I am a second-year undergraduate student at McGill University with a major in Neuroscience and a minor in Computer Science. Given my background as a pianist and my longstanding interests in music and the human brain, I am passionate about exploring the role of machine learning in music therapy. There are many ideas that I hope to explore at BLUE; for instance, given people's unique musical preferences and neurological makeup, can we "prescribe" music that is unique to the patient to help the patient achieve a particular outcome? Specifically, I am drawn to the following questions:

• "How do we break down music into individual elements (rhythm, pitch, etc.) and determine the specific elements that are responsible for someone's affective response to a composition?"

• Can we incorporate machine learning-generated compositions to the typical repertoire of music presented to patients in music therapy and achieve a better outcome?