Soheila Kookalani’s innovative approach to structural engineering, coupled with her strong commitment to sustainability and integration of advanced technologies, positions her as a highly suitable candidate for the Research for Best Researcher Award. Her work has significant implications for the future of sustainable construction, making her a valuable asset to both academia and industry.
Education
Soheila Kookalani pursued her academic journey with a solid foundation in architectural and civil engineering. She earned her Bachelor of Science in Architectural Engineering from Azad University in Iran, where her thesis explored hybrid architecture in cinematic arts. She then advanced her studies with a Master of Science in Civil and Structural Engineering from Hohai University, China, focusing on the seismic performance of hybrid structures in high-rise buildings. Her academic journey culminated with a Ph.D. from Shanghai Jiao Tong University, China, where she focused on the structural optimization of GFRP elastic gridshells using machine learning techniques. Her doctoral research contributed to advancing knowledge in structural design and building sustainability. Throughout her studies, Soheila has consistently integrated innovative technologies, such as artificial intelligence and machine learning, into her research, making her an authority in the field of structural design and optimization for sustainable construction.
Experience
Soheila Kookalani has accumulated extensive experience in civil and structural engineering, with a primary focus on sustainable design practices. She currently serves as a Research Associate at the University of Cambridge, where she is engaged in a groundbreaking project on the reuse of structural steel in construction. Her experience spans across diverse areas, including the circular economy, life-cycle assessment, building information modeling (BIM), and digital twin technology. From 2018 to 2022, she conducted research on GFRP elastic gridshells as part of her Ph.D. at Shanghai Jiao Tong University. Prior to this, Soheila gained practical experience working on seismic performance evaluation of hybrid structures during her Master’s at Hohai University. Her expertise also extends to the application of artificial intelligence in optimizing structural designs, demonstrating her capacity to bridge the gap between theoretical research and practical application in sustainable construction.
Awards and Honors
Throughout her academic and professional career, Soheila Kookalani has been recognized for her outstanding contributions to civil and structural engineering. She has received several prestigious awards and honors, including recognition from leading engineering conferences and academic institutions. Her work on the integration of AI and machine learning in structural design has garnered international attention, earning her accolades for innovation in sustainable construction. Soheila has also been honored for her research on GFRP elastic gridshells, receiving commendations for excellence in structural optimization and sustainable design. Her role as a published author in top-tier engineering journals has further solidified her reputation as a leading researcher in the field. Additionally, Soheila’s contributions to the reuse of structural steel and her involvement in cutting-edge projects at the University of Cambridge have earned her numerous industry awards, highlighting her commitment to environmental responsibility and sustainable engineering practices.
Research Focus
Soheila Kookalani’s research is centered on the intersection of civil engineering, sustainability, and advanced technology. Her primary focus is on steel reuse, promoting a circular economy in construction through the reuse of structural components. She is also deeply involved in life-cycle assessments, aiming to reduce the environmental impact of construction projects. Her research integrates building information modeling (BIM) and digital twin technology to enhance the design, monitoring, and optimization of construction projects. Soheila is particularly interested in applying artificial intelligence (AI) and machine learning to optimize structural designs, especially in the context of GFRP elastic gridshells. Her work on generative AI in structural engineering seeks to streamline design processes and improve sustainability. By combining these advanced technologies, her research contributes to developing more efficient, eco-friendly building practices that align with global sustainability goals.
Publication Top Notes
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BIM-based augmented reality for facility maintenance management
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Structural analysis of GFRP elastic gridshell structures by particle swarm optimization and least square support vector machine algorithms
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Shape optimization of GFRP elastic gridshells by the weighted Lagrange ε-twin support vector machine and multi-objective particle swarm optimization algorithm considering …
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An analytic approach to predict the shape and internal forces of barrel vault elastic gridshells during lifting construction
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Effect of Fluid Viscous Damper parameters on the seismic performance