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
Awards
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