Mayowa Emmanuel Bamisaye
Papers
2
Total Citations
13
H-Index
2
About
Mayowa Emmanuel Bamisaye is an emerging researcher at the forefront of sustainable construction and environmental systems engineering. His work centers on the intersection of waste management, building material lifecycles, and advanced computational modeling. Bamisaye’s major contributions lie in integrating System Dynamics (SD) with Machine Learning—specifically Random Forest algorithms—to analyze and mitigate the environmental impacts of construction and demolition (C&D) processes. His most cited paper, “Integrating system dynamics and machine learning for environmental impact analysis of building materials in the demolition process” (2025, 7 citations), pioneers a novel framework for assessing the carbon footprint of demolition activities. A second highly cited work, “Sustainable waste management of construction materials: Mathematical modelling and analysis” (2025, 6 citations), reveals that transportation alone accounts for 30% of total energy use and CO₂eq emissions in C&D waste streams, offering data-driven pathways for reduction. Though early in his career, Bamisaye’s interdisciplinary approach—merging environmental science, systems thinking, and AI—positions him as a promising voice in the global push toward net-zero construction. His research provides actionable insights for policymakers, engineers, and urban planners seeking to decarbonize the built environment.
Research Focus
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Top Papers
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