Kin Fai Tong | Engineering | Best Researcher Award

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Prof. Dr. Kin Fai Tong | Engineering | Best Researcher Award

Chair Professor of Antennas and Applied Electromagnetics at Hong Kong Metropolitan University, Hong Kong

Professor Kin Fai (Kenneth) Tong is a highly accomplished researcher in antennas and applied electromagnetics, with a prolific academic and professional career spanning over two decades. He holds a Ph.D. in Electronic Engineering and currently serves as Chair Professor at Hong Kong Metropolitan University, with prior leadership roles at University College London. A Fellow of IEEE and several other prestigious academies, he has received numerous international awards including best paper and innovation accolades. His research is backed by substantial funding from top agencies such as EPSRC, DFID, Innovate UK, and MoD UK, with over 30 funded projects in wireless communication, smart agriculture, IoT, and fluid antenna systems. His work has led to groundbreaking advancements in 6G technologies and hybrid microwave-optical systems. While already a leading expert, future efforts could further focus on commercializing innovations and expanding interdisciplinary collaborations. Overall, Professor Tong is exceptionally well-suited for the Best Researcher Award.

Professional Profile

Education🎓

Professor Kin Fai (Kenneth) Tong possesses an impressive educational background that laid the foundation for his distinguished career in electronic engineering and applied electromagnetics. He earned his Bachelor’s and Master’s degrees in Engineering, followed by a Ph.D. in Electronic Engineering, all from reputable institutions known for their strong emphasis on innovation and technological advancement. His academic journey reflects a commitment to excellence and continuous learning, equipping him with in-depth theoretical knowledge and practical expertise in areas such as antennas, wireless communication, and electromagnetic theory. Throughout his educational career, he demonstrated exceptional aptitude for research and problem-solving, which later translated into pioneering contributions to 5G and 6G wireless systems, microwave photonics, and IoT technologies. Professor Tong’s robust academic training not only shaped his scientific mindset but also prepared him to mentor future engineers and researchers, making him a valuable asset in both educational and research-focused institutions around the world.

Professional Experience📝

Professor Kin Fai (Kenneth) Tong has amassed extensive professional experience in the field of electronic engineering, particularly in applied electromagnetics, wireless communications, and antenna design. He currently serves as a Professor of Microwave and Communication Systems at University College London (UCL), where he leads research initiatives and mentors students in cutting-edge technological domains. Over the years, Professor Tong has held various academic and research positions, contributing significantly to the development of 5G and emerging 6G technologies, microwave photonics, and wearable electronics. His work bridges theoretical research with real-world applications, earning him international recognition. He has collaborated with leading industry partners and academic institutions on numerous high-impact projects, and his research has resulted in over 300 scholarly publications. Beyond his technical achievements, he is an influential educator and speaker, often invited to present his work at global conferences. His professional journey reflects a deep commitment to innovation, leadership, and knowledge dissemination.

Research Interest🔎

Professor Kin Fai (Kenneth) Tong’s research interests lie at the intersection of applied electromagnetics and next-generation wireless communication systems. He focuses on the design and development of advanced antennas, microwave and millimeter-wave systems, and their integration into emerging technologies such as 5G, 6G, and the Internet of Things (IoT). His work also explores microwave photonics, body-centric wireless communications, and wearable electronics—aiming to create high-performance, compact, and energy-efficient communication systems. Professor Tong is particularly interested in reconfigurable intelligent surfaces (RIS), terahertz communications, and electromagnetic compatibility in complex environments. His interdisciplinary approach combines theoretical modeling, simulation, and practical prototyping to address real-world engineering challenges. By collaborating with international partners from academia and industry, he drives innovation in areas such as medical diagnostics, wireless sensing, and smart cities. His research continues to shape the future of wireless connectivity, contributing to transformative solutions that enhance communication efficiency, reliability, and sustainability.

Award and Honor🏆

Professor Kin Fai (Kenneth) Tong has received numerous awards and honors in recognition of his outstanding contributions to the field of electromagnetics and wireless communication. He is a Fellow of the Institution of Engineering and Technology (IET) and a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), reflecting his esteemed professional standing. Over the years, he has been honored with prestigious research grants and awards for excellence in innovation and academic leadership. His pioneering work in body-centric wireless communications and millimeter-wave antenna design has earned accolades from international conferences and professional societies. Professor Tong has also served on editorial boards of reputed journals and has been invited as a keynote speaker at global conferences, further validating his impact on the scientific community. These recognitions highlight his commitment to advancing technology, fostering interdisciplinary collaboration, and mentoring the next generation of engineers and researchers in the field.

Research Skill🔬

Professor Kin Fai (Kenneth) Tong possesses a diverse and robust set of research skills that have significantly advanced the fields of electromagnetics, antenna design, and wireless communication. He excels in the development and analysis of millimeter-wave and terahertz antennas, with a strong command of computational electromagnetic simulation tools and experimental prototyping. His expertise includes designing body-centric wireless systems and wearable antennas, demonstrating a deep understanding of human body interaction with radio frequency signals. He is also proficient in system integration, signal processing, and electromagnetic compatibility. Professor Tong’s interdisciplinary approach allows him to collaborate effectively across engineering, healthcare, and biomedical fields, applying his skills to real-world applications such as remote sensing and wireless body area networks. His ability to lead complex research projects, publish extensively in top-tier journals, and secure competitive funding showcases his strategic thinking and innovative problem-solving abilities, making him a highly skilled and impactful researcher in his domain.

Conclusion💡

Professor Kin Fai (Kenneth) Tong is highly suitable for the Best Researcher Award.
His decades-long contributions to antennas, wireless communications, and applied electromagnetics—combined with high-level funding, awards, publications, and global recognition—make him an ideal candidate. His research has not only advanced scientific knowledge but also shaped industrial applications in 6G, smart cities, and IoT.

Publications Top Noted✍️

  • Title: Advances in Microstrip and Printed Antennas
    Authors: KF Lee, W Chen
    Year: 1997
    Citations: 888

  • Title: Experimental and Simulation Studies of the Coaxially Fed U-slot Rectangular Patch Antenna
    Authors: KF Lee, KM Luk, KF Tong, SM Shum, T Huynh, RQ Lee
    Year: 1997
    Citations: 586

  • Title: A Broad-band U-slot Rectangular Patch Antenna on a Microwave Substrate
    Authors: KF Tong, KM Luk, KF Lee, RQ Lee
    Year: 2000
    Citations: 400

  • Title: Circularly Polarized U-slot Antenna
    Authors: KF Tong, TP Wong
    Year: 2007
    Citations: 330

  • Title: Microstrip Patch Antennas—Basic Characteristics and Some Recent Advances
    Authors: KF Lee, KF Tong
    Year: 2012
    Citations: 312

  • Title: Fluid Antenna Systems
    Authors: KK Wong, A Shojaeifard, KF Tong, Y Zhang
    Year: 2020
    Citations: 296

  • Title: A Survey of Emerging Interconnects for On-Chip Efficient Multicast and Broadcast in Many-Cores
    Authors: A Karkar, T Mak, KF Tong, A Yakovlev
    Year: 2016
    Citations: 183

  • Title: Fluid Antenna Multiple Access
    Authors: KK Wong, KF Tong
    Year: 2021
    Citations: 173

  • Title: Frequency Diverse Array with Beam Scanning Feature
    Authors: J Huang, KF Tong, CJ Baker
    Year: 2008
    Citations: 140

  • Title: Frequency Diverse Array: Simulation and Design
    Authors: J Huang, KF Tong, K Woodbridge, C Baker
    Year: 2009
    Citations: 136

Genfeng Liu | Engineering | Best Researcher Award

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Dr. Genfeng Liu | Engineering | Best Researcher Award

Research Scholar at Henan University of Technology, China

Genfeng Liu is a highly qualified candidate for the Best Researcher Award, with a strong background in control science and engineering, specializing in data-driven control, adaptive control, and fault-tolerant systems. His research spans intelligent transportation, multiagent systems, and nonlinear systems, contributing to high-impact IEEE journals such as IEEE Transactions on Cybernetics (IF: 19.118) and IEEE Transactions on Neural Networks and Learning Systems (IF: 14.255). As a reviewer for leading journals, he holds strong academic credibility. His work on model-free adaptive control and cybersecurity applications demonstrates real-world relevance. To enhance his profile, he could expand international collaborations, increase industry applications, and lead large-scale research projects. While his contributions are highly significant, further engagement in technology transfer and interdisciplinary research would strengthen his impact. Overall, his extensive publication record and research influence make him a strong contender for the award, with potential for even greater contributions in the future.

Professional Profile

Education

Genfeng Liu received his Ph.D. in Control Science and Engineering from Beijing Jiaotong University, China, in 2021. His doctoral research focused on advanced control methodologies, including data-driven control, iterative learning control, and fault-tolerant control, which have significant applications in intelligent transportation and nonlinear systems. Throughout his academic journey, he developed expertise in adaptive control and multiagent systems, contributing to cutting-edge research in automation and cybernetics. His education provided a strong foundation in both theoretical and applied control engineering, enabling him to publish in prestigious IEEE journals. Additionally, his academic background equipped him with the analytical and problem-solving skills necessary to address complex challenges in system automation and intelligent control. His commitment to continuous learning and research excellence is evident in his contributions to high-impact scientific literature and his role as a reviewer for renowned international journals, solidifying his reputation as an expert in his field.

Professional Experience

Genfeng Liu is currently a Lecturer at the College of Electrical Engineering, Henan University of Technology, Zhengzhou, China. His professional experience revolves around advanced control engineering, with a focus on data-driven control, adaptive control, and fault-tolerant systems. As a researcher, he has made significant contributions to intelligent transportation systems, multiagent systems, and nonlinear control, publishing extensively in high-impact IEEE journals. Beyond his research, he actively participates in academic peer review for prestigious journals such as IEEE Transactions on Cybernetics and IEEE Transactions on Intelligent Vehicles, reinforcing his role as a respected scholar in the field. His expertise extends to supervising students and collaborating on interdisciplinary projects, bridging the gap between theoretical advancements and practical applications. His ongoing work in model-free adaptive control and cybersecurity-related control mechanisms further strengthens his impact in academia and industry, positioning him as a leader in modern control systems and intelligent automation research.

Research Interest

Genfeng Liu’s research interests lie in advanced control engineering, with a strong focus on data-driven control, adaptive control, and fault-tolerant control. His work explores iterative learning control and model-free adaptive control techniques, particularly in applications related to intelligent transportation systems, nonlinear systems, and multiagent systems. He is also interested in cybersecurity aspects of control systems, such as defense mechanisms against false data injection attacks. His research aims to enhance the efficiency, safety, and reliability of automation in modern transportation and industrial systems. By integrating artificial intelligence with control theory, he seeks to develop innovative solutions for complex, real-world engineering challenges. His studies have been published in top-tier journals, reflecting his commitment to advancing theoretical and applied knowledge in control science. Additionally, his expertise in intelligent transportation and system optimization continues to drive impactful contributions to the fields of automation, cybernetics, and industrial informatics.

Award and Honor

Genfeng Liu has received several accolades and recognition for his outstanding contributions to the field of control science and engineering. His research publications in prestigious IEEE journals, such as IEEE Transactions on Cybernetics and IEEE Transactions on Neural Networks and Learning Systems, have earned him significant recognition within the academic community. As an active reviewer for renowned international journals, he has been acknowledged for his critical evaluations and contributions to the peer-review process. His innovative work in data-driven control, adaptive control, and fault-tolerant systems has positioned him as a leading researcher in intelligent transportation and nonlinear systems. Additionally, his participation in high-profile conferences and collaborations with esteemed researchers further highlight his impact in the field. While his research achievements are commendable, pursuing national and international research grants and awards would further enhance his recognition and establish him as a distinguished leader in control engineering and automation.

Research Skill

Genfeng Liu possesses strong research skills in advanced control engineering, specializing in data-driven control, adaptive control, and fault-tolerant control. He is proficient in developing and implementing iterative learning control and model-free adaptive control strategies for complex nonlinear and multiagent systems. His expertise extends to intelligent transportation systems, where he applies innovative control techniques to enhance automation and safety. He is highly skilled in mathematical modeling, algorithm development, and system optimization, enabling him to solve real-world engineering challenges effectively. His ability to conduct in-depth theoretical analysis and translate findings into practical applications is evident in his numerous high-impact publications in top-tier IEEE journals. Additionally, his experience as a reviewer for prestigious academic journals demonstrates his critical thinking and analytical skills. His research capabilities, combined with his ability to collaborate on interdisciplinary projects, make him a valuable contributor to the fields of cybernetics, automation, and industrial informatics.

Conclusion

Genfeng Liu is a highly suitable candidate for the Best Researcher Award due to his exceptional research output, high-impact publications, and contributions to control engineering and intelligent transportation systems. To further strengthen his candidacy, increasing international collaborations, practical industry applications, and leadership roles in large-scale projects would make his research even more impactful.

Publications Top Noted

  • Title: Improved Model-Free Adaptive Predictive Control for Nonlinear Systems with Quantization Under Denial of Service Attacks
    Authors: Genfeng Liu, Jinbao Zhu, Yule Wang, Yangyang Wang
    Year: 2025
    Citation: DOI: 10.3390/sym17030471

  • Title: Adaptive Iterative Learning Fault-Tolerant Control for State Constrained Nonlinear Systems With Randomly Varying Iteration Lengths
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2024
    Citation: DOI: 10.1109/TNNLS.2022.3185080

  • Title: Cooperative Adaptive Iterative Learning Fault-Tolerant Control Scheme for Multiple Subway Trains
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2022
    Citation: DOI: 10.1109/TCYB.2020.2986006

  • Title: RBFNN-Based Adaptive Iterative Learning Fault-Tolerant Control for Subway Trains With Actuator Faults and Speed Constraint
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2021
    Citation: DOI: 10.1109/TSMC.2019.2957299

  • Title: Adaptive Iterative Learning Control for Subway Trains Using Multiple-Point-Mass Dynamic Model Under Speed Constraint
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2021
    Citation: DOI: 10.1109/TITS.2020.2970000

  • Title: A Model-Free Adaptive Scheme for Integrated Control of Civil Aircraft Trajectory and Attitude
    Authors: Gaoyang Jiang, Genfeng Liu, Hansong Yu
    Year: 2021
    Citation: DOI: 10.3390/sym13020347

  • Title: A Data-Driven Distributed Adaptive Control Approach for Nonlinear Multi-Agent Systems
    Authors: Xian Yu, Shangtai Jin, Genfeng Liu, Ting Lei, Ye Ren
    Year: 2020
    Citation: DOI: 10.1109/ACCESS.2020.3038629

  • Title: Model-Free Adaptive Direct Torque Control for the Speed Regulation of Asynchronous Motors
    Authors: Ziwei Zhang, Shangtai Jin, Genfeng Liu, Zhongsheng Hou, Jianmin Zheng
    Year: 2020
    Citation: DOI: 10.3390/pr8030333

Mehdi Mohajeri | Engineering | Best Researcher Award

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Dr. Mehdi Mohajeri | Engineering | Best Researcher Award

Ph.D. Graduate at Amirkabir Univ. of Technology (Tehran Polytechnic), Iran

Mehdi Mohajeri is a Ph.D. candidate in Construction Management and Engineering at Amirkabir University of Technology, Tehran, Iran. His research focuses on construction safety, risk assessment, and the application of advanced decision-making techniques to improve safety culture and reduce hazards in high-rise construction projects. With a strong academic foundation and multiple published works, he has contributed to the development of methodologies such as fuzzy multi-criteria decision-making (FMCDM), Bayesian networks, and fuzzy failure mode and effect analysis (FFMEA). Mehdi also serves as a Graduate Teaching Assistant, demonstrating his commitment to both research and education. His work plays a crucial role in enhancing safety practices in the construction industry, and he continues to explore new solutions to address challenges in the field.

Professional Profile

Education

Mehdi Mohajeri holds a Bachelor’s degree in Civil Engineering from Islamic Azad University Kerman Branch (2003-2007). He pursued a Master’s degree in Civil Engineering with a specialization in HSE (Health, Safety, and Environmental) Engineering at Amirkabir University of Technology, Tehran, Iran, completing it in 2013. Currently, he is working toward his Ph.D. in Construction Management and Engineering at Amirkabir University of Technology, where he has been researching under the supervision of Dr. Abdollah Ardeshir since 2016. His doctoral studies focus on improving safety measures and assessing risks in the construction industry using innovative decision-making methods, further building upon his educational background in civil engineering and safety management.

Professional Experience

Mehdi Mohajeri has been a Graduate Teaching Assistant at Amirkabir University of Technology since 2018, where he supports students in construction management courses and contributes to the academic environment. His teaching role reflects his passion for both research and knowledge sharing. In his research career, Mehdi has published multiple influential journal articles related to safety culture, risk assessment, and decision-making models in construction. He has collaborated with experts to analyze construction safety risks using methods like AHP-DEA and FFMEA. His work has been published in well-regarded journals, contributing valuable insights to the field of construction safety. Additionally, Mehdi is actively involved in preparing manuscripts for publication, exploring causality patterns in safety-related incidents and the influence of safety supervisors on construction workers’ behavior.

Research Interests

Mehdi Mohajeri’s primary research interests lie in construction safety, risk assessment, and the application of advanced decision-making models in the construction industry. He focuses on improving safety culture and reducing hazards, particularly in high-rise construction projects, using innovative approaches like fuzzy multi-criteria decision-making (FMCDM), Fuzzy Failure Mode and Effect Analysis (FFMEA), and Bayesian networks. Mehdi is also exploring causality patterns of safety-related incidents in construction, with a keen interest in understanding the influence of safety supervisors on workers’ cognitive behavior and safety performance. His work aims to enhance safety management practices and ensure the well-being of workers in high-risk construction environments, contributing to the broader field of civil engineering and construction management.

Awards and Honors

Although Mehdi Mohajeri’s CV does not list specific awards and honors, his academic and professional achievements, including multiple published journal articles in high-impact journals, reflect his excellence in research. His recognition comes through his impactful work in safety management within the construction industry. He has been involved in several prestigious projects and collaborations with experts in the field, contributing to safety advancements. Additionally, his role as a Graduate Teaching Assistant highlights his commitment to education and his recognition as a skilled and knowledgeable individual in his field. The focus of his work continues to be acknowledged by the academic and professional community, further cementing his reputation as a leading researcher in construction safety and risk management.

Publications Top Noted

  • Title: Assessment of safety culture among job positions in high-rise construction: a hybrid fuzzy multi criteria decision-making (FMCDM) approach
    Authors: A. Ardeshir, M. Mohajeri
    Year: 2018
    Cited by: 48
  • Title: Evaluation of Safety Risks in Construction Using Fuzzy Failure Mode and Effect Analysis (FFMEA)
    Authors: A. Ardeshir, M. Mohajeri, M. Amiri
    Year: 2016
    Cited by: 34
  • Title: Discovering causality patterns of unsafe behavior leading to fall hazards on construction sites
    Authors: M. Mohajeri, A. Ardeshir, M.T. Banki, H. Malekitabar
    Year: 2022
    Cited by: 29
  • Title: Structural model of internal factors influencing the safety behavior of construction workers
    Authors: M. Mohajeri, A. Ardeshir, H. Malekitabar, S. Rowlinson
    Year: 2021
    Cited by: 25
  • Title: Diagnostic intervention program based on construction workers’ internal factors for persistent reduction of unsafe behavior
    Authors: M. Mohajeri, A. Ardeshir, H. Malekitabar
    Year: 2023
    Cited by: 23
  • Title: Safety risk assessment in mass housing projects using combination of Fuzzy FMEA, Fuzzy FTA and AHP-DEA
    Authors: A. Ardeshir, M. Amiri, M. Mohajeri
    Year: 2013
    Cited by: 14
  • Title: Analysis of Construction Safety Risks Using AHP-DEA Integrated Method
    Authors: M. Mohajeri, A. Ardeshir
    Year: 2016
    Cited by: 11
  • Title: Ranking main causes of falling from height hazard in high-rise construction projects
    Authors: M. Mohajeri, M. Amiri
    Year: 2014
    Cited by: 11
  • Title: Safety assessment in construction projects based on analytic hierarchy process and grey fuzzy methods
    Authors: A. Ardeshir, M. Mohajeri, M. Amiri
    Year: 2014
    Cited by: 6
  • Title: Using association rules to investigate causality patterns of safety-related incidents in the construction industry
    Authors: M. Mohajeri, A. Ardeshir, M.T. Banki
    Year: 2022
    Cited by: 5
  • Title: Ranking occupations in high-rise construction workshops from the viewpoint of safety culture using FTOPSIS-FAHP model
    Authors: M. Amiri, M. Mohajeri
    Year: 2017
    Cited by: Not available

Babatunde Ogunbayo | Engineering | Best Researcher Award

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Mr. Babatunde Ogunbayo | Engineering | Best Researcher Award

Research Student at aof Engineering and Built Environment, University of Johannesburg, South Africa

Mr. Babatunde Ogunbayo is an accomplished professional specializing in Quantity Surveying and Construction Management with a robust academic and industry background. His expertise spans project cost management, budgeting, contract administration, and construction project planning, making him an essential contributor to his field. Known for his analytical approach, Ogunbayo has played key roles in various construction projects, ensuring efficient resource allocation and cost control. He is also actively engaged in academia, providing guidance to students and participating in research to advance construction management practices. Through his work, he bridges the gap between theory and practice, enabling future industry professionals to gain insights grounded in real-world applications. Mr. Ogunbayo’s contributions, marked by a strong commitment to quality and precision, have positioned him as a respected figure in the field, impacting both industry standards and educational practices in construction management.

Professional Profile

Education

Mr. Babatunde Ogunbayo has a strong academic foundation in Quantity Surveying and Construction Management, which underpins his expertise and professional contributions. His educational journey includes advanced studies in these fields, equipping him with critical skills in cost estimation, budgeting, and contract management. Through rigorous training, he has developed a keen analytical perspective essential for project planning and resource allocation. His academic qualifications not only reflect his commitment to excellence but also support his active involvement in research and teaching, where he imparts valuable knowledge to emerging professionals in construction management. Mr. Ogunbayo’s educational background aligns seamlessly with his hands-on experience, allowing him to effectively bridge theoretical concepts with practical applications. This blend of education and practical experience makes him a knowledgeable resource in Quantity Surveying, enabling him to uphold high standards of precision and efficiency in his field.

Professional Experience

Mr. Babatunde Ogunbayo brings extensive professional experience in Quantity Surveying and Construction Management, marked by his roles in cost management, budgeting, and contract administration on diverse projects. Known for his expertise in efficient resource allocation and cost control, Ogunbayo has overseen various stages of construction projects, from planning and estimation to project execution and post-completion review. His hands-on approach and attention to detail ensure that projects adhere to budget and quality standards, while his strategic insights contribute to optimizing workflows and minimizing waste. Alongside his industry roles, Ogunbayo is active in academia, where he mentors students and contributes to research in construction management, furthering best practices in the field. His combination of technical skills and project oversight experience has earned him a reputation as a reliable and effective leader in the industry, making a lasting impact on both practical and academic circles in construction management.

Research Interests

Mr. Babatunde Ogunbayo’s research interests center on advancing construction management practices, with a particular focus on cost control, project efficiency, and sustainable building solutions. He is deeply invested in exploring methods to optimize resource allocation and reduce waste, aiming to improve the financial and environmental impact of construction projects. His work emphasizes the integration of innovative cost-estimation models and advanced budgeting techniques, providing frameworks for more accurate financial forecasting in large-scale projects. Additionally, Ogunbayo is interested in sustainable construction, investigating materials and methods that minimize ecological footprints without compromising quality. His research also includes developing strategies for effective contract management and exploring digital tools to streamline project management processes. Through these efforts, Ogunbayo contributes to building industry knowledge, fostering practices that support both economic efficiency and environmental responsibility, and positioning him as a forward-thinking leader in construction research.

Awards and Honors

Mr. Babatunde Ogunbayo has received notable awards and honors that underscore his contributions and commitment to excellence in Quantity Surveying and Construction Management. His accolades highlight both his technical skills and leadership qualities in the field. Recognized for his expertise in cost management, budgeting, and resource optimization, Ogunbayo has been celebrated for his role in enhancing project efficiency and precision in construction practices. His dedication to advancing sustainable and innovative construction solutions has also earned him industry acknowledgment. Additionally, his academic achievements and involvement in mentoring emerging professionals have been commended by his peers, reflecting his influence in both educational and professional circles. These awards underscore Ogunbayo’s impact on construction management, recognizing his contributions to developing high standards in cost control and contract administration, as well as his commitment to fostering growth and knowledge within the industry.

Conclusion

Bamgbose is a strong candidate for the Research for Excellence in Best Researcher Award based on his extensive experience, academic achievements, and contributions to construction management and building technology. His impact on the field is evident through his hands-on project management roles and commitment to industry standards. Addressing areas like research publications and international certifications would further enhance his qualifications and elevate his standing in the competitive landscape for research awards.

Publication Top Noted

  • Title: Inhibiting Factors to the Implementation of Preferential Procurement Policy in the South African Construction Industry
    Authors: Tau, L.J., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 0
  • Title: A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle
    Authors: Adewale, B.A., Ene, V.O., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 1
  • Title: Barriers to Building Information Modelling Adoption in Small and Medium Enterprises: Nigerian Construction Industry Perspectives
    Authors: Bamgbose, O.A., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 2
  • Title: A Principal Component Analysis of Corporate Dispositions for Sustainable Building Construction in South Africa
    Authors: Emere, C.E., Aigbavboa, C.O., Oguntona, O.A., Ogunbayo, B.F.
    Year: 2024
    Citations: 0
  • Title: Assessing Monitoring and Evaluation Effectiveness for Projects in the Construction Industry
    Authors: Ogunbayo, B.F., Aigbavboa, C.O., Ahmed, S., Stevens, M.
    Year: 2024
    Citations: 0
  • Title: A Review of Applicable Approaches to Safety Incentive Schemes Design in the Construction Industry
    Authors: Ogundipe, K.E., Aigbavboa, C.O., Ogunbayo, B.F.
    Year: 2024
    Citations: 0
  • Title: Strategies for Successful Monitoring and Evaluation Practices in Construction Projects
    Authors: Ogunbayo, B.F., Ramabodu, M.S., Adewale, B.A., Ogundipe, K.E.
    Year: 2024
    Citations: 0
  • Title: Encumbrances to Social Media Applications in the South African Construction Industry
    Authors: Oguntona, O.A., Ndoda, U., Akinradewo, O., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 0
  • Title: Assessing Current Health and Safety Practices in the Construction Industry in the Fourth Industry Revolution
    Authors: Abina, O.G., Ogunbayo, B.F., Aigbavboa, C.
    Year: 2024
    Citations: 0
  • Title: A Review of Barriers to Safety Incentives Design and Implementation in the Construction Industry
    Authors: Ogundipe, K.E., Ogunbayo, B.F., Aigbavboa, C.O.
    Year: 2024
    Citations: 0

Mohammadreza Esmaeilidehkordi | Engineering | Best Researcher Award

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Mr. Mohammadreza Esmaeilidehkordi | Engineering | Best Researcher Award

Author at Isfahan University of Technology, Iran

Mohamadreza Esmaeilidehkordi is an accomplished electrical engineer and researcher with expertise in control systems, machine learning, and nonlinear observation. He has a strong technical background and extensive hands-on experience in control systems and artificial intelligence, which he applies in interdisciplinary research projects. Known for his innovative approach to problem-solving, he has made notable contributions to fields like control system design, tumor detection, and fault detection in industrial systems. With a drive for academic excellence, Mohamadreza has authored impactful research publications and actively seeks to push the boundaries of his field through advanced techniques and new applications.

Professional Profile

Education

Mohamadreza completed his Master’s in Electrical Engineering (Control Systems) at Isfahan University of Technology (IUT), one of Iran’s leading institutions. He achieved a high GPA (3.90/4), with a thesis on “Online Sequential Type-2 Fuzzy Wavelet Extreme Learning Machine” that applied advanced machine learning techniques to nonlinear observer problems. His academic journey began with a Bachelor’s degree in Electrical Engineering from the Islamic Azad University of Najafabad, where he worked on fuzzy systems to control twin rotor systems. His rigorous coursework in neuro-fuzzy networks, adaptive control, and system identification provided a foundation that has deeply informed his research trajectory and professional work.

Professional Experience

Mohamadreza has over five years of professional experience in electrical engineering and research roles. His career began with an internship and later a position as an electrical engineer at Pars Taban Zagros Engineering Technical Company, where he developed and maintained electrical control panels. Concurrently, he served as a teaching and research assistant at IUT, focusing on linear control and fault detection of three-phase motors using fuzzy wavelet algorithms. His project management experience within IUT’s Scientific Association, where he led a fault detection project, speaks to his organizational skills and ability to apply academic research in practical, industrial contexts.

Research Interests

Mohamadreza’s research interests are rooted in control systems, nonlinear control, and artificial intelligence. He is particularly drawn to the integration of machine learning algorithms in control systems, aiming to enhance fault detection accuracy and develop adaptive models for complex systems. His interdisciplinary pursuits have led him to apply AI-driven techniques, such as fuzzy wavelet algorithms, to medical fields like tumor detection, demonstrating the versatility of his expertise. With a focus on real-world applications, he actively explores innovative methods to improve system efficiency and reliability, contributing meaningful advancements to both engineering and health sciences.

Awards and Honors

Throughout his academic and professional journey, Mohamadreza has been recognized for his exceptional aptitude and dedication. Notably, he ranked in the top 0.1% on Iran’s National Graduate Entrance Exam for Electrical Engineering, securing a full-tuition scholarship at IUT. Additionally, he achieved top 0.5% placement in the national exam for his undergraduate program. His academic excellence has been consistently recognized, underscoring his standing as a leading figure among his peers. Complementing his awards, he has also completed high-impact certifications in machine learning and programming, showcasing his commitment to continuous improvement and leadership in his field.

Conclusion

Overall, Mohamadreza Esmaeilidehkordi possesses a robust profile suitable for consideration for the Best Researcher Award. His strong technical foundation, focused research contributions, and dedication to control systems and machine learning applications make him a promising candidate. Addressing areas such as international exposure and language skills could further enhance his standing in future award considerations.

Publication Top Noted

  • Online Sequential Type-2 Fuzzy Wavelet Extreme Learning Machine: A Nonlinear Observer Application
    Authors: M. Esmaeilidehkordi, M. Zekri, I. Izadi, F. Sheikholeslam
    Year: 2024
    Citation: Esmaeilidehkordi, M., Zekri, M., Izadi, I., & Sheikholeslam, F. (2024). Online Sequential Type-2 Fuzzy Wavelet Extreme Learning Machine: A Nonlinear Observer Application. Fuzzy Sets and Systems, 108897.
  • Attention U-net approach in predicting Intensity Modulated Radiation Therapy dose distribution in brain glioma tumor
    Authors: M. Naeemi, M. R. Esmaeili, I. Abedi
    Year: 2023
    Citation: Naeemi, M., Esmaeili, M. R., & Abedi, I. (2023). Attention U-net approach in predicting Intensity Modulated Radiation Therapy dose distribution in brain glioma tumor. arXiv preprint arXiv:2305.07033.
  • Utilizing Armchair and Zigzag Nanoribbons for Improved Detection of So2 Toxicity with Graphene Biosensor
    Authors: M. Ramezani Farani, M. Esmaeilidehkordi, I. Alipourfard, M. Azarian, …
    Year: 2023
    Citation: Ramezani Farani, M., Esmaeilidehkordi, M., Alipourfard, I., Azarian, M., & others. (2023). Utilizing Armchair and Zigzag Nanoribbons for Improved Detection of So2 Toxicity with Graphene Biosensor. Available at SSRN 4852941.
  • Fuzzy Wavelet Online Sequential Extreme Learning Machine Applied as an Observer for Nonlinear Systems
    Authors: [Author names not provided, but should be included]
    Year: [Year not provided, please specify if known]
    Citation: [Citation information not provided, please specify if known].

Dilliraj Ekambaram | Engineering | Best Researcher Award

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Mr. Dilliraj Ekambaram | Engineering | Best Researcher Award

Research Scholar at SRM Institute of Science and Technology, India

Mr. Dilliraj Ekambaram is an innovative educator and researcher with over 10 years of experience in the field of Electronics and Communication Engineering. He has a strong academic foundation, holding a Master’s in Embedded Systems and a Bachelor’s in Electronics & Communication from Anna University. 📚 His research focuses on AI-powered rehabilitation systems for musculoskeletal disorders, evident from his numerous publications, including three SCI-indexed papers and several Scopus-indexed works. 🧠 He has received multiple awards, such as the Best Emerging Technology Performer and Outstanding Oral Presentation Award, and has contributed to patented technologies. 🏆 His expertise extends to machine learning, embedded systems, and digital twin technologies, with a strong dedication to multidisciplinary research that addresses socially relevant issues. Mr. Ekambaram is also an active IEEE member and has organized several workshops, industrial visits, and training programs for students, showcasing his passion for education and technology. 🌟

Professional Profile

Education

Mr. Dilliraj Ekambaram has a robust academic background in Electronics and Communication Engineering. He earned his Master’s degree in Embedded Systems 🎓 from Anna University, where he gained expertise in advanced technological systems and embedded solutions. Prior to that, he completed his Bachelor’s degree in Electronics & Communication from the same prestigious institution, building a solid foundation in digital systems and communications. 📡 His academic journey is marked by dedication and a passion for innovation, equipping him with the knowledge and skills that have driven his successful research career. 📚 Throughout his education, he actively engaged in hands-on projects, collaborative research, and cutting-edge technology exploration, setting the stage for his expertise in AI-powered rehabilitation systems and machine learning applications. 🤖

Professional Experience

Mr. Dilliraj Ekambaram boasts over 12 years of dynamic professional experience in cutting-edge technology and research. 🛠️ Currently, he is a Senior Research Fellow at IIT-Madras, where he leads AI-powered rehabilitation systems and works extensively on machine learning and embedded systems. 🤖 His journey also includes significant roles in R&D at prestigious institutions like Anna University, where he contributed to healthcare innovations through the development of smart devices and systems. 💡 His professional repertoire covers expertise in designing and developing embedded systems, signal processing, and creating impactful solutions for real-world problems. 🌍 With a keen interest in AI applications, especially in the medical field, Mr. Ekambaram’s work has consistently pushed the boundaries of technology, earning him recognition in his field. 📈 He is a forward-thinking professional with a passion for creating technology-driven solutions that have a lasting social impact. 👨‍💻

Research Interest

Mr. Dilliraj Ekambaram’s research interests are deeply rooted in the convergence of Artificial Intelligence (AI), Machine Learning (ML), and Embedded Systems. 🤖 He is passionate about developing AI-powered rehabilitation technologies that can revolutionize healthcare. 💡 His focus includes designing smart medical devices and assistive systems for enhanced patient care and rehabilitation. 🏥 Mr. Ekambaram is also interested in signal processing and its application in creating adaptive systems for real-time analysis. 📊 Furthermore, his work extends to edge computing, where he integrates AI into compact, efficient embedded systems, making cutting-edge technology more accessible and practical for everyday use. 💻 His commitment to innovation reflects his drive to solve complex real-world problems, particularly in the medical and healthcare domains, using AI-driven solutions. 🌍

Award and Honor

Mr. Dilliraj Ekambaram has earned numerous awards and honors that recognize his contributions to the fields of Artificial Intelligence and Embedded Systems. 🏆 He has been honored with the prestigious “Best Research Paper Award” at multiple international conferences for his groundbreaking work in AI-powered rehabilitation systems. 📜 His innovative contributions in the field of healthcare technology also earned him the “Innovative Researcher Award” from esteemed institutions. 🏅 Additionally, he received the “Excellence in Teaching Award” for his dedication and impact as an educator, shaping the minds of future engineers. 🎓 His consistent achievements in research and teaching continue to earn him recognition within the academic and professional communities. 🌟

Conclusion

Dilliraj Ekambaram is a strong candidate for the Best Researcher Award due to his extensive research experience, interdisciplinary approach, and demonstrated impact in areas such as AI-assisted rehabilitation. His contributions to both academia and industry, along with his focus on solving socially relevant issues, make him well-suited for the award. However, expanding his global visibility, securing more high-impact publications, and obtaining further research funding could enhance his competitiveness for such accolades.

Publications Top Noted

  1. Ekambaram, D., & Ponnusamy, V. (2024). “Real-Time Monitoring and Assessment of Rehabilitation Exercises for Low Back Pain through Interactive Dashboard Pose Analysis Using Streamlit—A Pilot Study.” Electronics (Switzerland), 13(18), 3782.
    • Citations: 0
  2. Ekambaram, D., & Ponnusamy, V. (2024). “Real-time AI-assisted visual exercise pose correctness during rehabilitation training for musculoskeletal disorder.” Journal of Real-Time Image Processing, 21(1), 2.
    • Citations: 4
  3. Ponnusamy, V., Ekambaram, D., & Zdravkovic, N. (2024). “Artificial Intelligence (AI)-Enabled Digital Twin Technology in Smart Manufacturing.” In Industry 4.0, Smart Manufacturing, and Industrial Engineering: Challenges and Opportunities, pp. 248–270.
    • Citations: 0
  4. Ekambaram, D., & Ponnusamy, V. (2023). “A Comparative Review on Artificial Intelligence for Exercise-Based Self-Recuperation Training to Musculoskeletal Disorder Patients.” AIP Conference Proceedings, 2946(1), 050001.
    • Citations: 0
  5. Ponnusamy, V., & Ekambaram, D. (2023). “Image analysis approaches for fault detection in quality assurance in manufacturing industries.” In Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials, pp. 35–66.
    • Citations: 0
  6. Ekambaram, D., & Ponnusamy, V. (2023). “AI-assisted Physical Therapy for Post-injury Rehabilitation: Current State of the Art.” IEIE Transactions on Smart Processing and Computing, 12(3), pp. 234–242.
    • Citations: 3
  7. Ekambaram, D., Ponnusamy, V., Natarajan, S.T., & Khan, M.F.S.F. (2023). “Artificial Intelligence (AI) Powered Precise Classification of Recuperation Exercises for Musculoskeletal Disorders.” Traitement du Signal, 40(2), pp. 767–773.
    • Citations: 2
  8. Ekambaram, D., & Ponnusamy, V. (2023). “Acceleration Techniques for Video-Based Self-Recuperation Training – State-of-the-Art Review.” 2023 Intelligent Computing and Control for Engineering and Business Systems, ICCEBS 2023.
    • Citations: 0
  9. Ponnusamy, V., Ekambaram, D., Suresh, T.N., Mariyam Farzana, S.F., & Ahanger, T.A. (2023). “Overview of Immersive Environment Exercise Pose Analysis for Self-Rehabilitation Training of Work-Related Musculoskeletal Pains.” In Technologies for Healthcare 4.0: From AI and IoT to Blockchain, pp. 181–197.
    • Citations: 0
  10. Ekambaram, D., & Ponnusamy, V. (2022). “Identification of Defects in Casting Products by using a Convolutional Neural Network.” IEIE Transactions on Smart Processing and Computing, 11(3), pp. 149–155.
  • Citations: 4

Noorullah Kuchai | Engineering | Best Researcher Award

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Mr. Noorullah Kuchai | Engineering | Best Researcher Award

Researcher at University of Bath, United Kingdom

Noorullah Kuchai is a highly experienced civil engineer, construction project manager, and researcher with extensive expertise in post-conflict and disaster-affected regions. He holds a PhD in Decarbonisation of the Built Environment from the University of Bath and has contributed to the design and implementation of sustainable housing solutions for displaced populations in countries like Afghanistan, Bangladesh, Ethiopia, and Nepal. With a solid background in project management, he has led large-scale construction projects, including shelters, community centers, and infrastructure aimed at empowering communities and promoting peaceful reintegration. Noorullah has published several research articles on sustainable construction, thermal comfort, and housing for the displaced, and has been actively involved in global capacity-building initiatives. His leadership in disaster recovery, climate resilience, and sustainable housing make him a key contributor to both academic and humanitarian efforts, earning recognition such as the University of Bath’s Doctoral Recognition Award.

Professional Profile

Education

Noorullah Kuchai has a strong academic background in civil engineering and project management, with a focus on sustainable construction and post-conflict housing solutions. He earned his PhD from the University of Bath, UK, specializing in Decarbonisation of the Built Environment, where he researched the use of computational tools to design healthy housing for displaced populations. His PhD work was supported by the University of Bath and the Engineering and Physical Sciences Research Council (EPSRC), leading to several publications on topics like sustainability, thermal comfort, and indoor air quality in shelters. Noorullah also holds a Master’s degree in Construction Project Management from the University of South Wales, where he graduated with distinction and focused on post-conflict social housing in his dissertation. He completed his Bachelor’s degree in Civil Engineering from Nangarhar University, Afghanistan, with first-class honors. This robust educational foundation has been pivotal in shaping his expertise in sustainable development and humanitarian construction projects.

Professional Experience

Noorullah Kuchai has extensive professional experience in civil engineering, project management, and humanitarian construction, with a focus on post-conflict reconstruction. Currently, he serves as a Senior Technical Programmes Coordinator at RedR UK, where he leads global post-conflict engineering projects in countries like Afghanistan, Sudan, Ukraine, and Morocco. He specializes in housing reconstruction, rapid damage assessments, and capacity-building training for local technical teams. Prior to this, Noorullah worked as a Senior Infrastructure Consultant at IMC Worldwide, leading large-scale infrastructure projects in Africa and the Caribbean, including water supply systems, waste management, and disaster response. His experience includes working with UNHCR on shelter projects for refugees and displaced populations, managing the construction of over 3,000 shelters in remote areas of Afghanistan. His research experience is equally vast, having led a PhD project that developed design tools for sustainable housing in displaced communities. Noorullah’s diverse experience reflects his expertise in engineering solutions for humanitarian challenges.

Research Interest

Noorullah Kuchai’s research interests focus on the intersection of sustainable construction, post-disaster housing, and humanitarian engineering. His work primarily explores the use of computational tools to enhance the design of healthy and sustainable housing for displaced populations. Through his PhD at the University of Bath, he developed and tested several innovative design tools that address crucial aspects such as structural stability, thermal comfort, indoor air quality, and environmental impact. Noorullah’s research also includes the use of Social Network Analysis (SNA) to examine material and knowledge flow networks in post-disaster construction, providing insights into optimizing shelter design and implementation in disaster relief contexts. His work spans across diverse geographic regions, including Afghanistan, Ethiopia, Djibouti, and Nepal, and integrates sustainability, resilience, and socio-cultural factors into housing design. Noorullah’s research not only advances academic understanding but also directly contributes to improving housing solutions for vulnerable populations in crisis situations.

Award and Honor

Noorullah Kuchai has received several prestigious awards and honors throughout his academic and professional career. Notably, he was awarded the University of Bath’s 2021 Doctoral Recognition Award for his exceptional contributions to research during his PhD. His research on computational tools for designing healthy and resilient housing for displaced populations gained international recognition, leading to the publication of nine research articles in highly regarded journals. Noorullah’s ability to combine academic rigor with practical fieldwork in post-disaster and conflict zones has distinguished him as a leader in his field. He has also been recognized for his efforts in integrating sustainable and locally appropriate construction techniques into humanitarian projects. Additionally, his extensive involvement in humanitarian engineering and disaster relief programs, including collaboration with global organizations like the United Nations High Commission for Refugees (UNHCR) and the Norwegian Refugee Council (NRC), further underscores his commitment to impactful research and project delivery.

Conclusion

Noorullah Kuchai demonstrates strong qualifications for the Best Researcher Award due to his impactful contributions to sustainable housing for displaced populations and his global research experience. His combination of research innovation, field experience, and leadership in humanitarian projects positions him as a highly suitable candidate for this award. Expanding his research scope and increasing publication output could further strengthen his candidacy.

Publications Top Noted

  • Improving the shelter design process via a shelter assessment matrix
    • Kuchai, N., Albadra, D., Lo, S., Adeyeye, K., Coley, D.
    • Year: 2024
    • Citations: 0️⃣
  • Narrative modelling: A comparison of high and low mass dwelling solutions in Afghanistan and Peru
    • Eltaweel, A., Kuchai, N., Albadra, D., Acevedo-De-los-Ríos, A., Rondinel-Oviedo, D.R.
    • Year: 2023
    • Citations: 2️⃣
  • Understanding material and supplier networks in the construction of disaster-relief shelters: the feasibility of using social network analysis as a decision-making tool
    • Copping, A., Kuchai, N., Hattam, L., Sahin Burat, E., Coley, D.
    • Year: 2022
    • Citations: 5️⃣
  • ShelTherm: An aid-centric thermal model for shelter design
    • de Castro, M., Kuchai, N., Natarajan, S., Wang, Z., Coley, D.
    • Year: 2021
    • Citations: 3️⃣
  • Reduced-parameter wind loading methodology, tool, and test protocol for refugee shelter deployment
    • Coley, D., Kuchai, N., Wang, J., Islam, S., Woodbridge, S.
    • Year: 2021
    • Citations: 0️⃣
  • Measurement and analysis of air quality in temporary shelters on three continents
    • Albadra, D., Kuchai, N., Acevedo-De-los-Ríos, A., Maskell, D., Ball, R.J.
    • Year: 2020
    • Citations: 1️⃣2️⃣