Dr Louis McCallum

Staff details

Position Associate Lecturer / Post Doctoral Researcher

Department Computing

Email l.mccallum (@gold.ac.uk)

Twitter @louismccallum

With a background in music and robotics, Louis has been at Goldsmiths since 2017, researching interactive machine learning with motion sensors, as well as AI for musicians. Since 2019 he has been teaching both undergraduate and Master's courses in machine learning for creative practice. Louis performs using machine learning systems, and also builds AI software for other artists, most recently Actress's Young Paint project.

Qualifications

PhD, Media & Arts Technology, Queen Mary, University of London. Friend Me Your Ears: A Musical Approach to Human-Robot Relationships
BSc Music Informatics, University of Sussex

Research Interests

Music and AI
Social and musical robotics

Publications

Conference or Workshop Item

McCallum, Louis and Yee-King, Matthew. 2020. 'Network Bending Neural Vocoders'. In: 4th Workshop on Machine Learning for Creativity and Design at NeurIPS 2020, Vancouver, Canada.. Vancouver, Canada 2020.

Vigliensoni, Gabriel; McCallum, Louis and Fiebrink, Rebecca. 2020. 'Creating Latent Spaces for Modern Music Genre Rhythms Using Minimal Training Data'. In: International Conference on Computational Creativity (ICCC). Coimbra, Portugal 7 – 11 September 2020.

Yee-King, Matthew; McCallum, Louis; Llano, Maria Teresa; Ruzicka, Vit; d'Inverno, Mark and Grierson, Mick. 2020. 'Examining Student Coding Behaviours in Creative Computing Lessons using Abstract Syntax Trees and Vocabulary Analysis'. In: 2020 ACM Conference on Innovation and Technology in Computer Science Education. Trondheim, Norway.

Grierson, Mick; Yee-King, Matthew; McCallum, Louis; Kiefer, Chris and Zbyszynski, Michael. 2019. 'Contemporary Machine Learning for Audio and Music Generation on the Web: Current Challenges and Potential Solutions'. In: ICMC/NYCEMF 2019. New York, United States 16-23 June 2019.

McCallum, Louis and Fiebrink, Rebecca. 2019. 'Supporting Feature Engineering in End-User Machine Learning'. In: CHI 2019 Workshop on Emerging Perspectives in Human-Centered Machine Learning. Glasgow, United Kingdom 4 May 2019.