Seyed Ali Ekrami Kakhki | Civil Engineering | Research Excellence Award

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Dr. Seyed Ali Ekrami Kakhki | Civil Engineering | Research Excellence Award

Semnan University | Iran

Dr. Seyed Ali Ekrami Kakhki, a distinguished Civil Engineering scholar at Semnan University, specializes in structural engineering with a focus on reinforced concrete structures and progressive collapse analysis. He earned his Ph.D. in Civil Engineering – Structural Engineering from Azad University of Semnan, following an M.Sc. in Structural Engineering from Tafresh State University and a B.Sc. from Islamic Azad University, Taft. Dr. Ekrami Kakhki has led and supervised major civil engineering projects, including urban metro construction, rural road development, and structural strengthening of residential and institutional buildings, demonstrating a combination of technical expertise and leadership in project management. His research centers on the progressive collapse of reinforced concrete frames, incorporating soil-structure interaction and sensitivity analysis to enhance structural resilience. He has published multiple peer-reviewed articles in high-impact JCR Q2 journals such as the International Journal of Concrete Structures and Materials and contributed to the Journal of Structural and Construction Engineering, advancing the understanding of structural stability under critical load conditions. Recognized for his academic excellence and leadership, Dr. Ekrami Kakhki actively contributes to the civil engineering community through editorial roles, peer review, and collaborative research, reflecting a sustained commitment to innovation and scholarly impact in structural engineering.

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Top 5 Featured Publications

 


Numerical Investigation of the Progressive Collapse of RC Wall-Frame Structures

– International Journal of Concrete Structures and Materials, 2023


Evaluation of Progressive Collapse of RC Frames Based on Sensitivity Index

– International Journal of Concrete Structures and Materials, 2022


Analysis of Electrical Engineering Systems

– Journal of Electrical Engineering, 2016


Perovskite-Type LaFeO3 & LaFeO3-CNTs Nanocrystals for Methanol Oxidation

– Published under Springer (Chemistry/Nanocatalysts)

Sayyid Ali Banihashemi | Engineering | Editorial Board Member

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Assist. Prof. Dr. Sayyid Ali Banihashemi | Engineering | Editorial Board Member

Faculty Member | Payame Noor University | Iran

Assist. Prof. Dr. Sayyid Ali Banihashemi, Associate Professor in the Department of Industrial Engineering at Payame Noor University, is a recognized scholar specializing in project scheduling, data envelopment analysis, supply chain management, and organizational agility. He holds advanced degrees in industrial engineering with a concentration in operations research and performance evaluation, complemented by rigorous training in quantitative decision-making. His professional experience includes leading academic programs, supervising research initiatives, and contributing to major analytical and optimization projects that support organizational and operational improvement. Dr. Banihashemi’s research portfolio encompasses influential publications, high-impact citations, and methodological advancements that have shaped contemporary practices in project planning efficiency, productivity assessment, and supply chain performance. His scholarly contributions are further reflected in editorial responsibilities for reputable journals, memberships in distinguished professional societies, and certifications in advanced analytical methods. Widely cited and respected in his field, he has earned multiple recognitions for research excellence, academic service, and contributions to the industrial engineering community, establishing him as a dedicated leader committed to advancing theory and practice in operations and performance management.

Profiles: Google Scholar

Featured Publications

1. Dahmardeh, N., & Banihashemi, S. A. (2010). Organizational agility and agile manufacturing. European Journal of Economics, Finance and Administrative Sciences, 27, 178–184.

2. Banihashemi, S. A. (2011). The role of communication to improve organizational process. European Journal of Humanities and Social Sciences, 1(1), 13–24.

3. Banihashemi, S. A., Khalilzadeh, M., Shahraki, A., Malkhalifeh, M. R. M., & others. (2020). Optimization of environmental impacts of construction projects: A time–cost–quality trade-off approach. International Journal of Environmental Science and Technology, 1–16.

4. Banihashemi, S. A., & Khalilzadeh, M. (2021). Time-cost-quality–environmental impact trade-off resource-constrained project scheduling problem with DEA approach. Engineering, Construction and Architectural Management, 28(7), 1979–2004.

5. Banihashemi, S. A., Khalilzadeh, M., Antucheviciene, J., & Edalatpanah, S. A. (2023). Identifying and prioritizing the challenges and obstacles of green supply chain management in the construction industry using the fuzzy BWM method. Buildings, 13(1), 38.

Dr. Sayyid Ali Banihashemi’s work advances scientific and industrial practice by integrating optimization, sustainability, and performance evaluation to improve project delivery and supply chain systems. His research supports data-driven decision-making that enhances organizational efficiency, reduces environmental impacts, and strengthens the resilience and agility of modern industries.

Selcuk Comlekci | Bioengineering | Outstanding Scientist Award

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Prof. Selcuk Comlekci | Bioengineering | Outstanding Scientist Award

Professor | Suleyman Demirel University | Turkey

Assoc. Prof. Dr. Selçuk Çömlekçi is a distinguished faculty member at Süleyman Demirel University, Faculty of Engineering and Architecture, Department of Electronics and Communication Engineering in Isparta, Turkey. He holds a Ph.D. in Electrical and Electronics Engineering from Sakarya University, where he specialized in advanced electrical, electronic, and communication systems. With extensive academic and professional experience, he has served in various academic roles, including lecturer, assistant professor, and associate professor, contributing significantly to research, teaching, and innovation. His research expertise spans biomedical engineering, biophysics, electromagnetic and magnetic fields, microwave circuits, optoelectronic materials and devices, industrial and hazardous waste management, communication and control engineering, artificial intelligence, and fuzzy logic systems. Dr. Çömlekçi has participated in numerous national research projects focusing on areas such as wireless communication systems, nano-fiber production through electrospinning, and the development of electromagnetic shielding materials. His scientific work has contributed to advancements in biomedical signal processing, RF applications, and interdisciplinary engineering research. A respected academic and researcher, he has received recognition for his contributions to science and education and is actively involved in professional and scholarly communities through research collaborations, editorial engagements, and membership in scientific associations, exemplifying excellence and leadership in engineering and applied sciences.

Profiles: Google Scholar | Scopus

Featured Publications

1. Investigation of the efficiency of pulsed electromagnetic field treatment and stretching exercise in experimental skeletal muscle injury model. BMC Musculoskeletal Disorders, 2025.

2. Prophylactic effects of radiofrequency electromagnetic field on pulmonary ischemia-reperfusion via HIF-1α/eNOS pathway and BCL2/BAX signaling. Pulmonary Circulation, 2025.

3. Radiofrequency electromagnetic and pulsed magnetic fields protected the kidney against lipopolysaccharide-induced acute systemic inflammation, oxidative stress, and apoptosis by regulating the IL-6/HIF1α/eNOS and Bcl2/Bax/Cas-9 pathways. Medicina (Lithuania), 2025.

4. Effect of 10 kV/m electric field therapy in a pressure injury model in rats: An innovative preliminary report. Bioengineering, 2025.

5. Effect of short-term extremely low-frequency electromagnetic field on respiratory functions. Revista da Associação Médica Brasileira (1992), 2025.

Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

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Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

Phd Candidate at University of Exeter, United Kingdom

Amir Hossein Poursaeed is an accomplished researcher in electrical engineering with a specialization in power systems, machine learning applications, and renewable energy integration. Holding a Master’s degree from Lorestan University, he has developed a strong academic foundation complemented by an exceptional research portfolio. His work focuses on power system protection, stability, and optimization using advanced AI techniques such as explainable deep learning and quantum neural networks. With over 17 peer-reviewed journal publications, many in Q1 journals, and multiple IEEE conference contributions, his research demonstrates both depth and innovation. He collaborates with leading academics internationally and has contributed to interdisciplinary studies in environmental modeling and water resource management. Amir’s commitment to cutting-edge research in inverter-based power grids, fault diagnosis, and energy systems places him among the promising young scholars in the field. His achievements reflect a rare blend of technical expertise, research leadership, and forward-looking vision essential for shaping the future of smart grids.

Professional Profile 

Google Scholar
ORCID Profile 

Education

Amir Hossein Poursaeed has a solid educational background in electrical engineering with a focus on power systems. He earned his Master of Science degree from Lorestan University, Iran, where he specialized in Digital Power System Protection and Power System Dynamics. His M.Sc. thesis, supervised by Professor Farhad Namdari, focused on using Support Vector Machines for wide-area protection against voltage and transient instabilities. He previously obtained his Bachelor of Science in Electrical Engineering from the same university, where he explored the optimal placement of phasor measurement units using metaheuristic algorithms. His academic performance was commendable, with a GPA of 18.87/20 in his M.Sc. program, demonstrating both technical strength and research capability. Throughout his education, he consistently focused on high-voltage systems, optimization, and smart grid technologies, laying the foundation for his research in AI-based power system protection and stability. His educational journey highlights a continuous commitment to excellence and innovation in energy systems.

Professional Experience

Amir Hossein Poursaeed has developed a robust professional profile centered around advanced power system research and academic collaboration. While specific institutional roles aren’t explicitly mentioned, his extensive list of high-impact publications indicates active involvement in collaborative research projects, particularly with institutions such as Lorestan University and international partners. He has co-authored multiple studies with recognized scholars, including Professor Farhad Namdari and Dr. P.A. Crossley, highlighting his integration into the global research community. His contributions include the design of advanced fault detection systems, AI-driven stability analysis tools, and renewable energy integration models. Additionally, his work in inter-turn fault diagnosis and real-time system protection showcases applied engineering skills with a focus on practical solutions for modern grid challenges. His experience spans theoretical research, model development, and algorithm implementation in live or simulated systems, establishing him as a well-rounded researcher in academia and an emerging leader in AI-enabled power engineering technologies.

Research Interest

Amir Hossein Poursaeed’s research interests are rooted in the intersection of electrical power systems and artificial intelligence. His primary focus includes power system stability, digital protection systems, fault detection, and the integration of renewable energy sources. He is especially passionate about leveraging advanced machine learning and explainable AI techniques for enhancing grid reliability and system monitoring. His recent work involves deep learning, support vector machines, and quantum neural networks applied to inverter-based power systems and DC microgrids—fields gaining global relevance due to the rise of decentralized energy systems. Optimization algorithms, transient analysis, and wide-area protection schemes are other key domains of his expertise. He also extends his knowledge into environmental systems, working on AI-based models for water quality assessment. This multidisciplinary approach underlines his goal of developing intelligent, robust, and real-time frameworks for smart grid operations, making his research both innovative and impactful in addressing contemporary and future challenges in energy systems.

Award and Honor

Although specific awards and honors are not listed, Amir Hossein Poursaeed’s academic and research accomplishments position him as a candidate deserving of high recognition. His publication record in prestigious Q1 journals, such as Applied Soft Computing, Energy Reports, and Sustainable Energy Technologies and Assessments, reflects scholarly excellence. His papers have introduced novel contributions to power system protection and AI-based monitoring, often co-authored with leading international experts—an indication of his growing reputation in the field. His research has also been accepted at major IEEE conferences, including the International Universities Power Engineering Conference and the International Conference on Electric Power and Energy Conversion Systems, which highlights peer recognition of his work. Moreover, his interdisciplinary research in water resource management using machine learning models demonstrates his versatility and impact beyond core power engineering. Given these achievements, he is highly deserving of academic awards, particularly those that celebrate emerging researchers and innovators in smart energy systems.

Conclusion

Amir Hossein Poursaeed is an emerging thought leader in the field of power systems and intelligent energy technologies. With a strong educational background and a research focus on AI-driven solutions for grid stability and protection, he has consistently demonstrated excellence in both theoretical innovation and practical application. His contributions span power engineering, machine learning, and even environmental sciences—showcasing his ability to bridge disciplines for impactful solutions. Through numerous high-impact publications and international conference engagements, he has established himself as a respected voice in the global research community. His work addresses critical challenges in inverter-based grids, renewable integration, and real-time monitoring, aligning perfectly with the global shift toward sustainable and resilient energy systems. Amir’s trajectory reflects not only technical brilliance but also research leadership, collaboration, and a vision for smarter, safer, and more efficient power systems. He is undoubtedly a strong candidate for honors such as the Best Researcher Award.

Publications Top Notes

  • Title: An Ultra-Fast Directional Protection Scheme for DC Microgrids Based on High-Order Synchrosqueezing Transform
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2023
    Citations: 7

  • Title: Online Transient Stability Assessment Implementing the Weighted Least-Square Support Vector Machine with the Consideration of Protection Relays
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 6

  • Title: A New Strategy for Prediction of Water Qualitative and Quantitative Parameters by Deep Learning-Based Models with Determination of Modelling Uncertainties
    Authors: M. Poursaeid, A.H. Poursaeed
    Year: 2024
    Citations: 6

  • Title: Online Voltage Stability Monitoring and Prediction by Using Support Vector Machine Considering Overcurrent Protection for Transmission Lines
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2020
    Citations: 6

  • Title: High‐Speed Algorithm for Fault Detection and Location in DC Microgrids Based on a Novel Time–Frequency Analysis
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2024
    Citations: 3

  • Title: Hydraulic Modeling of the Water Resources Using Learning Techniques
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2022
    Citations: 3

  • Title: Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 2

  • Title: Simulation Using Machine Learning and Multiple Linear Regression in Hydraulic Engineering
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2023
    Citations: 2

  • Title: Optimized Explainable Tabular Transformer Model for Fault Localization in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari, P.A. Crossley
    Year: 2025
    Citations: 1

  • Title: Optimal Coordination of Directional Overcurrent Relays: A Fast and Precise Quadratically Constrained Quadratic Programming Solution Methodology
    Authors: A.H. Poursaeed, M. Doostizadeh, S. Hossein Beigi Fard, A.H. Baharvand, F. Namdari
    Year: 2024
    Citations: 1

Fred Lang | Engineering | Best Researcher Award

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Mr. Fred Lang | Engineering | Best Researcher Award

President at Exergetic Systems Limited, United States

Fred D. Lang, P.E., P.Eng., is a distinguished power plant engineer with over 50 years of experience in energy systems, nuclear safety, and thermal performance monitoring. Renowned across North America and Europe, he has significantly contributed to power plant engineering through software innovation, advanced testing methodologies, and novel monitoring techniques. As the President of Exergetic Systems Limited, he has developed industry-transforming tools for power plant efficiency and safety. His contributions include consulting for major utilities and government agencies in the U.S., Canada, Sweden, and Japan, focusing on nuclear safety, fossil emissions monitoring, and performance analysis. Lang’s expertise spans simulation, plant design, exergy analysis, and fuel efficiency optimization, making him a leader in the energy sector. His commitment to research and technological advancements has led to groundbreaking methodologies that enhance power plant performance and operational safety, earning him a reputation as an innovator in the field.

Professional Profile

Education

Fred D. Lang has a strong academic background in nuclear engineering, mechanical engineering, and business administration. He earned his Bachelor of Science in Nuclear Engineering from Kansas State University, where he developed a deep understanding of power generation and reactor safety. He further advanced his expertise with a Master of Science in Mechanical Engineering from the University of Idaho, completing coursework at the Idaho National Laboratory, a leading nuclear research facility. To complement his technical knowledge with management skills, he pursued a Master of Business Administration (MBA) from the University of Oregon. In addition to his formal degrees, Lang holds several professional certifications, including a California Energy Auditor Certificate (#5872). He is a licensed Professional Engineer (P.E.) in California for mechanical and nuclear engineering and an active P.Eng. in British Columbia (#54236). His diverse educational background has provided him with the expertise to drive innovation in power plant engineering.

Professional Experience

Fred D. Lang has had an illustrious career spanning over five decades in power plant engineering. He is the President of Exergetic Systems Limited, a company specializing in power plant performance monitoring and efficiency solutions. Previously, he founded and led Exergetic Systems, Inc., which for nearly 40 years served major utilities across North America with software and engineering services. Lang is known as the “Father of PEPSE,” a widely used power plant simulation software. His expertise includes thermodynamic analysis, emissions monitoring, and nuclear safety systems. He has conducted hundreds of power plant studies and has been involved in 33 thermal performance evaluation projects, each lasting several months. His professional experience also includes consulting for Babcock & Wilcox, Exxon Nuclear (now Framatome), and government agencies in Sweden and Japan on critical nuclear safety issues. His work has shaped modern approaches to fuel monitoring, efficiency testing, and safety in power generation.

Research Interests

Fred D. Lang’s research focuses on power plant thermodynamics, nuclear safety, emissions monitoring, and exergy analysis. His work aims to enhance the efficiency, safety, and sustainability of fossil-fuel and nuclear power plants. A major area of his research is the development of advanced monitoring techniques, such as the Input/Loss Method, which allows real-time determination of fuel chemistry, calorific value, and heat rate in coal-fired power plants. Another significant contribution is the NCV Method, a groundbreaking approach to nuclear reactor monitoring, neutron flux measurement, and coolant flow analysis, which improves nuclear safety. Lang has also developed innovative instrumentation for emissions testing, heat balance analysis, and fuel efficiency optimization. His research integrates software development, thermodynamic modeling, and real-world application, ensuring that power plants operate more efficiently while reducing environmental impact. His findings have led to significant improvements in plant performance and fuel economy worldwide.

Awards and Honors

Fred D. Lang has received numerous accolades for his contributions to power plant engineering and nuclear safety. He holds 38 patents, including 22 in the U.S. and 16 in Canada, Australia, and Europe, covering innovations in power plant instrumentation, Rankine cycle modifications, and emissions monitoring technologies. His pioneering Input/Loss Method and NCV Method have been recognized as transformative advancements in the energy sector. Lang has been invited by major utilities and government agencies to develop new technologies, including a 2021 invitation to design a novel nuclear plant monitoring system. His software tools, such as PEPSE, EX-FOSS, and THERM, are used by leading power utilities worldwide. In addition to his technical achievements, he has been honored for his mentorship and leadership in the engineering field. His work has redefined power plant efficiency, fuel monitoring, and nuclear safety standards, earning him a reputation as a pioneer in the industry.

Conclusion

Fred D. Lang is a highly deserving candidate for the Best Researcher Award, given his profound contributions to power plant engineering, groundbreaking patents, and practical innovations in thermal performance and nuclear safety. While strengthening academic publications and mentorship efforts could further solidify his influence, his technical advancements have already had a significant impact on the industry. His work represents a paradigm shift in power plant monitoring and nuclear reactor safety, making him a strong contender for this recognition.

Publications Top Noted

  • Lang, F. D. (Year Unknown). “Verified Knowledge of Nuclear Power Plants Using the NCV Method.” Conference Paper. Citations: 0

  • Lang, F. D., Mason, D., & Rodgers, D. A. T. (Year Unknown). “Effects on Boiler Efficiency Standards and Computed Coal Flow Given Variable Ambient Oxygen and Humidity.” Conference Paper. Citations: 0