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

Teaching
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 Lecture
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
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

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