Robert DiFazio is Head of R&D at Song Sleuth, where he oversees the development of novel analytic tools for the automatic recognition of online user-generated music content. His work revolves around the use of cutting-edge audio processing technology, data mining and machine-learning techniques to identify unlicensed uses of copyright protected works on platforms such as YouTube and TikTok.
While earning a Bachelor of Science in Sound Recording Technology at DePaul University in the early 2000’s, Robert began a career as a music engineer and studio manager at numerous recording facilities in the Chicago area, working with acts such as Snoop Dog, Machine Gun Kelly, and many others. In 2005, Robert became a member of the music business faculty at Columbia College Chicago, where he instructed courses in music production and business for thirteen years and was awarded the Provost’s Excellence in Teaching Award in 2016.
Robert’s life-long passion for music and technology subsequently drew him into the budding discipline of Music Information Retrieval, a field of scientific inquiry that combines the study of audio, music and computational intelligence, prompting him to continue his education at the University of Illinois at Chicago where he earned a Master of Science in Management Information Systems. Robert currently serves as a Clinical Assistant Professor and Coordinator of Music Business at The University of Illinois at Chicago where he oversees the Bachelor of Arts in Music Business program.