Artificial Intelligence for Music

Javier Nistal Hurle

Javier Nistal Hurle is an Associate Researcher with the Music Team at Sony Computer Science Laboratories in Paris. He studied Telecommunications Engineering at Universidad Politecnica de Madrid and received a Master's in Sound and Music Computing from Universitat Pompeu Fabra. He completed his doctoral studies at Telecom Paris in a collaborative effort with Sony CSL, where he researched Generative Adversarial Networks for musical audio synthesis. In the music tech industry, Javier has worked on diverse projects involving machine learning (ML) and music, including recommendation systems, instrument recognition, and automatic mixing. He contributed to the development of the Midas Heritage D, the first ML-driven audio mixing console, and created DrumGAN, the first ML-powered sound synthesizer to hit the market. Javier's current research interest lies at the intersection of music production and deep learning. He is dedicated to devising generative models for music co-creation, aiming to enhance artistic creativity and enable musicians to explore new realms of musical expression.

Zhiyao Duan

Zhiyao Duan is an associate professor in Electrical and Computer Engineering, Computer Science, and Data Science at the University of Rochester. He is also a co-founder of Violy, a company aiming to improve music education through AI. His research interest is in computer audition and its connections with computer vision, natural language processing, and augmented and virtual reality. He received a best paper award at the Sound and Music Computing (SMC) Conference in 2017, a best paper nomination at the International Society for Music Information Retrieval (ISMIR) Conference in 2017, and a CAREER award from the National Science Foundation (NSF). His work has been funded by NSF, National Institute of Health, National Institute of Justice, New York State Center of Excellence in Data Science, and University of Rochester internal awards on AR/VR, health analytics, and data science. 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 Transactions of the International Society for Music Information Retrieval. He is the President of ISMIR.

Fatemeh Jamshidi

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, as well as augmented and mixed reality. She has published in prestigious venues, including ACM SIGCSE, ISMIR, IEEE, and HCII. Fatemeh earned her Ph.D. in Computer Science and Software Engineering and a master's in Music Education from Auburn University in 2024 and 2023, respectively. During her Ph.D., she founded the Computing + Music programs, which have engaged hundreds of participants from underrepresented groups since 2018. From 2020 to 2023, she also served as the Director of the Persian Music Ensemble at Auburn University. Her long-term goal is to establish a music technology center that fosters undergraduate and graduate research in areas such as music therapy, music generation, game music, and mixed reality in music.

Gus Xia

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. Some 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.

Emmanouil Benetos

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 member of the Centre for Digital Music and 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.

Website: https://www.eecs.qmul.ac.uk/~emmanouilb/

Yung-Hsiang Lu

Professor of 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. Yung-Hsiang has published papers on computer vision and machine learning in venues such as AI Magazine, Nature Machine Learning, and Computer. He is one of the editors of the book "Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence" (ISBN 9780367744700, 2022 by Chapman & Hall).

Kristen Yeon-Ji Yun

Clinical Associate Professor of 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. She is the Principal Investigator of the research project "Artificial Intelligence Technology for Future Music Performers" (US National Science Foundation, IIS 2326198). Kristen is an active soloist, chamber musician, musical scholar, and clinician. She has toured many countries, including Malaysia, Thailand, Germany, Mexico, Japan, China, Hong Kong, Spain, France, Italy, Taiwan, and South Korea, giving a series of successful concerts and master classes.

George K. Thiruvathukal

Professor and Chairperson of 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. His research interests include high-performance computing and distributed systems, programming languages, software engineering, machine learning, digital humanities, and arts (primarily music). George has published multiple books, including "Software Engineering for Science" (ISBN 9780367574277, 2016 Chapman and Hall & CRC), "Web Programming: Techniques for Integrating Python, Linux, Apache, and MySQL" (ISBN 9780130410658, 2001 Prentice Hall), and "High-Performance Java Platform Computing: Multithreaded and Networked Programming" (ISBN 9780130161642, 2000 Prentice Hall).

Charalampos Saitis

Lecturer in Digital Music Processing

Dr. Saitis is an assistant professor in digital music processing at Queen Mary University of London where he leads the Communication Acoustics Lab (COMMA) at the Centre for Digital Music (C4DM) and is a co-investigator in the UKRI CDT in AI and Music based (2019-2028). Experienced leader in the intersecting fields of cognitive science, music informatics and generative AI with applications in sonic creativity, recommender systems and well-being.

Hao-Wen (Herman) Dong

Hao-Wen (Herman) Dong is an Assistant Professor in the Performing Arts Technology Department at the University of Michigan. Herman's research aims to empower music and audio creation with machine learning. His long-term goal is to lower the barrier of entry for music composition and democratize audio content creation. He is broadly interested in music generation, audio synthesis, multimodal machine learning, and music information retrieval. Herman received his PhD degree in Computer Science from the University of California San Diego, where he worked with Julian McAuley and Taylor Berg-Kirkpatrick. His research has been recognized by the UCSD CSE Doctoral Award for Excellence in Research, KAUST Rising Stars in AI, UChicago and UCSD Rising Stars in Data Science, ICASSP Rising Stars in Signal Processing, and UCSD GPSA Interdisciplinary Research Award.

Mei-Ling Shyu

Professor Science and Engineering

Dr. Shyu is a professor of Electrical and Computer Engineering, at the University of Missouri-Kansas City. Prior to UMKC, she was the Associate Chair and Professor at the Department of Electrical and Computer Engineering at the University of Miami. She received her PhD degree from the School of Electrical and Computer Engineering and three Master's degrees in Computer Science, Electrical Engineering, and Restaurant, Hotel, Institutional, and Tourism Management, all from Purdue University. Her research interests include data science, AI, machine learning, data mining, big data analytics, multimedia information systems, and semantic-based information management/fusion/retrieval.

Wen-Huang Cheng

Distinguished Chair Professor Department of Computer Science and Information Engineering

Dr. Cheng is a professor of Computer Science and Information Engineering at National Taiwan University. He is the founding director of the Artificial Intelligence and Multimedia (AIMM) Research Group. Before joining National Taiwan University, he was a Distinguished Professor at the Institute of Electronics, National Yang Ming Chiao Tung University, and led the Multimedia Computing Research Group at the Research Center for Information Technology Innovation at Academia Sinica. He is a fellow of the IEEE and Asia-Pacific Artificial Intelligence Association.