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The Martin Centre for Architectural and Urban Studies

- the research arm of the Department of Architecture

Studying at Cambridge

Seung Hyun Cha

Graduate Student

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Biography

I joined Cambridge as a PhD student under the supervision of Prof. Koen Steemers in October 2011. Prior to coming to Cambridge, I graduated with a B.E. from Korea University, Seoul, South Korea in 2009. Immediately thereafter, I continued my studies at Stanford University by pursuing a Master's Degree in Sustainable Design and Construction and received my MS in 2011. My research interests during my master’s study in user behavior and energy use led me to work on predicting more accurately users’ movement and space-use in buildings.

My PhD research involves developing space-preference models for work-related activities in association with spatial choice behavior. I do this by measuring the relationships between a user’s space preferences, user satisfaction, and space attributes such as IEQ, the amount of space, and the degree of enclosure. The models display varying space-use probabilities in different space conditions, and thus assist architects to detect potentially crowded and underutilized space across a building in order to eliminate unnecessary space and to modify the design at a level that does not impair its functionality.

Research Summary

Space-use prediction models during the design phase provide architects with information on potentially crowded or underutilized space across a building. With the information, architects are able to eliminate unnecessary space or modify design for the sake of more efficient space-use, thereby achieving economic and environmental sustainability. However, existing models have an internal limitation in predicting space-use because they ignore or oversimplify the role of space preference of spatial choice behavior despite the fact that such behavior accounts for much of space-use, and also lack classification of building space in light of space attributes. To address such problems, my research aims to develop space preference models of spatial choice behavior by measuring the relationships between such behavior and attribute-levels of space attributes. The space preference models provide fundamental understanding on unexplored spatial choice behavior in designed space and a potential opportunity to connect spatial choice behavior and existing space-use prediction models.