Dr. Zahra Beheshti | AI in Engineering | Best Researcher Award

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Dr. Zahra Beheshti | AI in Engineering | Best Researcher Award

Dr. Zahra Beheshti | Islamic Azad University | Iran

Dr. Zahra Beheshti is an Assistant Professor at the Islamic Azad University, Najafabad Branch, with a distinguished background in computer engineering and artificial intelligence. She holds a B.Sc. and M.Sc. in Computer Engineering (Software) and a Ph.D. in Computer Science with a focus on Artificial Intelligence, followed by postdoctoral research in Soft Computing. Dr. Beheshti has made significant contributions to the field, including the compilation of the book Centripetal Accelerated Particle Swarm Optimization and Applications. Her academic excellence has been recognized through scholarships awarded to top international Ph.D. students. She is actively involved in knowledge dissemination, having conducted multiple workshops on advanced topics such as Machine Learning, Fuzzy Expert Systems and their application in algorithm parameter determination, and Introduction to Fuzzy Logic along with the Design and Implementation of Fuzzy Expert Systems. Her research output includes 34 documents, cited 1,865 times by 1,698 publications, with an h-index of 20, reflecting the significant impact of her work. Through her teaching, research, and publications, Dr. Beheshti demonstrates a strong commitment to advancing computational intelligence, fostering innovation, and mentoring the next generation of researchers in AI and soft computing, combining both academic rigor and practical application.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Z Beheshti, SMH Shamsuddin, A review of population-based meta-heuristic algorithms, Int. J. Adv. Soft Comput. Appl 5 (1), 1-35, 744 citations, 2013

  • H Abedinpourshotorban, SM Shamsuddin, Z Beheshti, DNA Jawawi, Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm, Swarm and Evolutionary Computation 26, 8-22, 414 citations, 2016

  • M Jafarzadegan, F Safi-esfahani, Z Beheshti, Combining Hierarchical Clustering approaches using the PCA Method, Expert Systems with Applications 137, 1-10, 156 citations, 2019

  • Z Beheshti, SM Shamsuddin, S Hasan, Memetic binary particle swarm optimization for discrete optimization problems, Information Sciences 299, 58-84, 129 citations, 2015

  • Z Beheshti, SMH Shamsuddin, CAPSO: centripetal accelerated particle swarm optimization, Information Sciences 258, 54-79, 120 citations, 2014

  • M Banaie-Dezfouli, MH Nadimi-Shahraki, Z Beheshti, R-GWO: Representative-based grey wolf optimizer for solving engineering problems, Applied Soft Computing 106, 1-28, 108 citations, 2021

 

 

Dr. Bin Zhang | Structural Engineering | Best Researcher Award

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Dr. Bin Zhang | Structural Engineering | Best Researcher Award

Dr. Bin Zhang | Chongqing University of Science and Technology | China

Dr. Bin Zhang holds a Doctorate in Engineering and has completed postdoctoral research. He is a lecturer and master’s supervisor in the Department of Road and Bridge Engineering, School of Civil and Hydraulic Engineering, and a youth committee member of the World Transport Convention. His research focuses on the dynamic characteristics of underground and tunnel structures, the development of new materials and technologies for structural reinforcement, and intelligent monitoring of structural health. His research output includes 26 documents, 171 citations, 146 citing documents, and an h-index of 8. He teaches both undergraduate and postgraduate courses, including Tunnel Engineering, Engineering Surveying, Tunnel Mechanics, and Frontier Technologies in Civil Engineering, integrating theoretical knowledge with practical applications to advance innovation in civil and tunnel engineering. Additionally, he has developed advanced experimental methods for studying tunnel lining mechanics, contributing to safer and more efficient tunnel design practices.

Profile: Scopus | Orcid

Featured Publications

  • Study on the Stability of Buildings During Excavation in Urban Core Areas, Applied Sciences, 2025. Contributors: Kang Liu, Huafeng Liu, Yuntai Gao, Zijian Wang, Yunchuan Wang, Qi Liu, Chaolin Jia, Zihang Huang, Bin Zhang.

  • Experimental Study on Mechanical Differences Between Prefabricated and Cast-In Situ Tunnel Linings Based on a Load-Structure Model, Buildings, 2025. Contributors: Li-Ming Wu, Hong-Kun Li, Feng Gao, Zi-Jian Wang, Bin Zhang, Wen-Jie Luo, Jun-Jie Li.

  • Mechanical Properties of Steel Fiber-Reinforced Concrete Tunnel Secondary Lining Structure and Optimization of Support Parameters, Buildings, 2025. Contributors: Zijian Wang, Yunchuan Wang, Xiaorong Wang, Baosheng Rong, Bin Zhang, Liming Wu, Chaolin Jia, Zihang Huang.

  • Crystallization Blockage in Highway Tunnel Drainage System Based on Molecular Dynamics, AIP Advances, 2025. Contributors: Shiyang Liu, Xuefu Zhang, Bin Zhang.

  • Experimental Study on Grouting Diffusion Law of Tunnel Secondary Lining Cracks Based on Different Slurry Viscosities, Applied Sciences, 2025. Contributors: Bin Zhang, Peng Liu, Yi Wu, Liming Wu, Chen Li, Shiyang Liu, Yuanfu Zhou.

  • Experimental Study on Grouting Diffusion Law of the Different Crack Widths in Tunnel Lining, KSCE Journal of Civil Engineering, 2023. Contributors: Bin Zhang, Yuanfu Zhou, Xuefu Zhang, Zijian Wang, Wei Yang, Yixuan Ban.

  • Anti Crystallization Blocking of Flocking Drainage Pipe Based on Natural Phenomenon, Materials Science, 2022. Contributors: Xuefu Zhang, Shiyang Liu, Feng Gao, Yuanfu Zhou, Bin Zhang.

Dr. Priya Tyagi | Sustainable Engineering | Best Researcher Award

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Dr. Priya Tyagi | Sustainable Engineering | Best Researcher Award

Dr. Priya Tyagi | Sharda University | India

Dr. Priya Tyagi is a dedicated sustainable architect with extensive academic and professional expertise in sustainable design and rural housing development. She earned her Doctor of Philosophy from Malaviya National Institute of Technology, Jaipur, focusing on a decision-making framework for design quality assessment of rural houses in India, following her Master of Architecture in Sustainable Architecture from Deenbandhu Chhotu Ram University of Science and Technology, Murthal, and Bachelor of Architecture from Shri Ram Group of Colleges, Lucknow. She has actively contributed to research and practice in architecture, including a joint research project on municipal waste management at Massachusetts Institute of Technology, Boston, and holds professional credentials as a Green Rating for Integrated Habitat Assessment certified professional. Currently, she serves as Assistant Professor at Sharda School of Design, Architecture and Planning, Greater Noida, having previously held academic positions at Sanskar College of Architecture and Planning and practical experience with Shelter Architects and M/s Raj Architects and Builders. Dr. Tyagi has been recognized for her expertise through appointments as a reviewer for Scopus-indexed journals, including the Journal of Infrastructure, Policy and Development, and the Journal of Civil, Construction and Environmental Engineering. Her research output includes 9 documents with 6 citations and an h-index of 2, reflecting her growing impact in sustainable architecture, design quality assessment, and environmentally responsible building practices in India.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

Tyagi, P., Shrivastava, B., & Kumar, N. (2024). Investigating rural housing quality indicators in the Indian scenario for inclusive imageability. Environment, Development and Sustainability, 26(10), 25609-25643.

Tyagi, P., Shrivastava, B., & Kumar, N. (2023). Towards creating inclusive villages: The types of rural settlements in India. ISVS e-Journal, 10(2), 91-106.

Bhyan, P., Tyagi, P., Doddamani, S., Kumar, N., & Shrivastava, B. (2023). Life cycle assessment of lightweight and sustainable materials. Lightweight and Sustainable Composite Materials, 117-142.

Tyagi, P., Shrivastava, B., & Kumar, N. (2024). A comprehensive investigation of rural and low-rise housing design quality: A thematic and bibliometric analysis. Journal of Housing and the Built Environment, 39(3), 1323-1353.

Tyagi, P., Shrivastava, B., & Kumar, N. (2025). Optimizing rural housing design quality: Indicators and parameters for comprehensive assessment. Environment, Development and Sustainability, 1-43.

Prof. Ouajdi Korbaa | AI in Engineering | Innovative Research Award

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Prof. Ouajdi Korbaa | AI in Engineering | Innovative Research Award

Prof. Ouajdi Korbaa | University of Sousse | Tunisia

Prof. Ouajdi Korbaa is a distinguished researcher and professor at the Institute of Computer Science and Communication Techniques, University of Sousse, Tunisia, and a member of the Modeling of Automated Reasoning Systems Laboratory. His research focuses on modeling, discrete optimization, scheduling, and artificial intelligence, contributing significantly to the development of advanced methodologies in these areas. He has supervised numerous Master’s and PhD students and actively participates in academic juries, reflecting his commitment to mentoring the next generation of researchers. Prof. Korbaa has authored 157 documents cited by 998 sources, achieving an h-index of 18, demonstrating his strong impact and influence in the field. His work integrates theoretical foundations with practical applications, advancing computational techniques for problem-solving and decision-making. Recognized for his expertise in optimization and AI, he has made substantial contributions to both the academic community and the broader field of computer science, fostering innovation in modeling and automated reasoning systems.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Nssibi, M., Manita, G., & Korbaa, O. (2023). Advances in nature-inspired metaheuristic optimization for feature selection problem: A comprehensive survey. Computer Science Review, 49, 100559.

  • Jemili, F., Meddeb, R., & Korbaa, O. (2024). Intrusion detection based on ensemble learning for big data classification. Cluster Computing, 27(3), 3771–3798.

  • Benzarti, S., Triki, B., & Korbaa, O. (2017). A survey on attacks in Internet of Things based networks. In Proceedings of the 2017 International Conference on Engineering & MIS (ICEMIS) (pp. 1–7).

  • Meddeb, R., Jemili, F., Triki, B., & Korbaa, O. (2023). A deep learning-based intrusion detection approach for mobile Ad-hoc network. Soft Computing, 27(14), 9425–9439.

  • Abid, A., Jemili, F., & Korbaa, O. (2024). Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques. Cluster Computing, 27(2), 2217–2238.

  • Korbaa, O., Camus, H., & Gentina, J. C. (1997). FMS cyclic scheduling with overlapping production cycles. In Proceedings of the 18th International Conference on Application and Theory of Automation in Technology (pp. 1–10).

  • Lee, J., & Korbaa, O. (2004). Modeling and scheduling of ratio-driven FMS using unfolding time Petri nets. Computers & Industrial Engineering, 46(4), 639–653.

  • Meddeb, R., Triki, B., Jemili, F., & Korbaa, O. (2017). A survey of attacks in mobile ad hoc networks. In Proceedings of the 2017 International Conference on Engineering & MIS (ICEMIS) (pp. 1–7).

 

Mr. Bimal Kumar Dora | AI in Engineering | Best Researcher Award

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Mr. Bimal Kumar Dora | AI in Engineering | Best Researcher Award

Mr. Bimal Kumar Dora | Visvesvaraya National Institute of Technology | India

Mr. Bimal Kumar Dora is a dedicated researcher in Electrical Engineering, currently pursuing his Doctor of Philosophy at Visvesvaraya National Institute of Technology, Nagpur, after completing his Master of Technology in Control, Power and Electric Drives from the National Institute of Technology, Sikkim, and a Bachelor of Technology in Electrical Engineering from Biju Patnaik University of Technology, Odisha. He recently broadened his international research experience as a Visiting Researcher at the Montefiore Institute, University of Liège, Belgium, where he contributed to advanced studies in renewable energy integration and the development of global electricity grids. His doctoral research, titled Global Electricity Interconnection with Renewable Energy Generation, emphasizes methods such as the Enhanced Critical Time Window Framework, Weibull distribution analysis, and temporal variability indexing to identify and optimize renewable energy sites across Indian onshore and offshore regions. He has designed several innovative hybrid algorithms including Modified Pelican Optimization Algorithm, Novel Modified Pelican Driven Optimization Algorithm, Enhanced Pelican Foraging Algorithm, Enhanced Dragonfly and Moth Optimization Algorithm, Modified Reptile Optimization Algorithm, Modified Harris Hawk and Pelican Optimization Algorithm, and Enhanced Harris Hawk and Pelican Optimization Algorithm.  With 97 citations from 75 documents, 16 publications, and an index rating of 7, he is building a growing academic reputation that combines computational intelligence, renewable energy, and futuristic large-scale power system design.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  1. Dora, B. K., Rajan, A., Mallick, S., & Halder, S. (2023). Optimal reactive power dispatch problem using exchange market based butterfly optimization algorithm. Applied Soft Computing, 147, 110833.

  2. Halder, S., Bhat, S., & Dora, B. K. (2022). Inverse thresholding to spectrogram for the detection of broken rotor bar in induction motor. Measurement, 198, 111400.

  3. Halder, S., Bhat, S., & Dora, B. (2023). Start-up transient analysis using CWT and ridges for broken rotor bar fault diagnosis. Electrical Engineering, 105(1), 221–232.

  4. Halder, S., Dora, B. K., & Bhat, S. (2022). An enhanced pathfinder algorithm based MCSA for rotor breakage detection of induction motor. Journal of Computational Science, 64, 101870.

  5. Dora, B. K., Bhat, S., Halder, S., & Srivastava, I. (2024). A solution to multi objective stochastic optimal power flow problem using mutualism and elite strategy based pelican optimization algorithm. Applied Soft Computing, 158, 111548.

  6. Dora, B. K., Bhat, S., Halder, S., & Sahoo, M. (2023). Solution of reactive power dispatch problems using enhanced dwarf mongoose optimization algorithm. 2023 International Conference for Advancement in Technology (ICONAT), 1–6.

Mr. Andreas Fezer | Data Driven Engineering | Best Researcher Award

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Mr. Andreas Fezer | Data Driven Engineering | Best Researcher Award

Mr. Andreas Fezer | Materials Testing Institute, University of Stuttgart | Germany

Mr. Andreas Fezer is a Scientific Associate at the Materials Testing Institute, University of Stuttgart, Germany, specializing in joining technology and additive manufacturing. He holds both bachelor’s and master’s degrees in mechanical engineering from the University of Stuttgart. Since joining the institute, he has contributed to advanced research on resistance spot welding, aluminum alloys, and the integration of experimental and machine learning approaches in welding technology. His published works focus on improving manufacturing efficiency and material performance. With expertise spanning mechanical engineering fundamentals and applied welding processes, Mr. Fezer plays an active role in advancing industrial materials testing and innovative manufacturing solutions.

Professional Profile

Orcid

Education and Experience

Mr. Andreas Fezer earned his bachelor’s and master’s degrees in mechanical engineering from the University of Stuttgart, Germany. Following his academic training, he began his professional career at the Materials Testing Institute, University of Stuttgart, where he works as a Scientific Associate in the Department of Joining Technology and Additive Manufacturing. His work involves both experimental and computational research, focusing on welding processes, material resistance evaluation, and the development of innovative manufacturing techniques. Through his combined academic background and applied industrial research, Mr. Fezer contributes to the advancement of materials engineering and welding technologies in both academic and industrial contexts.

Summary Suitability

Mr. Andreas Fezer is an outstanding candidate for the Best Researcher Award due to his significant contributions to advanced materials testing and welding technology. As a Scientific Associate at the Materials Testing Institute, University of Stuttgart, he has demonstrated expertise in joining technology and additive manufacturing, focusing on aluminum alloys and resistance spot welding processes. His work combines experimental investigations with innovative machine learning techniques, enabling improved understanding of dynamic resistance and contact behavior in metal joining.

Professional Development 

Mr. Andreas Fezer has cultivated expertise in resistance spot welding, aluminum alloy characterization, and additive manufacturing processes. He engages in collaborative research integrating experimental methods with machine learning to improve process understanding and efficiency in manufacturing. His professional growth has been shaped by active participation in scientific publications, interdisciplinary teamwork, and applied research projects that connect engineering theory with industrial practice. Working within the renowned Materials Testing Institute at the University of Stuttgart has allowed him to refine his analytical, problem-solving, and technical skills, positioning him as a valuable contributor to innovation in mechanical engineering and materials science.

Research Focus 

Mr. Andreas Fezer’s research is centered on welding technology, particularly resistance spot welding of aluminum alloys used in automotive and structural applications. His work addresses both the physical phenomena involved in material joining and the development of methods for evaluating contact and bulk resistance in metals. He explores dynamic resistance behavior using a combination of laboratory experimentation and machine learning techniques, aiming to enhance process reliability, material performance, and production efficiency. His research focus falls under the category of advanced manufacturing and materials engineering, with an emphasis on joining processes, welding quality control, and the integration of data-driven approaches in manufacturing.

Awards and Honors

Mr. Andreas Fezer’s professional recognition is reflected in his contributions to peer-reviewed scientific publications and his role in advancing welding technology research. His work has appeared in reputable international journals, showcasing the impact and quality of his studies in materials testing and manufacturing innovation. Through collaborative projects and research dissemination, he has earned professional respect within the mechanical engineering and materials science community. His achievements underscore his reputation as a researcher whose work supports both academic advancement and industrial application in the field of joining technology and additive manufacturing.

Publication Top Notes

Title: Method for Determining the Contact and Bulk Resistance of Aluminum Alloys in the Initial State for Resistance Spot Welding
Year: 2025

Title: Experimental and Machine Learning Investigation of Dynamic Resistance in Aluminum Resistance Spot Welding for the Body-in-White
Year: 2025

Conclusion

Mr. Andreas Fezer’s innovative research, combining experimental methods and machine learning in welding technology, has made a significant impact on materials science and manufacturing. His work demonstrates technical excellence, practical relevance, and academic rigor, establishing him as a leading researcher in his field. His contributions to understanding and improving aluminum resistance spot welding processes highlight both his scientific insight and his ability to drive industrial innovation, making him exceptionally deserving of the Best Researcher Award.

 

Prof. Dr. Vedat Oruç | Engineering | Best Researcher Award

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Prof. Dr. Vedat Oruç | Engineering | Best Researcher Award

Prof. Dr. Vedat Oruç , Dcile University , Turkey.

Prof. Dr. Vedat Oruç 👨‍🏫 is a distinguished academic at the Department of Mechanical Engineering, Faculty of Engineering, Dicle University, Diyarbakır, Turkiye 🇹🇷. Since 1998, he has dedicated his career to advancing the fields of fluid mechanics, flow control, and refrigeration 🌬️❄️. With 41 publications in top-tier journals 📚 and a Web of Science H-index of 15 📈, his contributions are widely recognized. He actively shares his research across platforms like Scopus, Web of Science, and Google Scholar 🌐. Prof. Oruç is known for his dedication, impactful research, and long-standing commitment to engineering education and innovation ⚙️🎓.

Publication Profile

Scopus
Orcid
Google Scholar

Education and Experience 

  • 🎓 Academic Background: Mechanical Engineering, Dicle University

  • 👨‍🏫 Teaching Experience: Faculty member since 1998 at Dicle University

  • 🏛️ Institution: Department of Mechanical Engineering, Faculty of Engineering, Dicle University

  • 📍 Location: Diyarbakır, Turkiye

  • 🧪 Research Focus: Fluid Mechanics, Flow Control, Refrigeration

Suitability Summary

Prof. Dr. Vedat Oruç, a distinguished academic at Dicle University, Türkiye, is an ideal candidate for the Best Researcher Award. With over 25 years of experience in mechanical engineering, his work has significantly advanced the fields of fluid mechanics, flow control, and refrigeration. Prof. Oruç has authored 41 peer-reviewed journal articles indexed in SCI and Scopus, demonstrating both depth and consistency in research. His scholarly influence is reflected in a Web of Science H-index of 15, and his publications are widely cited across reputable platforms. His academic integrity and commitment to innovative research make him a strong contender for this prestigious honor.

Professional Development 

Prof. Dr. Vedat Oruç has steadily built his professional expertise through decades of teaching and research 🧑‍🔬📘. With over 41 publications in reputable journals indexed in SCI and Scopus 📄🔍, he demonstrates a strong foundation in experimental and theoretical engineering. His academic journey is supported by high-impact research reflected in a WOS H-index of 15 📊. He continues to contribute to the advancement of fluid mechanics and flow technologies through innovative work and continuous learning 🔄. By staying actively involved in scholarly platforms like Scopus, Web of Science, and Google Scholar 🌐, he ensures visibility and collaboration opportunities across borders 🌍.

Research Focus 

Prof. Dr. Vedat Oruç specializes in the dynamic fields of fluid mechanics, flow control, and refrigeration 🌊🌀❄️. His work investigates the behavior of fluids under various physical conditions, aiming to optimize control methods for engineering applications 🚀. These areas are critical in industries ranging from HVAC systems to aerospace and energy efficiency 🌡️✈️🔋. His 41 peer-reviewed journal publications illustrate a strong commitment to expanding theoretical and applied research. By focusing on efficient energy transfer and innovative flow techniques, Prof. Oruç contributes significantly to sustainable engineering and practical technological advancement ⚙️🌱📈.

Awards and Honors 

  • 🏆 Nominee: Best Researcher Award – Superior Engineering Research Awards

  • 🧪 Scientific Recognition: 41 peer-reviewed publications (SCI, Scopus)

  • 📈 Impact Metric: Web of Science H-index of 15

  • 🌍 Global Visibility: Active profiles on Scopus, Web of Science, ResearchGate, and Google Scholar

Publication Top Notes 

  • 🔬 The Thermodynamic and Environmental Analysis of a Variable Speed R404A Refrigeration System Using R455A

  • 📉 Isı Pompası Kullanıldığında Optimum Yalıtım Kalınlığının Belirlenmesi ve Ekonomik Analizi

    • Journal: DÜMF Mühendislik Dergisi

    • Date: October 5, 2024

    • DOI: 10.24012/dumf.1547522

    • Contributors: Uğur Yaman, Atilla Gencer Devecioğlu, Vedat Oruç

  • 🏠 The Evaluation and Improvement for the Energy Performance of Buildings: A Case Study

    • Journal: Next Energy

    • Date: July 2024

    • DOI: 10.1016/j.nxener.2024.100126

    • ISSN: 2949-821X

    • Contributors: Atilla G. Devecioğlu, Burhan Bilici, Vedat Oruç

  • ❄️ Retrofit of an Internal Heat Exchanger in a R404A Refrigeration System Using R452A

    • Journal: Next Energy

    • Date: April 2024

    • DOI: 10.1016/j.nxener.2024.100107

    • Contributors: Vedat Oruç, Atilla G. Devecioğlu, Derviş B. İlhan

  • 🌬️ An Investigation on the Utilization of R470A for Air-Conditioning Systems Towards 2025

    • Journal: Journal of Advanced Thermal Science Research

    • Date: August 16, 2023

    • DOI: 10.15377/2409-5826.2023.10.1

    • ISSN: 2409-5826

    • Contributors: Atilla G. Devecioğlu, Vedat Oruç

  • 🧊 Soğutma Sistemlerinde R454C Kullanılmasının Deneysel İncelenmesi

    • Journal: Politeknik Dergisi

    • Date: March 27, 2023

    • DOI: 10.2339/politeknik.898828

    • ISSN: 2147-9429

    • Contributors: Atilla Gencer Devecioğlu, Vedat Oruç

  • 🇪🇺 On the Satisfaction of EU F-Gas Regulation Using R455A as an Alternative to R404A

    • Journal: Materials Today: Proceedings

    • Date: 2022

    • DOI: 10.1016/j.matpr.2021.11.506

    • ISSN: 2214-7853

    • Contributors: Atilla G. Devecioğlu, Vedat Oruç

  • ♻️ Drop-in Assessment of Plug-in R404A Refrigeration Equipment Using Low-GWP Mixtures

    • Journal: International Journal of Low-Carbon Technologies

    • Date: July 25, 2022

    • DOI: 10.1093/ijlct/ctac078

    • ISSN: 1748-1325

    • Contributors: Atilla G. Devecioğlu, Vedat Oruç

Conclusion

Prof. Dr. Vedat Oruç’s outstanding publication record, impactful research, and long-standing academic contributions solidify his candidacy for the Best Researcher Award. His work not only advances core areas of mechanical engineering but also provides real-world applications in energy systems and fluid technologies. With a legacy of academic excellence and continued dedication to research, he exemplifies the high standards this award seeks to recognize.