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

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

 

 

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

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.

 

Neyara Radwan | Engineering | Women Researcher Award

Assoc. Prof. Dr. Neyara Radwan | Engineering | Women Researcher Award

Liwa College - Abu Dhabi Campus, United Arab Emirates

👨‍🎓Profiles

👩‍🏫 Early Academic Pursuits

Neyara Radwan embarked on her academic journey in Egypt, where she completed her Bachelor's degree in Production Engineering & Mechanical Design from Mansoura University. Her early academic pursuits were characterized by a strong foundation in engineering principles, leading to her Bachelor's project on designing belt conveyors for Belkas Sugar Factory. She further honed her expertise with a Master's degree in Production Engineering & Mechanical Design, from the same institution. The focus of her Master's thesis was on the "Utilization of Computer-Aided Expert System for Power Transmission Shaft Design," a work that would lay the groundwork for her future research. In 2008, she earned her Ph.D. in Production Engineering from Benha University, Egypt, with a thesis titled “CAD of Electro-Chemical Honing Machining and Statistical Modeling for Selection of Parameters Influencing Electro-Chemical Honing Process." This work demonstrated her expertise in advanced manufacturing techniques and solidified her role as a leading academic in the field.

🏢 Professional Endeavors

Throughout her career, She has held various academic and leadership positions across multiple institutions globally. She has been a Full-time Associate Professor at Liwa College, Abu Dhabi, UAE, as well as a Full-time Associate Professor in the Mechanical Department at Suez Canal University, Additionally, she has served at prestigious institutions such as Al Mareefa University, KSA, and King Abdul-Aziz University, KSA, where she was involved in quality assurance and Ph.D. program development. Her versatility is reflected in her work at both full-time and part-time capacities at institutions like the High Institute for Industrial Building and Production Technology and the Specialized Studies Academy in Egypt, marking her as a well-rounded academic professional with vast international experience.

🧑‍🔬 Contributions and Research Focus

Her research interests span across a wide range of fields, including Optimization, Lean Manufacturing, Sustainability, Supply Chain Management, and Solid Waste Management. Her focus on the application of Artificial Intelligence (AI) in manufacturing processes and energy systems has made significant contributions to both the theoretical and practical aspects of these disciplines. She has contributed to sustainable engineering systems by optimizing operation and enhancing renewable energy technologies. Her work emphasizes optimal scheduling operations, integration of AI for operational efficiency, and advancing quality management practices in industrial environments.

🌍 Impact and Influence

Her academic and professional influence extends globally through her work in teaching, research, and industry applications. Her contributions have been recognized in various prestigious awards, including the Certificate of Excellence as Best Global Educator and the Global Award from the International Research Academy of Science and Arts (IRASA). She has impacted both the academic community and industry by promoting sustainability, energy efficiency, and circular economy approaches, notably in Saudi Arabia's Vision 2030 waste management goals. Through her numerous awards, including the Golden Academic Award from Tradepreneur Global (2022), she has established herself as a leading voice in engineering education and research. Her extensive list of citations and publications further amplifies her reach and impact in the global academic community.

📚 Academic Cites and Research Recognition

Her research has garnered substantial recognition, with her contributions being cited extensively across various journals and international conferences. Her work on optimization and sustainable engineering has been pivotal in developing better operational strategies in industrial systems, contributing to both academic literature and real-world applications. She has received multiple research excellence awards from universities like Suez Canal University, highlighting her dedication to advancing knowledge in production engineering and sustainable systems.

🧰 Technical Skills

She is proficient in a diverse set of technical skills related to industrial and production engineering, including Optimization Algorithms, Lean Manufacturing Techniques, and AI Applications in Engineering Systems. She has applied these skills to enhance operational efficiency, improve quality management, and design sustainable energy systems. Her expertise also spans across renewable energy technologies, systems operation, and optimal scheduling, making her a significant contributor to both energy and manufacturing industries.

👨‍🏫 Teaching Experience

She has an extensive teaching career, spanning over two decades, during which she has mentored undergraduate and graduate students across various academic institutions in Egypt, the UAE, Saudi Arabia, and beyond. Her role as an educator has not only involved teaching core engineering concepts but also guiding students in conducting high-impact research in optimization, sustainable manufacturing, and energy systems. Her teaching approach integrates practical applications with theoretical knowledge, preparing her students to tackle real-world challenges in industrial management and engineering.

🌟 Legacy and Future Contributions

Her legacy in academia and research is defined by her commitment to promoting sustainability and innovation in engineering. She has significantly contributed to research in the fields of renewable energy, lean manufacturing, and artificial intelligence, making strides toward more efficient and environmentally friendly industrial practices. Moving forward, She is dedicated to advancing the field of sustainable engineering through interdisciplinary research that bridges technology, management, and energy systems. She aims to continue her legacy by mentoring the next generation of engineers and contributing to global sustainability goals, particularly in the context of waste management and circular economy approaches.

🏅 Awards and Recognition

Her exceptional contributions to education and research have been recognized through numerous awards. Some of her notable accolades include: Excellence Award from the Faculty of Economics and Administration at King Abdulaziz University, Global Award for Most Outstanding Engineering Educator, Golden Academic Award from Tradepreneur Global, Global Academic Excellence Award from ICWP, Global Service to Humanity Award from ADlafrica,

📖Notable Publications

  1. Computational Analysis of MHD Nanofluid Flow Across a Heated Square Cylinder with Heat Transfer and Entropy Generation
    • Authors: Madhu Sharma, Bhupendra K. Sharma, Chandan Kumawat, Arun K. Jalan, Neyara Radwan
    • Journal: Acta Mechanica et Automatica
    • Year: 2024
  2. The Varying Viscosity Impact in an Inclined Peristaltic Channel with Diffusion‐Thermo and Thermo‐Diffusion
    • Authors: Anum Tanveer, Sharak Jarral, A. Al‐Zubaidi, Salman Saleem, Neyara Radwan
    • Journal: ZAMM - Journal of Applied Mathematics and Mechanics
    • Year: 2024
  3. Applications of Lubrication Approximation Theory in the Analysis of the Roll‐Coating Using a Tangent Hyperbolic Fluid Model
    • Authors: Hafiz Muhammad Atif, Iffat Zaka, Neyara Radwan, Muhammad Asif Javed, Mubbashar Nazeer, Salman Saleem
    • Journal: ZAMM - Journal of Applied Mathematics and Mechanics
    • Year: 2024
  4. Chromium Contamination and Effect on Environmental Health and Its Remediation: A Sustainable Approaches
    • Authors: Shiv Prasad, Krishna Kumar Yadav, Sandeep Kumar, Neha Gupta, Marina M.S. Cabral-Pinto, Shahabaldin Rezania, Neyara Radwan, Javed Alam
    • Journal: Journal of Environmental Management
    • Year: 2021
  5. Strength and Flexural Behavior of Steel Fiber and Silica Fume Incorporated Self-Compacting Concrete
    • Authors: Abdalla M. Saba, Afzal Husain Khan, Mohammad Nadeem Akhtar, Nadeem A. Khan, Seyed Saeid Rahimian Koloor, Michal Petrů, Neyara Radwan
    • Journal: Journal of Materials Research and Technology
    • Year: 2021
  6. Measuring Industrial Symbiosis Index Using Multi-Grade Fuzzy Approach
    • Authors: Kalyan C., Abhirama T., Mohammed N.R., Aravind Raj S., Jayakrishna K.
    • Journal: Lecture Notes in Mechanical Engineering
    • Year: 2019