The Department of Architecture reflects the multi and trans-disciplinary nature of architecture and urbanism, focussing on real-world problems. This includes the work of the Urban Design Studies Unit (UDSU), which is pioneering 'urban morphometrics', harnessing spatial data science, urban geo-data processing, and machine learning approaches to better understand cities, their form, functions and impact, with the ultimate goal of making them more resilient.
Explore some of this Open Access research from the Departments of Architecture.
Esposito, Francesco P. and Cummins, Mark (2016) Multiple hypothesis testing of market risk forecasting models. Journal of Forecasting, 35 (5). pp. 381-399. ISSN 0277-6693
Jeon, Jooyoung and Taylor, James (2013) Using CAViaR models with implied volatility for value-at-risk estimation. Journal of Forecasting, 32 (1). 62–74. ISSN 0277-6693
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