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Brian McFee

Associate Professor of Music Technology and Data Science

Music and Performing Arts Professions

Brian McFee is Assistant Professor of Music Technology and Data Science at NYU Steinhardt and the NYU Center for Data Science. He holds a B.S. degree in Computer Science (2003) from the University of California at Santa Cruz, and M.S. (2008) and Ph.D. (2012) degrees in Computer Science and Engineering from the University of California at San Diego. 

His research lies at the intersection of machine learning, signal processing, and information retrieval, with the overarching goal of developing algorithms to expose latent structure in recorded audio. He is an active developer of open source scientific software, and is the primary maintainer of the librosa package for audio content analysis. 


Prior to joining the faculty at NYU, he was a Moore-Sloan Data Science Fellow at the Center for Data Science, and a Postdoctoral Scholar at Columbia University's Center for Jazz Studies. He is a recipient of the Qualcomm Innovation Fellowship.

Programs

Music Technology

Develop your expertise in an academic program that emphasizes creative experimentation and the integration of musical and technical skills.

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Courses

Fundamentals of Digital Signal Theory

Theoretical and practical foundations for digital signal processing. Topics covered include signal representation in time and frequency domains, Fourier transform, spectrum analysis, transfer functions, convolution, filter theory and implementation. Lectures are reinforced with a co-requisite weekly lab.
Course #
MPATE-GE 2599
Credits
3
Department
Music and Performing Arts Professions

Music Info Retrieval

Comprehensive overview of research in the multi-disciplinary field of Music Information Retrieval (MIR) which uses knowledge from diverse areas such as signal processing, machine learning and information and music theory. Exploration of how this knowledge can be used to develop novel methodologies for browsing and retrieval of large music collections. Emphasis would be given to audio signal processing techniques.
Course #
MPATE-GE 2623
Credits
3
Department
Music and Performing Arts Professions