2010.
(paper | web)