As both a computer scientist and a musician, she is interested in creating and studying new technologies for music composition and performance. Much of her current work focuses on applications of machine learning to music: for example, how can machine learning algorithms help people to create new digital musical instruments by supporting rapid prototyping and a more embodied approach to design? How can these algorithms support composers in creating real-time, interactive performances in which computers listen to or observe human performers, then respond in musically appropriate ways? She is interested both in how techniques from computer science can support new forms of music-making, and in how applications in music and other creative domains demand new computational techniques and bring new perspectives to how technology might be used and by whom.