Ajay's work revolves around one question: "How do you make a robotic instrument improvise with a human?" Using the rules set forth by Indian classical as well as other Asian musical traditions, Ajay has been driven to build new interfaces for musical expression through extending the classical and folk Asian musical forms, with added microchips and embedded sensor systems, while designing custom robotic musical instruments. He leads a team of artists and engineers exploring the intersection of music, composition, storytelling, science and technology in the KarmetiK Machine Orchestra. In this talk, Ajay will also discuss the educational pathway setup at California Institute of the Arts that helps foster the modern artist equipped with knowledge in technology, algorithms, and aesthetics. Ajay points to the future and talks about how Artificial Intelligence, Machine Learning and Deep Learning are being used to solve problems for music, performance and education.
Ajay Kapur is currently the Associate Dean for Research and Development in Digital Arts at the California Institute of the Arts, as well as the Director of Music Technology. He also runs a PhD Research Group in Wellington New Zealand called Sonic Engineering Lab for Creative Technology. He received an Interdisciplinary Ph.D. in 2007 from University of Victoria combining computer science, electrical engineering, mechanical engineering, music and psychology with a focus on intelligent music systems and media technology. Ajay graduated with a Bachelor of Science in Engineering and Computer Science from Princeton University in 2002. Kapur has published over 150 technical papers and presented lectures across the world on music technology, human computer interface for artists, robotics for making sound, machine learning, and building modern digital orchestras. His first book "Digitizing North Indian Music", discusses how sensors, machine learning and robotics are used to extend and preserve traditional techniques of Indian Classical music. His latest book "Introduction to Programming for Musicians and Digital Artists" is a textbook for artists to learn computer science.