M
Mat Santamouris
Researcher at University of New South Wales
Publications - 107
Citations - 4337
Mat Santamouris is an academic researcher from University of New South Wales. The author has contributed to research in topics: Urban heat island & Energy consumption. The author has an hindex of 33, co-authored 107 publications receiving 3270 citations. Previous affiliations of Mat Santamouris include Kyung Hee University & University College London.
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Cooling the buildings – past, present and future
TL;DR: In this paper, the authors present and discuss the details of the framework which defines the present and future cooling energy consumption of the building sector, while existing estimates and predictions regarding the future cooling consumption of individual buildings as well as of the total building sector are documented, evaluated and analyzed.
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Heat Island Research in Europe: The State of the Art
TL;DR: In this paper, the authors summarized recent research on urban heat islands carried out in Europe and presented new deterministic and data-driven models developed to estimate the amplitude of heat islands, as well as the impact of green spaces and the development and testing of white and coloured cool materials.
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Experimental testing of cool colored thin layer asphalt and estimation of its potential to improve the urban microclimate
Afroditi Synnefa,Theoni Karlessi,N. Gaitani,Mat Santamouris,D.N. Assimakopoulos,C. Papakatsikas +5 more
TL;DR: In this paper, the spectral properties and thermal performance of five color thin layer asphalt samples in comparison to a sample of conventional black asphalt were analyzed. And the results of a study aiming to measure and analyze the solar spectral properties was presented.
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Innovating to zero the building sector in Europe: Minimising the energy consumption, eradication of the energy poverty and mitigating the local climate change
TL;DR: In this article, the authors discuss issues related to the three major problems of the built environment in Europe and in particular, the energy consumption of buildings, energy poverty and the local climate change.
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The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: energy implications of AI-based thermal comfort controls
TL;DR: This work presents a review of the current AI-based methodologies being used to enhance thermal comfort in indoor spaces using diverse machine learning (ML) algorithms and their deployment in building control systems for energy saving purposes.