Posted on 20/08/202520/08/2025 by Best Paper Awards Dr. Soheila Kookalani | Engineering | Best Paper Award Research Associate at Cambridge University, United Kingdom Dr. Soheila Kookalani is a distinguished researcher in civil and structural engineering, specializing in artificial intelligence, machine learning, sustainable construction, and digital twin technologies. Currently a Research Associate at the University of Cambridge, her work focuses on steel reuse, circular economy, and structural optimization to promote sustainable infrastructure. She earned her Ph.D. in Civil and Structural Engineering from Shanghai Jiao Tong University, supported by strong academic training at Hohai University and Azad University. With an impressive publication record in high-impact journals and international conferences, she has advanced knowledge in structural design automation and resilient construction practices. Beyond research, she contributes as a reviewer, editorial board member, guest editor, and invited speaker, while also teaching and mentoring students. Her achievements demonstrate academic excellence, global collaboration, and leadership in advancing sustainable engineering solutions. Professional Profile Google Scholar | Orcid Profile | Scopus Profile Education Dr. Soheila Kookalani has built a strong academic foundation across globally recognized institutions. She earned her Ph.D. in Civil and Structural Engineering from Shanghai Jiao Tong University, where her research explored structural optimization and machine learning applications for gridshell structures. She completed her Master’s degree in Civil and Structural Engineering at Hohai University, focusing on the seismic performance of steel-concrete hybrid structures, following a Bachelor’s in Architectural Engineering from Azad University, where she developed hybrid architecture concepts for sustainable design. This academic journey provided her with multidisciplinary expertise spanning architecture, civil engineering, and computational modeling. Her progression from undergraduate through doctoral studies highlights a consistent dedication to merging innovative design with engineering principles, forming the basis for her later research on sustainable construction, digital twins, and artificial intelligence-driven structural design. Experience Dr. Kookalani is currently a Research Associate in Construction Engineering at the University of Cambridge, where she leads work on sustainable construction practices, including steel reuse, circular economy applications, and digital twin technologies. Her role has involved collaboration with international partners and industry stakeholders to develop innovative solutions for life cycle assessment and sustainable design. She has actively contributed to teaching and supervision at Cambridge, engaging with undergraduate and postgraduate students in mechanics, aerodynamics, and structural engineering courses. Previously, she undertook significant academic and research roles during her studies in China, working on advanced computational and structural analysis projects. Her professional experience is distinguished by its combination of high-impact research, curriculum development, knowledge transfer, and industry collaboration, positioning her as a bridge between academic innovation and practical engineering applications. Research Interest Dr. Kookalani’s research interests are centered on sustainable structural engineering and the integration of advanced technologies into civil infrastructure. She focuses on steel reuse, structural optimization, circular economy approaches, and life cycle assessment to advance sustainable design practices. Her expertise in artificial intelligence, machine learning, and deep learning enables her to apply advanced computational models to construction automation, lightweight structures, and generative design. She is also deeply engaged in digital twin applications, building information modeling, and robotics for the built environment, reflecting a forward-looking vision for smart and adaptive construction systems. Her interdisciplinary approach connects materials science, computational engineering, and sustainability, making her research highly relevant for addressing global challenges in resource efficiency, climate change mitigation, and infrastructure resilience. Awards and Honors Dr. Kookalani has earned multiple academic honors in recognition of her scholarly excellence and dedication. She received a full scholarship from Shanghai Jiao Tong University to pursue her Ph.D., reflecting her strong academic merit and research potential. Prior to that, she was awarded a scholarship for her Master’s studies at Hohai University. During her undergraduate years at Azad University, she was consistently recognized as a top student in architectural design courses, with her projects highlighted for their creativity and development. She also served as a member of the student board at the Architecture Engineering Scientific Association, demonstrating early leadership and academic engagement. These achievements reflect a trajectory of sustained academic distinction, research innovation, and leadership, laying a strong foundation for her ongoing success as a global researcher in sustainable engineering. Research Skill Dr. Kookalani possesses a comprehensive set of research skills that combine computational expertise, engineering knowledge, and interdisciplinary applications. She is proficient in programming languages such as Python and MATLAB, and advanced software including Abaqus, AutoCAD, Revit, Rhino, Grasshopper, Etabs, and SAP2000, enabling her to model, analyze, and optimize complex structures. Her technical expertise extends to machine learning, digital twins, life cycle assessment, and environmental product declarations, aligning with her sustainability-focused research. She is adept in data-driven modeling, structural performance prediction, and optimization techniques such as swarm intelligence and support vector machines. In addition, she has experience in visualization tools like Lumion, Blender, and Adobe Suite, enhancing her ability to present research outputs effectively. These skills empower her to bridge advanced computational methods with practical engineering solutions for sustainable construction. Publication Top Notes Title: Trajectory of Building and Structural Design Automation from Generative Design Towards the Integration of Deep Generative Models and Optimization: A ReviewAuthors: Soheila Kookalani, E. Parn, I. Brilakis, S. Dirar, M. Theofanous, A. Faramarzi, M. Mahdavipour, Q. FengYear: 2024Citation: Journal of Building Engineering, 97:110972 Title: Shape Optimization of GFRP Elastic Gridshells by the Weighted Lagrange Ε-Twin Support Vector Machine and Multi-Objective Particle Swarm Optimization Algorithm Considering Structural WeightAuthors: Soheila Kookalani, B. Cheng, S. XiangYear: 2021Citation: Structures, 33:2066–2084 Title: Structural Performance Assessment of GFRP Elastic Gridshells by Machine Learning Interpretability MethodsAuthors: Soheila Kookalani, B. Cheng, J. L. Chavez TorresYear: 2022Citation: Frontiers of Structural and Civil Engineering, 16:1249–1266 Title: Form-Finding of Lifting Self-Forming GFRP Elastic Gridshells Based on Machine Learning Interpretability MethodsAuthors: Soheila Kookalani, S. Nyunn, S. XiangYear: 2022Citation: Structural Engineering and Mechanics, 84(5):605–618 Title: An Overview of Optimal Damper Placement Methods in StructuresAuthors: Soheila Kookalani, D. Shen, L. Zhu, M. LindseyYear: 2021Citation: Iranian Journal of Science and Technology – Transactions of Civil Engineering, 46:1785–1804 Title: An Analytic Solution for Form Finding of GFRP Elastic Gridshells during Lifting ConstructionAuthors: S. Xiang, B. Cheng, Soheila KookalaniYear: 2020Citation: Composite Structures, 244:112290 Title: An Analytic Approach to Predict the Shape and Internal Forces of Barrel Vault Elastic Gridshells during Lifting ConstructionAuthors: S. Xiang, B. Cheng, Soheila Kookalani, J. ZhaoYear: 2021Citation: Structures, 29:628–637 Title: An Integrated Approach of Form Finding and Construction Simulation for Glass Fiber-Reinforced Polymer Elastic GridshellsAuthors: S. Xiang, B. Cheng, L. Zou, Soheila KookalaniYear: 2020Citation: Structural Design of Tall and Special Buildings, 29(5):e1698 Title: Introduction of Methodology for BIM & DSSAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 31–42 Title: BIM-Based DSS for HVAC Root-Cause DetectionAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 43–57 Title: BIM-Based DSS for Building Condition AssessmentAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 59–78 Title: BIM-Based DSS for Enhancing Occupants’ ComfortAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 79–99 Title: BIM-Based Augmented Reality for Facility Maintenance ManagementAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 101–112 Title: GFRP Elastic Gridshell Structures: A Review of Methods, Research, Applications, Opportunities, and ChallengesAuthors: Soheila Kookalani, Htay HtayaungYear: 2023Citation: Journal of Civil Engineering and Materials Application Title: Structural Analysis of GFRP Elastic Gridshell Structures by Particle Swarm Optimization and Least Square Support Vector Machine AlgorithmsAuthors: Soheila Kookalani, B. ChengYear: 2021Citation: Journal of Civil Engineering and Materials Application Title: Effect of Fluid Viscous Damper Parameters on the Seismic PerformanceAuthors: Soheila Kookalani, D. ShenYear: 2020Citation: Journal of Civil Engineering and Materials Application, 4(3) Title: An Overview of the Particle Swarm Optimization Algorithms Applied to Optimization of StructuresAuthors: Soheila KookalaniYear: 2019Citation: Civil Engineering Journal, 5(11):2336–2349 Title: Analysis and Optimal Location of Fluid Viscous Dampers for Multistory Irregular Steel Structures under Seismic ExcitationAuthors: Soheila Kookalani, M. Daneshvaran, M. NooriYear: 2019Citation: Civil Engineering Journal, 5(7):1594–1607 Title: Optimal Viscous Damper Location for Multi-Story Steel Structures by Genetic AlgorithmAuthors: Soheila Kookalani, S. Arabzadeh, M. NooriYear: 2018Citation: Civil Engineering Journal, 4(11):2590–2601 Title: Optimal Placement of Fluid Viscous Dampers in Steel Structures Subjected to Seismic Excitation by Genetic AlgorithmAuthors: Soheila Kookalani, S. Arabzadeh, M. NooriYear: 2018Citation: Civil Engineering Journal, 4(5):1061–1072 Conclusion Dr. Soheila Kookalani is an innovative and forward-thinking researcher whose career integrates civil engineering, artificial intelligence, and sustainability. With strong academic credentials, professional experience at leading institutions, and a significant publication record, she has made meaningful contributions to the advancement of structural optimization, digital construction, and sustainable design. Her work has influenced both academia and industry by offering scalable solutions for steel reuse, resilient infrastructure, and circular economy practices. Beyond research, her leadership through teaching, editorial activities, conference committees, and invited talks reflects her commitment to knowledge sharing and community impact. Recognized with prestigious scholarships and awards, she continues to expand her global collaborations and research impact. Dr. Kookalani exemplifies academic excellence, technical innovation, and societal contribution, making her a valuable contributor to the future of sustainable engineering. Soheila Kookalani | Engineering | Best Paper Awards
Dr. Soheila Kookalani is a distinguished researcher in civil and structural engineering, specializing in artificial intelligence, machine learning, sustainable construction, and digital twin technologies. Currently a Research Associate at the University of Cambridge, her work focuses on steel reuse, circular economy, and structural optimization to promote sustainable infrastructure. She earned her Ph.D. in Civil and Structural Engineering from Shanghai Jiao Tong University, supported by strong academic training at Hohai University and Azad University. With an impressive publication record in high-impact journals and international conferences, she has advanced knowledge in structural design automation and resilient construction practices. Beyond research, she contributes as a reviewer, editorial board member, guest editor, and invited speaker, while also teaching and mentoring students. Her achievements demonstrate academic excellence, global collaboration, and leadership in advancing sustainable engineering solutions. Professional Profile Google Scholar | Orcid Profile | Scopus Profile
Education Dr. Soheila Kookalani has built a strong academic foundation across globally recognized institutions. She earned her Ph.D. in Civil and Structural Engineering from Shanghai Jiao Tong University, where her research explored structural optimization and machine learning applications for gridshell structures. She completed her Master’s degree in Civil and Structural Engineering at Hohai University, focusing on the seismic performance of steel-concrete hybrid structures, following a Bachelor’s in Architectural Engineering from Azad University, where she developed hybrid architecture concepts for sustainable design. This academic journey provided her with multidisciplinary expertise spanning architecture, civil engineering, and computational modeling. Her progression from undergraduate through doctoral studies highlights a consistent dedication to merging innovative design with engineering principles, forming the basis for her later research on sustainable construction, digital twins, and artificial intelligence-driven structural design. Experience Dr. Kookalani is currently a Research Associate in Construction Engineering at the University of Cambridge, where she leads work on sustainable construction practices, including steel reuse, circular economy applications, and digital twin technologies. Her role has involved collaboration with international partners and industry stakeholders to develop innovative solutions for life cycle assessment and sustainable design. She has actively contributed to teaching and supervision at Cambridge, engaging with undergraduate and postgraduate students in mechanics, aerodynamics, and structural engineering courses. Previously, she undertook significant academic and research roles during her studies in China, working on advanced computational and structural analysis projects. Her professional experience is distinguished by its combination of high-impact research, curriculum development, knowledge transfer, and industry collaboration, positioning her as a bridge between academic innovation and practical engineering applications. Research Interest Dr. Kookalani’s research interests are centered on sustainable structural engineering and the integration of advanced technologies into civil infrastructure. She focuses on steel reuse, structural optimization, circular economy approaches, and life cycle assessment to advance sustainable design practices. Her expertise in artificial intelligence, machine learning, and deep learning enables her to apply advanced computational models to construction automation, lightweight structures, and generative design. She is also deeply engaged in digital twin applications, building information modeling, and robotics for the built environment, reflecting a forward-looking vision for smart and adaptive construction systems. Her interdisciplinary approach connects materials science, computational engineering, and sustainability, making her research highly relevant for addressing global challenges in resource efficiency, climate change mitigation, and infrastructure resilience. Awards and Honors Dr. Kookalani has earned multiple academic honors in recognition of her scholarly excellence and dedication. She received a full scholarship from Shanghai Jiao Tong University to pursue her Ph.D., reflecting her strong academic merit and research potential. Prior to that, she was awarded a scholarship for her Master’s studies at Hohai University. During her undergraduate years at Azad University, she was consistently recognized as a top student in architectural design courses, with her projects highlighted for their creativity and development. She also served as a member of the student board at the Architecture Engineering Scientific Association, demonstrating early leadership and academic engagement. These achievements reflect a trajectory of sustained academic distinction, research innovation, and leadership, laying a strong foundation for her ongoing success as a global researcher in sustainable engineering. Research Skill Dr. Kookalani possesses a comprehensive set of research skills that combine computational expertise, engineering knowledge, and interdisciplinary applications. She is proficient in programming languages such as Python and MATLAB, and advanced software including Abaqus, AutoCAD, Revit, Rhino, Grasshopper, Etabs, and SAP2000, enabling her to model, analyze, and optimize complex structures. Her technical expertise extends to machine learning, digital twins, life cycle assessment, and environmental product declarations, aligning with her sustainability-focused research. She is adept in data-driven modeling, structural performance prediction, and optimization techniques such as swarm intelligence and support vector machines. In addition, she has experience in visualization tools like Lumion, Blender, and Adobe Suite, enhancing her ability to present research outputs effectively. These skills empower her to bridge advanced computational methods with practical engineering solutions for sustainable construction. Publication Top Notes Title: Trajectory of Building and Structural Design Automation from Generative Design Towards the Integration of Deep Generative Models and Optimization: A ReviewAuthors: Soheila Kookalani, E. Parn, I. Brilakis, S. Dirar, M. Theofanous, A. Faramarzi, M. Mahdavipour, Q. FengYear: 2024Citation: Journal of Building Engineering, 97:110972 Title: Shape Optimization of GFRP Elastic Gridshells by the Weighted Lagrange Ε-Twin Support Vector Machine and Multi-Objective Particle Swarm Optimization Algorithm Considering Structural WeightAuthors: Soheila Kookalani, B. Cheng, S. XiangYear: 2021Citation: Structures, 33:2066–2084 Title: Structural Performance Assessment of GFRP Elastic Gridshells by Machine Learning Interpretability MethodsAuthors: Soheila Kookalani, B. Cheng, J. L. Chavez TorresYear: 2022Citation: Frontiers of Structural and Civil Engineering, 16:1249–1266 Title: Form-Finding of Lifting Self-Forming GFRP Elastic Gridshells Based on Machine Learning Interpretability MethodsAuthors: Soheila Kookalani, S. Nyunn, S. XiangYear: 2022Citation: Structural Engineering and Mechanics, 84(5):605–618 Title: An Overview of Optimal Damper Placement Methods in StructuresAuthors: Soheila Kookalani, D. Shen, L. Zhu, M. LindseyYear: 2021Citation: Iranian Journal of Science and Technology – Transactions of Civil Engineering, 46:1785–1804 Title: An Analytic Solution for Form Finding of GFRP Elastic Gridshells during Lifting ConstructionAuthors: S. Xiang, B. Cheng, Soheila KookalaniYear: 2020Citation: Composite Structures, 244:112290 Title: An Analytic Approach to Predict the Shape and Internal Forces of Barrel Vault Elastic Gridshells during Lifting ConstructionAuthors: S. Xiang, B. Cheng, Soheila Kookalani, J. ZhaoYear: 2021Citation: Structures, 29:628–637 Title: An Integrated Approach of Form Finding and Construction Simulation for Glass Fiber-Reinforced Polymer Elastic GridshellsAuthors: S. Xiang, B. Cheng, L. Zou, Soheila KookalaniYear: 2020Citation: Structural Design of Tall and Special Buildings, 29(5):e1698 Title: Introduction of Methodology for BIM & DSSAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 31–42 Title: BIM-Based DSS for HVAC Root-Cause DetectionAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 43–57 Title: BIM-Based DSS for Building Condition AssessmentAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 59–78 Title: BIM-Based DSS for Enhancing Occupants’ ComfortAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 79–99 Title: BIM-Based Augmented Reality for Facility Maintenance ManagementAuthors: H. Alavi, Soheila Kookalani, F. Rahimian, N. ForcadaYear: 2024Citation: Integrated Building Intelligence, pp. 101–112 Title: GFRP Elastic Gridshell Structures: A Review of Methods, Research, Applications, Opportunities, and ChallengesAuthors: Soheila Kookalani, Htay HtayaungYear: 2023Citation: Journal of Civil Engineering and Materials Application Title: Structural Analysis of GFRP Elastic Gridshell Structures by Particle Swarm Optimization and Least Square Support Vector Machine AlgorithmsAuthors: Soheila Kookalani, B. ChengYear: 2021Citation: Journal of Civil Engineering and Materials Application Title: Effect of Fluid Viscous Damper Parameters on the Seismic PerformanceAuthors: Soheila Kookalani, D. ShenYear: 2020Citation: Journal of Civil Engineering and Materials Application, 4(3) Title: An Overview of the Particle Swarm Optimization Algorithms Applied to Optimization of StructuresAuthors: Soheila KookalaniYear: 2019Citation: Civil Engineering Journal, 5(11):2336–2349 Title: Analysis and Optimal Location of Fluid Viscous Dampers for Multistory Irregular Steel Structures under Seismic ExcitationAuthors: Soheila Kookalani, M. Daneshvaran, M. NooriYear: 2019Citation: Civil Engineering Journal, 5(7):1594–1607 Title: Optimal Viscous Damper Location for Multi-Story Steel Structures by Genetic AlgorithmAuthors: Soheila Kookalani, S. Arabzadeh, M. NooriYear: 2018Citation: Civil Engineering Journal, 4(11):2590–2601 Title: Optimal Placement of Fluid Viscous Dampers in Steel Structures Subjected to Seismic Excitation by Genetic AlgorithmAuthors: Soheila Kookalani, S. Arabzadeh, M. NooriYear: 2018Citation: Civil Engineering Journal, 4(5):1061–1072 Conclusion Dr. Soheila Kookalani is an innovative and forward-thinking researcher whose career integrates civil engineering, artificial intelligence, and sustainability. With strong academic credentials, professional experience at leading institutions, and a significant publication record, she has made meaningful contributions to the advancement of structural optimization, digital construction, and sustainable design. Her work has influenced both academia and industry by offering scalable solutions for steel reuse, resilient infrastructure, and circular economy practices. Beyond research, her leadership through teaching, editorial activities, conference committees, and invited talks reflects her commitment to knowledge sharing and community impact. Recognized with prestigious scholarships and awards, she continues to expand her global collaborations and research impact. Dr. Kookalani exemplifies academic excellence, technical innovation, and societal contribution, making her a valuable contributor to the future of sustainable engineering.