Song Hui received her Ph.D. in music technology from McGill University in 2013 with a focus on timbre perception with Dr. Stephen McAdams. She spent the subsequent three years at the Ohio State University as a postdoctoral fellow in music cognition with Dr. David Huron. For the next two years, Song Hui held a visiting professor position in the Electrical, Computer, and Telecomm department at Rochester Institute of Technology teaching computational problem solving and acoustics, as well as carrying out spatial audio research. She then worked as a research associate in the School of Speech, Language, and Hearing Sciences at the University of Colorado at Boulder, embarking on research in age-related hearing problems and hearing aids, before joining the Audio Engineering Technology faculty at Belmont in 2019. Her expertise is highly technical and includes five years of software development in Information Technology as well as three degrees in engineering -- an Engineer’s degree in Electrical Engineering from Stanford University, a Master’s degree in Electrical Engineering from the University of Washington, and a Bachelor’s degree in Computer Engineering from Chonbuk National University in Korea. Song Hui studied fortepiano with Dr. George Barth and harpsichord with Ms. Elaine Thornburgh at Stanford. She continued her study on the fortepiano and clavichord with Dr. Tom Beghin and the organ with Ms. Margaret de Castro at McGill. Song Hui’s research interests include auditory and music perception, more specifically in timbre and attention. Song Hui is currently an assistant professor at Belmont University in Nashville, TN. Prior to this position, she was a postdoctoral fellow in music cognition at the Ohio State University, working with Dr. David Huron. She finished her Ph.D. in 2013 in music technology with Dr. Stephen McAdams. Her dissertation topic was timbre salience, which is the attention-capturing quality of timbre that she proposed. Song Hui's research interests include music perception and cognition, auditory attention and auditory scene analysis.