Matthew Yee-King (DPhil, MSc, BSc) is an academic in the department of computing, Goldsmiths, University of London.
In 2013 he delivered the first English language MOOC on the coursera platform, attracting an enrolment of 97,000. As the project manager for the €3m PRAISE research project, he managed the development and trialling of innovative education technology, including media annotation systems.
He is the CTO of Museifi, a spin out company that is innovating PRAISE technology into the marketplace. He has also carried out research into audio analysis and creative applications of machine learning, including a series of commissioned musical AI systems that have performed alongside human musicians on BBC national radio and at venues such as the Wellcome Collection.
- BSc Zoology and Genetics, Leeds University, 1996
- MSc Evolutionary and Adaptive Systems, Sussex University, 2000
- DPhil Computer Science and Artificial Intelligence, Sussex University, 2010
Matthew is responsible for development of online course provision within the Computing department, having developed and delivered MOOCs that have been taken by hundreds of thousands of students. He has previously taught a range of courses including programming, audiovisual computing and web development.
Education technology, creative musical Ais, computer Music, automatic sound synthesizer programming, genetic algorithms, interactive music systems.
Automated sound synthesizer programming and interactive music systems.
McCormack, Jon; Hutchings, Patrick; Gifford, Toby; Yee-King, Matthew; Llano, Maria Teresa and d'Inverno, Mark. 2020. Design Considerations for Real-Time Collaboration with Creative Artificial Intelligence. Organised Sound, 25(1), pp. 41-52. ISSN 1355-7718
Yee-King, Matthew; Wilmering, Thomas; Llano, Maria Teresa; Krivenski, Maria and d'Inverno, Mark. 2019. Technology Enhanced Learning: The Role of Ontologies for Feedback in Music Performance. Frontiers in Digital Humanities, 5(29),
Yee-King, Matthew; Fedden, Leon and d'Inverno, Mark. 2018. Automatic Programming of VST Sound Synthesizers using Deep Networks and Other Techniques. IEEE Transactions on Emerging Topics in Computational Intelligence, 2(2), pp. 150-159. ISSN 2471-285X
Gifford, Toby; Knotts, Shelly; McCormack, Jon; Kalonaris, Stefano; Yee-King, Matthew and d'Inverno, Mark. 2018. Computational Systems for Music Improvisation. Digital Creativity, 29(1), pp. 19-36. ISSN 1462-6268
Yee-King, Matthew; Grierson, Mick and d'Inverno, Mark. 2017. Evidencing the value of inquiry based, constructionist learning for student coders. International Journal of Engineering Pedagogy, 7(3), pp. 109-129. ISSN 2192-4880
Yee-King, M J. 2016. The Use of Interactive Genetic Algorithms in Sound Design: A Comparison Study. Computers in Entertainmnent: Special Issue on Musical Metacreation,
Confalonieri, Roberto; Yee-King, Matthew; Hazelden, Katina; d'Inverno, Mark; De Jonge, Dave; Osman, Nardine; Sierra, Carles; Agmoud, Leila and Prade, Henri. 2015. Engineering multiuser museum interactives for shared cultural experiences. Engineering Applications of Artificial Intelligence, 46(Part A), pp. 180-195. ISSN 0952-1976
Yee-King, Matthew and d'Inverno, Mark. 2014. Pedagogical Agents for Social Music Learning in Crowd-Based Socio-Cognitive Systems. Crowd Intelligence: Foundations, Methods, and Practices (CEUR Workshop Proceedings), 1148, pp. 76-93. ISSN 1613-0073
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.
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.
McCormack, Jon; Gifford, Toby; Hutchings, Patrick; Llano, Maria Teresa; Yee-King, Matthew and d'Inverno, Mark. 2019. 'In a Silent Way: Communication between AI and improvising musicians beyond sound'. In: CHI 2019 Conference on Human Factors in Computing Systems. Glasgow, United Kingdom 4-9 May 2019.
Zbyszynski, Michael; Grierson, Mick; Yee-King, Matthew and Fedden, Leon. 2017. 'Write once run anywhere revisited: machine learning and audio tools in the browser with C++ and emscripten'. In: Web Audio Conference 2017. Centre for Digital Music, Queen Mary University of London, United Kingdom 21-23 August 2017.
Yee-King, Matthew; Grierson, Mick and d'Inverno, Mark. 2017. 'STEAM WORKS: Student coders experiment more and experimenters gain higher grades'. In: EDUCON2017: IEEE Global Engineering Education Conference. Athens, Greece April 26-28, 2017.
Zbyszynski, Michael; Grierson, Mick and Yee-King, Matthew. 2017. 'Rapid Prototyping of New Instruments with CodeCircle'. In: New Interfaces for Musical Expression. Copenhagen, Denmark 15-18 May 2017.
al-Rifaie, Mohammad Majid; Yee-King, Matthew and d'Inverno, Mark. 2016. 'Investigating Swarm Intelligence for Performance Prediction'. In: Proceedings of the 9th International Conference on Educational Data Mining. Raleigh, NC, United States 29 June - 2 July 2016.
Yee-King, Matthew and d'Inverno, Mark. 2016. 'Experience driven design of creative systems'. In: Proceedings of the Seventh International Conference on Computational Creativity. Paris, France 27 June - 1 July 2016.
Gillies, Marco; Brenton, Harry; Yee-King, Matthew; Grimalt-Reynes, Andreu and d'Inverno, Mark. 2015. 'Sketches vs Skeletons: Video Annotation Can Capture What Motion Capture Cannot'. In: Proceedings of the 2Nd International Workshop on Movement and Computing. Vancouver, Canada.
Brenton, Harry; Yee-King, Matthew; Grimalt-Reynes, Andreu; Gillies, Marco; Krivenski, Maria and D'Inverno, Mark. 2014. 'A Social Timeline for Exchanging Feedback about Musical Performances'. In: Proceedings of the 28th International BCS Human Computer Interaction. Southport, United Kingdom.
Yee-King, Matthew and d'Inverno, Mark. 2014. 'Pedagogical agents for social music learning in Crowd-based Socio-Cognitive Systems'. In: Crowd Intelligence: Foundations, Methods, and Practices (CEUR Workshop Proceedings). Barcelona, Spain.
Hazelden, Katina; Yee-King, Matthew; Confalonieri, Roberto; Sierra, Carles; Ghedini, Fiammetta; De Jonge, Dave; Osman, Nardine and d'Inverno, Mark. 2013. 'Multiuser Museum Interactives for Shared Cultural Experiences: an Agent-based Approach'. In: CHI'13 Extended Abstracts on Human Factors in Computing Systems. Paris.
Hazelden, Katina; Yee-King, Matthew; d'Inverno, Mark; Confalonieri, Roberto; De Jonge, Dave; Amgoud, Leila; Osman, Nardine; Prade, Henri and Sierra, Carles. 2012. 'WeCurate: Designing for synchronised browsing and social negotiation'. In: The first International Conference on Agreement Technologies. Dubrovnik, Croatia.
Yee-King, Matthew and Roth, Martin. 2011. 'A Comparison of Parametric Optimisation Techniques for Musical Instrument Tone Matching'. In: Audio Engineering Society Convention 130. London, United Kingdom.
Grierson, Mick; Kiefer, Chris and Yee-King, Matthew. 2011. 'Progress Report on the EAVI BCI Toolkit for Music: Musical Applications of Algorithms for use with consumer brain computer interfaces'. In: Proc. ICMC. Huddersfield, United Kingdom.
Osman, Nardine; d'Inverno, Mark; Sierra, Carles; Amgoud, Leila; Prade, Henri; Yee-King, Matthew; Confalonieri, Roberto; de Jonge, Dave and Hazelden, Katina. 2013. An Experience-Based BDI Logic: Motivating Shared Experiences and Intentionality. Working Paper. IIIA, Vienna, Austria.