Yordanis Alonso-Roque | Engineering | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Broadband Two-Port Rectangular Patch Radiating Element Based on a Self-Complementary Structure

Yordanis Alonso-Roque
Affiliation Research Institute of Oceanic Engineering
Country Spain
Article Title Broadband Two-Port Rectangular Patch Radiating Element Based on a Self-Complementary Structure
Documents 11
Citations 1
Subject Area Engineering
Award Category Best Paper Award
Event International Research Excellence and Best Paper Awards
ORCID 0000-0002-0649-7455

The Best Paper Award recognizes the scholarly contribution of Yordanis Alonso-Roque from the Research Institute of Oceanic Engineering for the publication entitled Broadband Two-Port Rectangular Patch Radiating Element Based on a Self-Complementary Structure. The publication contributes to the advancement of engineering research by exploring broadband antenna design using self-complementary structures. Through innovative electromagnetic design principles and practical engineering methodologies, the study supports the development of efficient radiating elements suitable for modern wireless communication systems and related applications.

Abstract

This award-recognized publication presents research on a broadband two-port rectangular patch radiating element developed using a self-complementary structure. The study investigates antenna design strategies intended to achieve wide operational bandwidth while maintaining desirable radiation characteristics. The proposed approach contributes to antenna engineering by demonstrating design concepts that may enhance the performance of broadband wireless communication systems.

Keywords

Broadband Antenna; Patch Antenna; Self-Complementary Structure; Electromagnetic Engineering; Wireless Communications; Radiating Element; Microwave Engineering; RF Design.

Introduction

Broadband antennas play a critical role in modern wireless communication technologies, radar systems, and advanced sensing applications. Researchers continue to investigate innovative antenna geometries capable of improving bandwidth, radiation efficiency, and integration into compact communication platforms. Self-complementary antenna structures have attracted considerable interest because of their theoretical broadband characteristics and practical engineering advantages.

Research Profile

The research was conducted at the Research Institute of Oceanic Engineering, Spain. The institute supports multidisciplinary engineering research with emphasis on innovative technologies, applied electromagnetic systems, and advanced engineering solutions that contribute to scientific and industrial development.

Scientific Background

Recent advances in wireless communications require antenna systems capable of operating efficiently over increasingly wider frequency ranges. Broadband antenna architectures improve communication reliability while reducing system complexity. Self-complementary geometries provide an important theoretical framework for developing broadband radiating structures suitable for next-generation engineering applications.

Methodology

The publication investigates a broadband rectangular patch radiating element incorporating a self-complementary configuration. Electromagnetic analysis, antenna design principles, and engineering evaluation methods were employed to examine the broadband characteristics and operational performance of the proposed radiating structure.

Key Findings

The study demonstrates the feasibility of applying self-complementary design concepts to broadband rectangular patch radiating elements. The proposed design contributes to broadband antenna engineering by providing a practical approach for achieving improved operational bandwidth while maintaining effective radiation performance for engineering applications.

Scientific Contributions

This publication contributes to engineering research by advancing broadband antenna design methodologies. The proposed radiating element expands knowledge in electromagnetic engineering and supports continued innovation in wireless communication technologies, RF systems, and modern antenna development.

Conclusion

The award-winning publication represents a valuable contribution to antenna engineering by investigating a broadband two-port rectangular patch radiating element based on a self-complementary structure. The research supports ongoing advances in broadband communication technologies and demonstrates the importance of innovative electromagnetic design in modern engineering applications.

References

  1. ORCID. Yordanis Alonso-Roque
    . https://orcid.org/0000-0002-0649-7455
  2. International Research Excellence and Best Paper Awards.
    https://bestpaperawards.com/

  3. Hexagonal Patch Antenna of Circular Polarization fed by an Atractive Method of Microstripline.
    https://www.researchgate.net/publication/370109111_Hexagonal_Patch_Antenna_of_Circular_Polarization_fed_by_an_Atractive_Method_of_Microstripline

  4. Electromagnetic Analysis of a 2 Port-Aperture Coupled-Rectangular Patch Antenna with Complementary Rectangular Stub.
    https://www.researchgate.net/publication/370108553_Electromagnetic_Analysis_of_a_2_Port-Aperture_Coupled-Rectangular_Patch_Antenna_with_Complementary_Rectangular_Stub

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Soheila Kookalani | Engineering | Best Paper Awards

Published on 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 Review
Authors: Soheila Kookalani, E. Parn, I. Brilakis, S. Dirar, M. Theofanous, A. Faramarzi, M. Mahdavipour, Q. Feng
Year: 2024
Citation: 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 Weight
Authors: Soheila Kookalani, B. Cheng, S. Xiang
Year: 2021
Citation: Structures, 33:2066–2084

Title: Structural Performance Assessment of GFRP Elastic Gridshells by Machine Learning Interpretability Methods
Authors: Soheila Kookalani, B. Cheng, J. L. Chavez Torres
Year: 2022
Citation: Frontiers of Structural and Civil Engineering, 16:1249–1266

Title: Form-Finding of Lifting Self-Forming GFRP Elastic Gridshells Based on Machine Learning Interpretability Methods
Authors: Soheila Kookalani, S. Nyunn, S. Xiang
Year: 2022
Citation: Structural Engineering and Mechanics, 84(5):605–618

Title: An Overview of Optimal Damper Placement Methods in Structures
Authors: Soheila Kookalani, D. Shen, L. Zhu, M. Lindsey
Year: 2021
Citation: 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 Construction
Authors: S. Xiang, B. Cheng, Soheila Kookalani
Year: 2020
Citation: Composite Structures, 244:112290

Title: An Analytic Approach to Predict the Shape and Internal Forces of Barrel Vault Elastic Gridshells during Lifting Construction
Authors: S. Xiang, B. Cheng, Soheila Kookalani, J. Zhao
Year: 2021
Citation: Structures, 29:628–637

Title: An Integrated Approach of Form Finding and Construction Simulation for Glass Fiber-Reinforced Polymer Elastic Gridshells
Authors: S. Xiang, B. Cheng, L. Zou, Soheila Kookalani
Year: 2020
Citation: Structural Design of Tall and Special Buildings, 29(5):e1698

Title: Introduction of Methodology for BIM & DSS
Authors: H. Alavi, Soheila Kookalani, F. Rahimian, N. Forcada
Year: 2024
Citation: Integrated Building Intelligence, pp. 31–42

Title: BIM-Based DSS for HVAC Root-Cause Detection
Authors: H. Alavi, Soheila Kookalani, F. Rahimian, N. Forcada
Year: 2024
Citation: Integrated Building Intelligence, pp. 43–57

Title: BIM-Based DSS for Building Condition Assessment
Authors: H. Alavi, Soheila Kookalani, F. Rahimian, N. Forcada
Year: 2024
Citation: Integrated Building Intelligence, pp. 59–78

Title: BIM-Based DSS for Enhancing Occupants’ Comfort
Authors: H. Alavi, Soheila Kookalani, F. Rahimian, N. Forcada
Year: 2024
Citation: Integrated Building Intelligence, pp. 79–99

Title: BIM-Based Augmented Reality for Facility Maintenance Management
Authors: H. Alavi, Soheila Kookalani, F. Rahimian, N. Forcada
Year: 2024
Citation: Integrated Building Intelligence, pp. 101–112

Title: GFRP Elastic Gridshell Structures: A Review of Methods, Research, Applications, Opportunities, and Challenges
Authors: Soheila Kookalani, Htay Htayaung
Year: 2023
Citation: 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 Algorithms
Authors: Soheila Kookalani, B. Cheng
Year: 2021
Citation: Journal of Civil Engineering and Materials Application

Title: Effect of Fluid Viscous Damper Parameters on the Seismic Performance
Authors: Soheila Kookalani, D. Shen
Year: 2020
Citation: Journal of Civil Engineering and Materials Application, 4(3)

Title: An Overview of the Particle Swarm Optimization Algorithms Applied to Optimization of Structures
Authors: Soheila Kookalani
Year: 2019
Citation: Civil Engineering Journal, 5(11):2336–2349

Title: Analysis and Optimal Location of Fluid Viscous Dampers for Multistory Irregular Steel Structures under Seismic Excitation
Authors: Soheila Kookalani, M. Daneshvaran, M. Noori
Year: 2019
Citation: Civil Engineering Journal, 5(7):1594–1607

Title: Optimal Viscous Damper Location for Multi-Story Steel Structures by Genetic Algorithm
Authors: Soheila Kookalani, S. Arabzadeh, M. Noori
Year: 2018
Citation: Civil Engineering Journal, 4(11):2590–2601

Title: Optimal Placement of Fluid Viscous Dampers in Steel Structures Subjected to Seismic Excitation by Genetic Algorithm
Authors: Soheila Kookalani, S. Arabzadeh, M. Noori
Year: 2018
Citation: 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.