Joseph Meyer

Joseph Meyer is an Associate Lecturer and PhD student at the University of the Arts London's Creative Computing Institute. His academic journey includes a Bachelor of Arts in Computer Science from Reed College (2015-2019) followed by industry experience as a Data Scientist and Software Engineer at AppLovin in Palo Alto.

His research interests focus on the intersection of machine learning and creative expression, specifically: New Interfaces for Musical Expression; Human-Computer Interaction; Interactive Machine Learning; Neural Audio Synthesis; and Computer Vision. Meyer's work bridges technical machine learning approaches with artistic applications, particularly in audio and poetry generation.

Meyer's recent publication 'Interactive Movement-to-Audio with Pre-Trained Neural Networks' (ACM Creativity and Cognition 2025) demonstrates his focus on using neural networks to transform human movement into audio outputs. His GitHub repositories reveal additional projects in transformer-based poetry generation, sound synthesis, and reinforcement learning applications.

As an Associate Lecturer at the Creative Computing Institute since April 2025, Meyer contributes to teaching while pursuing his PhD research. His industry background at AppLovin provides practical context for his academic work, particularly in how machine learning systems can be designed for both technical effectiveness and creative potential. His dual role as both student and lecturer offers a unique perspective on the integration of machine learning techniques within creative computing disciplines.