
About
Kambiz Rakhshanbabanari is a Lecturer in Construction Engineering and Management and Deputy Programme Leader for the Construction Engineering Management (CEM) BSc program. His research focuses on integrating computer vision, machine learning, and deep learning into sustainable building design and management, with an emphasis on energy efficiency, thermal performance, and circular economy frameworks. He holds a PhD and has over 15 years of industry experience in the Oil and Gas sector, specializing in mega-projects and applied data science.
Key research interests include building damage detection via computer vision, predictive thermal performance modeling using IR thermography, and optimizing building operations through Bayesian Networks and Gaussian Processes. He advocates for the circular economy in construction through machine learning-driven resource optimization and explores renewable energy integration, HVAC systems, and whole-building design for sustainability. Ongoing projects include the Upgrading Britain’s Homes coalition (UKGBC Home Retrofit Investment Calculator) and the Demonstration of Energy Efficiency Potential (DEEP) initiative.
His work also addresses barriers to circular economy adoption in construction, economic analyses of sustainable practices, and life cycle assessments (LCA/LCCA) to enhance environmental and economic outcomes. He contributes to conferences like the Sustainable Ecological Engineering Design for Society (SEEDS) and collaborates on technology evaluations such as the SMETER project.
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