SEES Fellows: Building Informatics: Utilizing Data-Driven Methodologies to Enable Energy Efficiency and Sustainability Planning of Urban Building Systems

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The project is supported under the NSF Science, Engineering and Education for Sustainability Fellows (SEES Fellows) program, with the goal of helping to enable discoveries needed to inform actions that lead to environmental, energy and societal sustainability while creating the necessary workforce to address these challenges. Sustainability science is an emerging field that addresses the challenges of meeting human needs without harm to the environment, and without sacrificing the ability of future generations to meet their needs. A strong scientific workforce requires individuals educated and trained in interdisciplinary research and thinking, especially in the area of sustainability science. With the SEES Fellowship support, this project will enable a promising early career researcher to establish himself in an independent research career related to sustainability. This project addresses the fact that buildings are responsible for over 40% of all energy consumption and GHG emissions in the US. The impact of building systems is even more pronounced in dense urban areas like New York City (NYC) where over 75% of GHG emissions come from energy used in buildings. Any transition towards a sustainable NYC will require addressing this energy and pollution intensive built environment. This research proposal aims to integrate data-driven methodologies from information science, social science, network science and urban planning with engineering to increase the energy efficiency and sustainability of urban building systems. Specifically, this project will identify district level energy efficiency opportunities for urban buildings systems, characterize the interdependencies between the built, natural and human environments and model the impact of energy policy instruments to enhance the sustainability and resilience of NYC and Mumbai, India. As a part of this project, the PI will build upon his expertise in civil engineering and building systems by incorporating data science, social science and urban planning into his exploration of energy and sustainability challenges facing urban building systems.