My research interests lie in the field of music informatics, an interdisciplinary area that uses and develops new computational methods and models for processing and producing music and musical information. Specifically, I am interested in advancing the state of research in artificial intelligence, machine learning, and probabilistic modeling by using music-related problems as motivators. I am intrigued by this field precisely because it combines computational study with an art form that requires a great deal of contextual knowledge.
Some Interesting Problems
- Computational studies of hierarchical music analysis: I'm analyzing Schenkerian analysis using probabilistic models to uncover the statistical regularities in the way people analyze music. Check out my dissertation for the most recent findings.
- Harmonic and melodic analysis: I'm interested in going beyond chord labeling. Can we get a complete functional harmonic analysis with Roman numerals, figured bass, and identification of all non-harmonic tones with their functions? What about analyzing the voice-leading of a piece; can we identify the melodic connections between notes at multiple structural levels?
- Finding a grammar of music: Does it exist? Is it possible to algorithmicize Lerdahl and Jackendoff's A Generative Theory of Tonal Music?
- Algorithmic composition and machine creativity