Juhan Nam, "My Journey Toward Musically Intelligent Machines"

Abstract
Creating intelligent machines that can listen to, play, and even making music has been a longstanding human ambition. Recent advancements in AI, especially through deep learning, have brought us closer to realizing this vision. In this talk, I will share my personal journey in developing musically intelligent machines, beginning with my PhD research on music representation learning during the early days of deep learning, and continuing with my collaborative work with students over the past decade at KAIST. Key topics will include bridging music audio with language, human-AI music ensemble performances, and neural audio processing.


Bio
Juhan Nam (PhD, CCRMA, Stanford University, 2013) is an Associate Professor at the Graduate School of Culture Technology at the Korea Advanced Institute of Science and Technology (KAIST), South Korea. Since joining KAIST in 2014, he has directed the Music and Audio Computing Lab, leading pioneering research in music information retrieval and audio signal processing. Prior to KAIST, Dr. Nam served as a Staff Research Engineer at Qualcomm (2012–2014) and as a Software/DSP Engineer at Young Chang (Kurzweil), a prominent electronic musical instrument manufacturer (2001–2006). Actively involved in the International Society for Music Information Retrieval (ISMIR), he will serve as General Chair of the ISMIR 2025 conference in Daejeon, Korea. He also contributes to the IEEE Audio and Acoustic Signal Processing Technical Committee. For more information on his work, please visit the lab website (https://mac.kaist.ac.kr/).


Zoom
https://stanford.zoom.us/j/7733389381?pwd=Z2xkVUEvNTA3dTRSclBHUlNRZGFZdz09
Meeting ID: 773 338 9381
Passcode: 601462