Data Journeys

Dr. Brian McFee develops machine learning tools to analyze multimedia data. This includes recommender systems, image and audio analysis, similarity learning, cross-modal feature integration, and automatic annotation. As of Fall, 2014, he is a data science fellow at the Center for Data Science at New York University. Previously, he was a postdoctoral research scholar in the Center for Jazz Studies and LabROSA at Columbia University.   My conversation with Brian today was focused on discussing his research in music informatics and its many facets and applications. He tells about some of the methods he used during his dissertation, and I ask him for insight on how to get a recommender system to recommend stuff that you actually like.   Here are some of the highlights of the show:   [3:17] What came first for Brian, the data science or the music? [5:19] Of all the things he could have chose to study, why did Brian choose music? [7:35] What is it like to be in a branch of data science that has become so closely