His research is focused on using machine learning and deep learning techniques for music and art. He recently spent a year and a half as a visiting scientist at Google Brain (California) on the Magenta team, where he worked on generative systems such as PerformanceRNN. Together with his brother Dani, he co-created “Radical Cycle”, a duo instrumental CD combining classical art songs with improvisation. He has performed as soloist with orchestras both as a classical soloist and as an improviser. Sageev studied piano performance with music teachers from Dalhousie, Juilliard, and UBC. He completed his undergraduate degree in Mathematics (Dalhousie), and MSc and PhD degrees in Computer Science (University of Toronto) working with Geoffrey Hinton.