Louis Discusses Early Robotics Work
Yee-King, Matthew and McCallum, Louis. 2021. Studio report: sound synthesis with DDSP and network bending techniques. In: 2nd Conference on AI Music Creativity (MuMe + CSMC). Graz,Austria 18 – 22 July 2021
McCallum, L and Yee-King, M; Network Bending Neural Vocoders in Machine Learning for Creativity and Design Workshop, NeurIPS 2020
Louis McCallum, Rebecca Fiebrink, The challenge of feature engineering in programming for moving bodies, In: NordiCHI ’20 Workshop on Programming for Moving Bodies, 26 October 2020, Online.
Gabriel Vigliensoni, Louis McCallum, Esteban Maestre, Rebecca Fiebrink, Generation and visualization of rhythmic latent spaces, AI Music 2020
Vigliensoni, Gabriel, Louis McCallum, and Rebecca Fiebrink. “Creating Latent Spaces for Modern Music Genre Rhythms Using Minimal Training Data“, ICCC 2020
Yee-King, M; McCallum, L; Llano , M.T; Ruzicka, V; d’Inverno, M; Grierson, M.; Examining Student Coding Behaviours in Creative Computing Lessons using Abstract Syntax Trees and Vocabulary Analysis In ITiCSE ’20: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, June 2020, Pages 273–27
Grierson, M; Yee-King, M; McCallum, L; Kiefer, C and Zbyszynski, M. 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, L. and R. Fiebrink.. Supporting Feature Engineering in End-User Machine Learning. Emerging Perspectives in Machine Learning Workshop, held at CHI 2019, 4 May 2019. (workshop paper)
McCallum, L. and McOwan, P.W., Extending Human-Robot Relationships Based in Music with Virtual Presence
IEEE Transactions on Cognitive and Developmental Systems, Journal Paper, 2017
McCallum, L., Friend Me Your Ears: A Musical Approach to Human-Robot Relationships, PhD Thesis, QMUL, 2016
McCallum, L. and McOwan, P.W., Face the Music and Glance: How Nonverbal Behaviour Improves Human-Robot Relationships Based in Music, March 2015 ACM Human Robot Interaction Conference, Portland, OR, Presented Paper
McCallum, L. and McOwan, P.W., Shut up and Play: A Musical Approach to Engagement and Social Presence in Human Robot Relationships IEEE International Symposium on Robot and Human Interactive Communication, Presented Paper, shortlisted for Best Paper Award
Show Us Your Screens, Computer Music Journal, MIT Press, Winter 2011, DVD supplement, Documentary into Live Coding Practise
Grants
$20,000 Google AMI Research Award 2021 Network Bending Differentiable Digital Signal Processing (DDSP) w/ Matthew Yee-King
£25,000 Alan Turing Institute Network Grant, Open Source AI Tools for Music and Art
Teaching
Course Leader MSc Data Science and AI for the Creative Industries,
2020 – present, Creative Computing Institute, UAL
Developing and Delivering 6 units:
Course Leader MRes Creative Computing,
Creative Computing Institute, UAL,2020 – 2021,
Subject Matter Expert,
Apply Creative Machine Learning, FutureLearn Course 2020
Lead Instructor and Module Convenor
Data and Machine Learning for Creative Practice, 3rd Year Undergraduate Module, Goldsmiths, University of London, 2019-20
Lead Instructor and Module Convenor
Data and Machine Learning for Artistic Practice, Masters Module, Goldsmiths, University of London, 2019-20
Invited Lecturer
Perceptual and Multimedia Computing, 2nd Year Undergraduate Module, Goldsmiths, University of London, 2019-20
Group Supervisor
Software Projects, 2nd Year 2 term Undergraduate Module, Goldsmiths, University of London, 2018-19
Workshops and Talks
Empowering Musicians and Artists using Machine Learning to Build Their Own Tools in the Browser, W3C Workshop on Web and Machine Learning, 2020
Using Machine Learning to Build Musical Instruments in the Browser with MIMIC, at NIME2020, July 2020
Using Machine Learning to Build Musical Instruments in the Browser with MIMIC, at Network Music Festival 2020, July 2020
Using Machine Learning to Build Musical Instruments in the Browser with MIMIC, at ICCC2021, Sept 2021
AI Artathon 2.0 – Building Interactive Controllers with Machine Learning, October 2021
Machine Learning for Mapping – Intermedia Mapping and Scripting Workshop, CIRMNT 2019
Awards
Karajan Institute Sennheiser AI Prize, 2019
GRAGGGGGG:Generative Remix App Generator, Music Hackday, London, Winner of EMI Sandbox API Prize
IWARP: Interactions with a Robotic Percussionist, Undergraduate Thesis, Winner of Best Artificial Intelligence Project, 2010