AI (Artificial Intelligence) for Musicians

This is a Research Team Studying How Musicians can Benefit from AI (Artificial Intelligence)

This project is supported by the National Science Foundation Artificial Intelligence Technology for Future Music Performers.

Research Team


Create AI-based software for musicians. Evaluate whether the software actually helps musicians. Educate students for AI, software, and music performance.

Vertically Integrated Project

Artificial Intelligence in Music is an undergraduate course. Meeting time in Spring 2024: Varies by project; email below

Multidisciplinary Research

This project includes students and professors from Music, Engineering, Technology, Art, and Management.

User Studies

Evaluate how musicians use AI-based tools and how these tools can be improved.


Gives speeches and concerts about AI and music.


Demonstrate the technology.

Cello Lessons

Learn how to play cello, from beginners to stage performers.

Project Director:

Kristen Yeon-Ji Yun is a clinical associate professor of Music.

Josh Kamphuis is a leader of the Evaluator undergraduate research team.

Tim Nadolsky is the leader of the Companion undergraduate research team.

Haichang Li is the leader of the Mus2Vid undergraduate research team.

Brian Ng is an undergraduate student.

Victor Yingjie Chen is a professor of Computer Graphics Technology.

Yung-Hsiang Lu is a professor of Electrical and Computer Engineering.

Cheryl Zhenyu Qian is a professor of Interaction Design in Industrial Design.

Mohammad Saifur Rahman is the inaugural Daniels School Chair in Management and a Professor of Management at the Mitchell E. Daniels, Jr. School of Business.


The Evaluator aims to improve individual practice and performance. It analyzes a musician’s sound and compares it to digitized music scores to detect deviations in intonation, rhythm, and dynamics and suggest better posture based on sample performers’ recording with correct posture.

Drawing by Cecilia Ines Sanchez.


The Companion plays the part of one or several instruments to replace absent musicians with matching tempo, and style of the human musicians through audio analysis of their performance while also responding in real-time to verbal instructions.

Drawing by Cecilia Ines Sanchez.

Visualize Music

This project analyzes music elements and transforms them into textual descriptions. These descriptions are converted into visual representations (images or videos). The visual depictions are dynamically adjusted to mirror the music.

Get in touch

We would love to hear from you.

  • Address

    Elliot 34, 712 3rd Street
    Purdue University, West Lafayette, IN 47907
  • Email
  • Phone

    (765) 494-0973
  • Social