Matt McVicar is a Machine Learning Engineer at Apple in London, England. Previously, he worked at Jukedeck, a music AI startup, as a machine learning researcher and head of research. He has also worked as a postdoctoral research assistant at the National Institute for Advanced Industrial Science and Technology in Tsukuba, Japan, a visiting postgraduate researcher at Columbia University in the city of New York, and a data scientist at the University of Bristol in Bristol, England. At the University of Bristol, he is a co-principal investigator (along with Tijl De Bie) on the 2-year EPSRC-funded project: "Data Science for the Detection of Emerging Music Styles."

Matt is highly educated, having completed an undergraduate master's degree in Pure and Applied Mathematics, a master's degree in Complexity Sciences, and a Ph.D. in Engineering Mathematics, all at the University of Bristol. His thesis title was "A Machine Learning Approach to Automatic Chord Estimation," supervised by Tijl De Bie.

As a Machine Learning Engineer, Matt's primary expertise is developing and implementing machine learning algorithms. He has applied these skills in the music industry, as well as in academic research conducted at the University of Bristol and AIST. Matt's research interests include data science, music informatics, and machine learning.