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Wafiullah Shirzad researcher portrait

Researcher

Wafiullah Shirzad

Civil Engineering Researcher

Spinghar Institute of Higher Education
Moscow, Russia
4 published works

Wafiullah Shirzad is a civil engineer and researcher specializing in Building Information Modeling (BIM), Life Cycle Energy Assessment (LCEA), sustainable construction, and digital and data-driven approaches to building performance. He holds an M.Sc. in Civil Engineering (Buildings of Energy-Efficient Life Cycle) from Moscow State University of Civil Engineering (NRU MGSU), Russia, and a B.Sc. in Civil Engineering from Alfalah University, Afghanistan, where he graduated first in his class and received the Gold Medal. His research spans BIM–LCA integration, building life-cycle energy and carbon assessment, machine learning and digital tools for sustainable construction, climate-responsive and energy-efficient design, sustainable construction materials, climate change adaptation, water resources, and environmental engineering. His research portfolio includes peer-reviewed publications and conference studies addressing urban noise pollution, waste-glass applications in concrete, sustainable waste management, climate-responsive urban design, groundwater depletion, surface-water variability, and community-based climate adaptation in Afghanistan. His master's research focused on digital and data-driven approaches to building Life Cycle Energy Assessment, applying a PRISMA-compliant systematic review methodology to examine technologies and methods including BIM, machine learning, the Internet of Things (IoT), and digital twins. Combining academic research with practical experience in site engineering and surveying, his work focuses on advancing evidence-based, digitally enabled, and context-sensitive approaches to sustainable and energy-efficient built environments, particularly in developing and data-scarce regions.

1:Life Cycle Energy Assessment (LCEA) and Life Cycle Assessment (LCA) of Buildings2:BIM-LCA Integration and Digital Tools for Sustainable Construction3:Machine Learning and Data-Driven Methods for Building Performance Prediction

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