Dr Kynan Tan
- PhD Art, Design and Media, UNSW Art & Design, 2018
- BMus (First Class Honours), Western Australian Academy of Performing Arts, Edith Cowan University, WA, 2010
I am an artist and researcher working with digital technologies to investigate data and algorithm. I obtained my PhD degree at UNSW Art & design, Sydney. I completed a Bachelor of Music (Music Technology) with Honours at the Western Australian Academy of Performing Arts. I am currently a postdoctoral fellow at UNSW Art & Design working with Professor Anna Munster (UNSW) and Professor Adrian Mackenzie (ANU) on the project "Re-imaging the empirical: statistical visualisation in art and science".
My artworks have been exhibited at Primavera, Museum of Contemporary Art Sydney; UNSW Galleries; Lyon Housemuseum Galleries, Melbourne; Dominik Mersch Gallery, Sydney; Beijing Media Arts Biennale; Artspace, Sydney; Perth Institute of Contemporary Arts, WA; Fremantle Arts Centre, WA; and Longli International New Media Art Festival, Guizhou Province, China. I have completed residencies at SymbioticA Biological Arts Facility at the University of Western Australia; Centre for Interdisciplinary Arts, Perth; and Performance Space, Carriageworks, Sydney. I have also performed sound and audio-visual works across Australia, China, and Japan.
I am interested in the ways that data and algorithm are rendered sensory through processes such as visualisation and sonification. In particular, my work has investigated the aspects of computation that contribute to these processes but are often rendered imperceptible, such as data centres, the materiality of data storage systems, workers who assemble electronics such as smart phones, or the extent to which these large quantities of data exist beyond our comprehension. I am currently working with machine learning systems to attempt to visualise and render sensory their complex processes, as well as to use these techniques to question the relationality and conditionality of these systems.
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
My practice-based PhD research considered how the relationality of data and algorithm can be experienced through multisensory digital artworks. In this research, I created a number of artworks using data visualisation and sonification, computer-generated simulation, and algorithmic processes. These works investigated how data and algorithm are part of larger systems which are normally nonsensible across various scales: from from voltage differences; to the imperceptibility of data and algorithmic operations; to the secrecy surrounding data centres. I draw on Alfred North Whitehead's modes of perception to explore how this nonsensibility is not the same as imperceptibility, as some aspect of these processes enters into perception as their associative relations in the mode of causal efficacy. I am continuing to examine how computational systems are rendered perceptible through both artistic and textual research.
My Teaching
I have previously taught in the areas of data aesthetics, computational design, and music composition. I am interested in teaching in areas around data visualisation and sonification, computer-generated 3D graphics and simulation, sound theory and composition, coding and interactive media, machine learning and big data.