Jamie is a musician, artist/coder and interdisciplinary scientific researcher. His artistic research engages with theory and practices of computational art, specialising in sound, data analysis and technological forms of social and political intervention. Jamie’s scientific research focuses on the development of computational methods for modelling processes associated with the perception, cognition and creation of music. He has undertaken post-doctoral work in the fields of computational creativity and artificial intelligence; statistical modelling of music and natural language; multi-agent systems; and knowledge representation and discovery within the Semantic Web.
- PhD (Computer Science), Goldsmiths, University of London 2012
- MA (Electroacoustic Composition), City University, London 2004
- BMus Hons (Music), City University, London 2003
Teaching and Supervision
Publications and research outputs
Wiggins, Geraint A. and Forth, Jamie. 2018. Computational Creativity and Live Algorithms. In: Alex McLean and Roger Dean, eds. The Oxford Handbook of Algorithmic Music. Oxford, UK: Oxford University Press. ISBN 9780190226992
Forth, Jamie and Wiggins, Geraint A.. 2009. An approach for identifying salient repetition in multidimensional representations of polyphonic music. In: Joseph Chan; Jacqueline W. Daykin and M. Sohel Rahman, eds. London Algorithmics 2008: Theory and Practice. London: College Publications, pp. 44-58. ISBN 9781904987970
Dean, Roger T. and Forth, Jamie. 2020. Towards a Deep Improviser: a prototype deep learning post-tonal free music generator. Neural Computing and Applications, 32(4), pp. 969-979. ISSN 0941-0643
Xiao, Ping; Toivonen, Hannu; Gross, Oskar; Cardoso, Amílcar; Correia, João; Machado, Penousal; Martins, Pedro; Goncalo Oliveira, Hugo; Sharma, Rahul; Pinto, Alexandre Miguel; Díaz, Alberto; Francisco, Virginia; Gervás, Pablo; Hervás, Raquel; León, Carlos; Forth, Jamie; Purver, Matthew; Wiggins, Geraint A.; Miljković, Dragana; Podpečan, Vid; Pollak, Senja; Kralj, Jan; Žnidaršič, Martin; Bohanec, Marko; Lavrač, Nada; Urbančič, Tanja; van der Velde, Frank and Battersby, Stuart. 2019. Conceptual Representations for Concept Creation. ACM Computing Surveys, 52(1), ISSN 0360-0300
van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S. and Wiggins, Geraint A.. 2017. Linking neural and symbolic representation and processing of conceptual structures. Frontiers in Psychology, 8, 1297. ISSN 1664-1078
Agres, Kathleen; Forth, Jamie and Wiggins, Geraint A.. 2016. Evaluation of Musical Creativity and Musical Metacreation Systems. Computers in Entertainment, 14(3), pp. 1-33.
Forth, Jamie; Agres, Kat; Purver, Matthew and Wiggins, Geraint A. 2016. Entraining IDyOT : Timing in the Information Dynamics of Thinking. Frontiers in Psychology, 7, 1575. ISSN 1664-1078
Pontis, Sheila; Kefalidou, Genovefa; Blandford, Ann; Forth, Jamie; Makri, Stephann; Sharples, Sarah; Wiggins, Geraint and Woods, Mel. 2015. Academics' responses to encountered information: Context matters. Journal of the Association for Information Science and Technology, 67(8), pp. 1883-1903. ISSN 2330-1643
Boso, Marianna; Forth, Jamie; Bordin, Annamaria; Faggioli, Raffaella; D'Angelo, Egidio; Politi, Pierluigi; Barale, Francesco and Heaton, Pam F.. 2013. Transposition Ability in a Young Musician With Autism and Blindness: Testing Cognitive Models of Autism. Psychomusicology: Music, Mind, and Brain, 23(2), pp. 109-116. ISSN 0275-3987
Forth, Jamie; Wiggins, Geraint A. and McLean, Alex. 2010. Unifying Conceptual Spaces: Concept Formation in Musical Creative Systems. Minds and Machines, 20(4), pp. 503-532. ISSN 0924-6495
Conference or Workshop Item
Lewis, David; Woodley, Ron; Forth, Jamie; Rhodes, Christophe and Wiggins, Geraint. 2011. 'Tools for Music Scholarship and their Interactions: A Case Study'. In: Supporting Digital Humanities. Copenhagen, Denmark.
Forth, Jamie; McLean, Alex and Wiggins, Geraint A.. 2008. 'Musical creativity on the conceptual level'. In: Proceedings of the 5th International Joint Workshop on Computational Creativity. Madrid, Spain.
Forth, Jamie. 2012. Cognitively-motivated geometric methods of pattern discovery and models of similarity in music. Doctoral thesis, Goldsmiths, University of London