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.
Deng, Shounian and Fei, Chen and Fei, Weiyin and Mao, Xuerong (2022) The truncated EM method for jump-diffusion SDDEs with super-linearly growing diffusion and jump coefficients. Journal of Computational Mathematics. ISSN 0254-9409 (In Press)
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