Collaborators

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John Maclachlan
School of Geography & Earth Sciences, McMaster
Data GIS

John is the Director of Maps, Data and Geographic Information Systems (GIS) at McMaster University. He is also a lecturer at McMaster in courses related to environmental science, earth science and GIS and gives students the opportunity to complete non-traditional assignments using blogs, wikis and podcasts. Current research interests include exploring how to effectively incorporate multimedia into classes and further advancement of incorporating GIS into non-traditional fields outside of geography.

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Nick Collins
Durham University, UK
MIR, computer music researcher, composer

Nick is a researcher in the field of computer music, also active in composition and performance. He lectures at the University of Sussex, UK, running the music informatics degree programmes and research group. Research interests include machine listening, music information retrieval, interactive and generative music, and the musicology of electronic music. He co-edited the Cambridge Companion to Electronic Music (Cambridge University Press 2007) and The SuperCollider Book (MIT Press, 2011) and wrote the Introduction to Computer Music (Wiley 2009). iPhone apps include RISCy, TOPLAPapp, Concat, BBCut, and PhotoNoise for iPad. Further information, including publications, music, code and more, is available here. In September 2013 Nick takes up the post of Reader in Music Composition at University of Durham, UK.

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Dan Tidhar
Centre for Music & Science, University of Cambridge, UK
Data mining, musician, computer science

Following several years as a software developer (specialising in operating systems and storage devices), Dan completed an M.Sc. in Computational Linguistics (Edinburgh), a Masters in Music (UdK-Berlin) and a PhD in Computer Science (TU-Berlin). Subsequently he held post-doctoral research fellowships in Computational Linguistics and Text Mining (Cambridge University, UK), Information Retrieval and Databases (Goldsmiths, University of London), and MIR and Semantic Web technologies (Queen Mary, University of London). Dan’s research interests include Data Mining, Multimedia and MIR. His current position, at King’s College London, involves research in Machine Learning and Music Visualization.