Mr Mark J Whitlam

My PhD reserach focuses on the role of autonomous and semi-autonomous intelligent softwares in mediating indeterminacy in composition and the performance of music.  I am interested in exploring the opportnuities and limitations afforded by current machine learning (artificial intelligence) models on the creation of music and co-improvisation in human-machine networks in an aim to reveal surprising and rewarding ways of creating new musical gestures. This reserach project has evolved from two decades of professional experience as an improvising performer with various leading artists in the UK jazz scene.  

Beyond investigating my inidividual excperience as a composer/performer interacting with computer agents, I am keen to explore how this experience elicits reactions in other performers/improvisors when working collectively. As such, some of my research engages with behavioural frameworks, including Actor-Network Theory (ANT), 4E cognition and swarm intelligence.  

My research output is a growing portfolio of composed material for live performance utilising motion/gesture capture methods, generative AI tools and spatialised sound reproduction, in part, developing compositional techniques by Claude Vivier, using ring modulation concepts as an approach to generating 'timbral harmony'.