Artificial Intelligence for Music

Geoffroy Peeters

Télécom Paris · S2A team

Self-Supervised Learning for Invariant and Equivariant representations

Geoffroy Peeters is full-professor in the (Laboratoire Traitement et Communication de l'Information) S2A team at Télécom Paris. He received his PhD in 2001 and Habilitation in 2013 from University Paris-VI on audio signal processing, data analysis and machine learning. Before joining Télécom Paris, he led research related to Music Information Retrieval at IRCAM (Institut de recherche et coordination acoustique/musique). His current research is on signal processing, machine learning, and deep learning applied to audio and music data analysis.

• Homepage ↗

Zhiyao Duan

University of Rochester · ECE / CS / Data Science

Zhiyao Duan is an associate professor in Electrical and Computer Engineering, Computer Science, and Data Science at the University of Rochester, and co-founder of Violy, a company aiming to improve music education through AI. His research is in computer audition and its connections with computer vision, NLP, and AR/VR. He received best paper recognition at SMC 2017 and ISMIR 2017, and a CAREER award from NSF. He is a senior area editor of IEEE Signal Processing Letters, an associate editor for IEEE Open Journal of Signal Processing, and a guest editor for TISMIR. He is the President of ISMIR.

• Homepage ↗

Fatemeh Jamshidi

Cal Poly Pomona · Computer Science

Fatemeh Jamshidi is an Assistant Professor in the Department of Computer Science at Cal Poly Pomona. Her research spans artificial intelligence, computer science education, computer music, machine learning and deep learning in music, game AI, human–AI collaboration, and augmented and mixed reality. She has published in ACM SIGCSE, ISMIR, IEEE, and HCII. Fatemeh earned her PhD in Computer Science and Software Engineering and a master's in Music Education from Auburn University in 2024 and 2023, respectively. During her PhD she founded the Computing + Music programs, which have engaged hundreds of participants from underrepresented groups since 2018. From 2020 to 2023, she served as the Director of the Persian Music Ensemble at Auburn.

• Homepage ↗

Gus Xia

MBZUAI · Machine Learning

Gus Xia is an assistant professor of Machine Learning at the Mohamed bin Zayed University of Artificial Intelligence in Masdar City, Abu Dhabi. His research includes the design of interactive intelligent systems to extend human musical creation and expression. This research lies at the intersection of machine learning, human–computer interaction, robotics, and computer music. Representative works include interactive composition via style transfer, human–computer interactive performances, autonomous dancing robots, large-scale content-based music retrieval, haptic guidance for flute tutoring, and bio-music computing using slime mold.

• Homepage ↗

Emmanouil Benetos

Queen Mary University of London / Alan Turing Institute

Machine learning paradigms for music and audio understanding

Emmanouil Benetos is Reader in Machine Listening and Director of Research at the School of Electronic Engineering and Computer Science of Queen Mary University of London. Within Queen Mary, he is a member of the Centre for Digital Music and the Centre for Multimodal AI, is Deputy Director at the UKRI Centre for Doctoral Training in AI and Music (AIM), and co-leads the School's Machine Listening Lab. His main area of research is computational audio analysis — also referred to as machine listening or computer audition — with applications to music, urban, everyday, and nature sounds.

• Homepage ↗

Yung-Hsiang Lu

Purdue University · Electrical and Computer Engineering

Yung-Hsiang Lu is a professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He is a fellow of the IEEE and a distinguished scientist of the ACM.

• Homepage ↗

Kristen Yeon-Ji Yun

Purdue University · Music

Kristen Yeon-Ji Yun is a clinical associate professor in the Department of Music at the Patti and Rusty Rueff School of Design, Art, and Performance at Purdue University, and Principal Investigator of "Artificial Intelligence Technology for Future Music Performers" (NSF IIS 2326198).

• Homepage ↗

George K. Thiruvathukal

Loyola University Chicago · Computer Science

George K. Thiruvathukal is a professor and chairperson of Computer Science at Loyola University Chicago and a visiting computer scientist at Argonne National Laboratory.

• Homepage ↗