Building Energy & Sustainability Laboratory (BESLab)
BESLab is now officially renamed to TensorBuild Lab and hosted on University of Arizona's Official Website:Â
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The Building Energy & Sustainability Laboratory (BESLab), led by Prof. Liang Zhang, is an interdisciplinary research group in the Department of Civil and Architectural Engineering and Mechanics (CAEM) at the University of Arizona (U of A).
The Building Energy & Sustainability Laboratory (BESLab), led by Prof. Liang Zhang, is an interdisciplinary research group in the Department of Civil and Architectural Engineering and Mechanics (CAEM) at the University of Arizona (U of A).
BESLab advances science, engineering, and education toward an energy-efficient and sustainable evolution of smart buildings and cities in the global challenges of climate change and grid transformation. Our research explores creative solutions to energy modeling and analysis from building scale to urban scale, connects renewable and conventional resources for buildings and cities, and applies advanced controls and fault detections in building energy systems for greater grid security and flexibility.
BESLab advances science, engineering, and education toward an energy-efficient and sustainable evolution of smart buildings and cities in the global challenges of climate change and grid transformation. Our research explores creative solutions to energy modeling and analysis from building scale to urban scale, connects renewable and conventional resources for buildings and cities, and applies advanced controls and fault detections in building energy systems for greater grid security and flexibility.
 Recent News
 Recent News
[September 13, 2024] [New Paper Published] Zhang, L., Chen, Z., & Ford, V. (2024). Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies. (link)
[September 13, 2024] [New Paper Published] Zhang, L., Chen, Z., & Ford, V. (2024). Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies. (link)
[August 23, 2024] [Group Member] We warmly welcome Xiaoqin Fu, who has recently joined the BESLab team as a graduate research assistant!
[August 23, 2024] [Group Member] We warmly welcome Xiaoqin Fu, who has recently joined the BESLab team as a graduate research assistant!
[July 29, 2024] [New Paper Published] Zhang, L., Kaufman, Z., & Leach, M. (2024). Physics-informed hybrid modeling methodology for building infiltration. Energy and Buildings, 114580. (link)
[July 29, 2024] [New Paper Published] Zhang, L., Kaufman, Z., & Leach, M. (2024). Physics-informed hybrid modeling methodology for building infiltration. Energy and Buildings, 114580. (link)
[May 27, 2024] [New Paper Published] Jiang, G., Ma, Z., Zhang, L., & Chen, J. (2024). EPlus-LLM: A large language model-based computing platform for automated building energy modeling. Applied Energy, 367, 123431.
[May 27, 2024] [New Paper Published] Jiang, G., Ma, Z., Zhang, L., & Chen, J. (2024). EPlus-LLM: A large language model-based computing platform for automated building energy modeling. Applied Energy, 367, 123431.
[Jan 16, 2024] [New Funding & Project] BESLab is delighted to announce the AI-Enhanced Interactive Data Infrastructure project, a transformative initiative to decarbonize building and transportation sectors using Large Language Models like GPT-4 for data analysis and interaction. Spearheaded by Prof. Liang Zhang, this award-winning project funded by FY24 Innovative Projects in Energy Grants, is set to deliver an interactive data framework and a comprehensive case study for the City of Tucson, advancing sustainability efforts and research capabilities at University of Arizona.
[Jan 16, 2024] [New Funding & Project] BESLab is delighted to announce the AI-Enhanced Interactive Data Infrastructure project, a transformative initiative to decarbonize building and transportation sectors using Large Language Models like GPT-4 for data analysis and interaction. Spearheaded by Prof. Liang Zhang, this award-winning project funded by FY24 Innovative Projects in Energy Grants, is set to deliver an interactive data framework and a comprehensive case study for the City of Tucson, advancing sustainability efforts and research capabilities at University of Arizona.
[Feb 5, 2024] [Group Member] We warmly welcome Amir Hosain Sharif, who has recently joined the BESLab team as a Postdoctoral Researcher!
[Feb 5, 2024] [Group Member] We warmly welcome Amir Hosain Sharif, who has recently joined the BESLab team as a Postdoctoral Researcher!
[March 21, 2023] [New Paper Published] Zhang, L., Chen, Z., Zhang, X., Pertzborn, A., & Jin, X. (2023, March). Challenges and opportunities of machine learning control in building operations. In Building Simulation (pp. 1-22). Beijing: Tsinghua University Press. (link)
[March 21, 2023] [New Paper Published] Zhang, L., Chen, Z., Zhang, X., Pertzborn, A., & Jin, X. (2023, March). Challenges and opportunities of machine learning control in building operations. In Building Simulation (pp. 1-22). Beijing: Tsinghua University Press. (link)
[August 23, 2022] [We Are Hiring] Two funded PhD positions are available in BESLab in the Department of Civil and Architectural Engineering and Mechanics at the University of Arizona. See details here.
[August 23, 2022] [We Are Hiring] Two funded PhD positions are available in BESLab in the Department of Civil and Architectural Engineering and Mechanics at the University of Arizona. See details here.
[August 1, 2024] [New Funding & Project] BESLab is delighted to announce the participation in the Bridging Gaps Towards a Sustainable Energy Future by Applying Human Factors in Transportation-Building Integration project, funded by RII 2024 UArizona National Labs Partnerships Grants. Spearheaded/lead by Prof. Alyssa Ryan and co-lead by Prof. Liang Zhang, this award-winning project is set to deliver human behavior models, particularly in the integrated domains of building and transportation energy use modeling, as part of the broader endeavor toward decarbonization.
[August 1, 2024] [New Funding & Project] BESLab is delighted to announce the participation in the Bridging Gaps Towards a Sustainable Energy Future by Applying Human Factors in Transportation-Building Integration project, funded by RII 2024 UArizona National Labs Partnerships Grants. Spearheaded/lead by Prof. Alyssa Ryan and co-lead by Prof. Liang Zhang, this award-winning project is set to deliver human behavior models, particularly in the integrated domains of building and transportation energy use modeling, as part of the broader endeavor toward decarbonization.
[Feb 5, 2024] [New Funding & Project] BESLab is delighted to announce the subcontract Technical Support for Empirical Validation Data Analysis and Specification Development funded by the U.S. Department of Energy and National Renewable Energy Laboratory. The Subcontractor will foster a collaborative partnership with the academic community and NREL staff to advance energy-related research and engage faculty and students. Key responsibilities include utilizing machine learning for building energy modeling and control, providing expertise in fault detection and diagnostics to reduce energy wastage, contributing to the development of smart and connected communities through advanced controls and modeling to identify energy and carbon reduction strategies, and offering analytical support in foundational building energy modeling to underpin various projects within the building sector.
[Feb 5, 2024] [New Funding & Project] BESLab is delighted to announce the subcontract Technical Support for Empirical Validation Data Analysis and Specification Development funded by the U.S. Department of Energy and National Renewable Energy Laboratory. The Subcontractor will foster a collaborative partnership with the academic community and NREL staff to advance energy-related research and engage faculty and students. Key responsibilities include utilizing machine learning for building energy modeling and control, providing expertise in fault detection and diagnostics to reduce energy wastage, contributing to the development of smart and connected communities through advanced controls and modeling to identify energy and carbon reduction strategies, and offering analytical support in foundational building energy modeling to underpin various projects within the building sector.
[January 15, 2023] [New Paper Published] Zhang, L., Leach, M., Chen, J., & Hu, Y. (2023). Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings. Energy, 263, 125577. (link)
[January 15, 2023] [New Paper Published] Zhang, L., Leach, M., Chen, J., & Hu, Y. (2023). Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings. Energy, 263, 125577. (link)
[September 30, 2023] [Group Member] Prof. Liang Zhang starts his joint appointment with National Renewable Energy Laboratory to promote research and education in building decolonization with advanced modeling and AI technologies.
[September 30, 2023] [Group Member] Prof. Liang Zhang starts his joint appointment with National Renewable Energy Laboratory to promote research and education in building decolonization with advanced modeling and AI technologies.
[August 23, 2022] [MISC] The Website of Building Energy & Sustainability Laboratory is online. URL: https://sites.google.com/view/beslab
[August 23, 2022] [MISC] The Website of Building Energy & Sustainability Laboratory is online. URL: https://sites.google.com/view/beslab
 Research Highlights
 Research Highlights
Urban Building Energy Modeling
Grid-Interactive Efficient Building
Machine Learning Control in Buildings
Smart and Connected Communities
Fault Detection and Diagnostics
Smart Sensors
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