Nick (Nicholas) J. Bryan









Note: I currently work in industry and no longer update this webpage (thesis defense was on 11/22/13).

Previously, I was a PhD candidate at the Center for Computer Research in Music and Acoustics (CCRMA), Stanford University, advised by Prof. Ge Wang with additional work with Prof. Julius O. Smith III and Jonathan S. Abel at CCRMA and Gautham J. Mysore and Paris Smaragdis at Adobe Research. My research interests are at the intersection of signal processing, machine learning, and human-computer interaction.

I received a M.S. in Electrical Engineering in 2011, an M.A. in Music, Science, and Technology in 2008, both from Stanford University. In 2007, I received a B.S. in Electrical Engineering and B.M. in Music Engineering (summa cum laude, departmental honors in EE, general honors) from the University of Miami-FL.

Thesis: For my dissertation, I worked on the problem of taking a single audio recording (e.g. a pop song) and separating it into its respective sound sources (e.g. drums, bass, vocals, etc.). In particular, I was interested in incorporating interactive user-feedback into the separation process to iteratively improve separation quality. For more information, please see the demo video below, my thesis, and/or for free, open-source, cross-platform source separation software.

Interactive Sound Source Separation Demonstration