Ahmed El-Sherbeeny | Human Factors Engineering | Best Researcher Award

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Dr. Ahmed El-Sherbeeny | Human Factors Engineering | Best Researcher Award

Assistant Professor | King Saud University  | Saudi Arabia

Dr. Ahmed M. El-Sherbeeny is an Assistant Professor of Industrial Engineering at King Saud University, specializing in safety engineering, human factors and ergonomics, and environmental engineering. With an extensive interdisciplinary research portfolio, he has contributed significantly to high-impact domains including public health, intelligent systems, machine learning, environmental remediation, and industrial sustainability. His scholarly impact is reflected in 456 publications 7,784 citations, an h-index of 44, and an i10-index of 135, positioning him as a highly influential researcher within and beyond his primary discipline.Dr. El-Sherbeeny has collaborated on several landmark global studies most notably the Recovery trials published in The Lancet, which transformed clinical decision-making for COVID-19 treatment. His co-authored works on Tocilizumab Casirivimab/Imdevimab Azithromycin Baricitinib and corticosteroid therapy collectively account for thousands of citations underscoring his role in research that shaped international health policies. Beyond clinical research he has made notable contributions to intelligent security frameworks for electric vehicles machine-learning-driven medical diagnostics and blockchain-based IoT access control demonstrating strong engagement with emerging technological frontiers.In the environmental and materials engineering domains his publications address photocatalytic degradation nanocomposites for pollutant removal drug-delivery materials groundwater quality assessment and energy-efficient systems reflecting an impressive breadth of problem-solving across sustainability and environmental protection. His collaborative works span multiple continents involving international teams from engineering medical sciences environmental chemistry and computational intelligence.Dr. El-Sherbeeny’s research outputs appearing in top-tier journals such as The Lancet Chemical Engineering Journal Journal of Hazardous Materials ACS Omega and IEEE Access highlight both methodological rigor and societal impact. His contributions advance safer industrial systems enhance public health resilience support data-driven environmental management and promote technologically integrated solutions for global sustainability challenges.

Profiles : ORCID | Scopus | Google Scholar

Featured Publications

1.Avatefipour, O., Al-Sumaiti, A. S., El-Sherbeeny, A. M., Awwad, E. M., & Elmeligy, M. A. (2019). An intelligent secured framework for cyberattack detection in electric vehicles’ CAN bus using machine learning. Cited By : 185

2.Nadeem, A., Ahmad, S. F., Al-Harbi, N. O., Fardan, A. S., & El-Sherbeeny, A. M. (2017). IL-17A causes depression-like symptoms via NFκB and p38MAPK signaling pathways in mice: Implications for psoriasis associated depression.
Cited By : 172

3.Nadeem, A., Al-Harbi, N. O., Al-Harbi, M. M., El-Sherbeeny, A. M., & Ahmad, S. F. (2015). Imiquimod-induced psoriasis-like skin inflammation is suppressed by BET bromodomain inhibitor in mice through RORC/IL-17A pathway modulation. Pharmacological Research, 99, 248–257.  Cited By : 132

4.Mahum, R., Rehman, S. U., Meraj, T., Rauf, H. T., Irtaza, A., & El-Sherbeeny, A. M. (2021). A novel hybrid approach based on deep CNN features to detect knee osteoarthritis. Cited By : 117

5.Yang, X., Wang, J., El-Sherbeeny, A. M., AlHammadi, A. A., & Park, W. H. (2022). Insight into the adsorption and oxidation activity of a ZnO/piezoelectric quartz core-shell for enhanced decontamination of ibuprofen: Steric, energetic, and oxidation studies. Cited By : 98

Dr. Ahmed M. El-Sherbeeny’s interdisciplinary research integrates industrial engineering, machine learning, and environmental sciences to advance public health, industrial safety, and sustainable technologies. His work informs global healthcare strategies, enhances intelligent systems, and drives innovative solutions with broad societal and industrial impact.

Hadi Gokcen | Engineering | Best Researcher Award

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Prof. Hadi Gokcen | Engineering | Best Researcher Award

Professor | Gazi University Industrial Engineering Department | Turkey

Dr. Hadi Gökçen, affiliated with Gazi University, Ankara, Turkey, is a distinguished researcher recognized for his influential contributions to industrial engineering, operations research, and computational intelligence. With 51 published documents, an h-index of 23, and more than 1,920 citations from 1,367 citing documents, his scholarly impact spans data-driven decision systems, intelligent manufacturing, and applied artificial intelligence. His recent works reflect a strong integration of machine learning, optimization, and sustainability in solving real-world industrial and economic problems. In Computational Economics , he introduced a hybrid machine learning model that combines clustering and stacking ensemble approaches for improved real estate price prediction. His research published in Applied Sciences Switzerland, proposed a dynamic scheduling method for identical parallel-machine environments through a multi-purpose intelligent utility framework. In Flexible Services and Manufacturing Journal, he presented innovative balancing and sequencing strategies for mixed-model parallel robotic assembly lines, emphasizing energy-efficient production. Further, his Survey Review paper applied hybrid unsupervised learning to identify sub-real estate markets, enhancing prediction accuracy and market segmentation. His contribution to developing a Digital Transformation Perception Scale underscores his focus on organizational innovation and industrial adaptation within the Industry paradigm. Dr. Gökçen’s interdisciplinary research bridges artificial intelligence, optimization, and digital transformation, advancing the understanding and implementation of intelligent, sustainable, and adaptive systems in engineering and economic domains.

Profiles : ORCID | Scopus | Google Scholar 

Featured Publications

1. Demirel, N. Ö., & Gökçen, H. (2008). A mixed integer programming model for remanufacturing in reverse logistics environment. The International Journal of Advanced Manufacturing Technology, 39(11), 1197–1206.
Cited By : 258

2. Demirel, E., Demirel, N., & Gökçen, H. (2016). A mixed integer linear programming model to optimize reverse logistics activities of end-of-life vehicles in Turkey. Journal of Cleaner Production, 112, 2101–2113.
Cited By : 247

3. Gökçen, H., Ağpak, K., & Benzer, R. (2006). Balancing of parallel assembly lines. International Journal of Production Economics, 103(2), 600–609.
Cited By : 226

4. Gökçen, H. (2007). Yönetim bilgi sistemleri. Ankara: Palme Yayıncılık.
Cited By : 217

5. Erel, E., & Gökçen, H. (1999). Shortest-route formulation of mixed-model assembly line balancing problem. European Journal of Operational Research, 116(1), 194–204.
Cited By : 189

Jafar Fathali | Operations Research | Best Researcher Award

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Prof.Jafar Fathali | Operations Research | Best Researcher Award

University Professor at Shahrood University of Technology, Iran 

Professor Jafar Fathali 🎓 is a renowned academic in Operations Research and Applied Mathematics, currently serving as a Professor at the Faculty of Mathematical Sciences, Shahrood University of Technology, Iran 🇮🇷. With decades of contribution to location theory, heuristic optimization, and scheduling problems , he has become a distinguished figure in computational mathematics. A prolific researcher, Prof. Fathali has authored over 50+ peer-reviewed journal articles  in internationally recognized platforms such as EJOR, Soft Computing, and Computers & Industrial Engineering. He is actively involved in scholarly communities including the Iranian Mathematical Society and the Iranian Operations Research Society . Beyond research, he contributes as a referee for leading journals, mentoring students and advancing mathematical modeling in real-world applications. His academic journey is defined by innovation, persistence, and leadership , making him a vital contributor to the global research ecosystem .

🔹Professional Profile

SCOPUS

ORCID

📘 Education & Experience

Prof. Jafar Fathali holds a BSc in Applied Mathematics from Ferdowsi University of Mashhad , an MSc from Amirkabir University of Technology , and earned his Ph.D. in Applied Mathematics from Ferdowsi University in 2005 . With a solid foundation in mathematical theories, he began teaching at Shahrood University of Technology, where he advanced to a full professorship . Over the years, he has taught a wide array of undergraduate and graduate courses, including Operations Research, Advanced Linear & Nonlinear Programming, Combinatorial Optimization, and Numerical Analysis . His expertise spans both theoretical frameworks and practical applications, equipping students with problem-solving and analytical skills 🔍. With his academic and mentoring experience, Prof. Fathali has played a key role in shaping Iran’s next generation of mathematicians and operations research .

🚀 Professional Development

Professor Fathali has shown remarkable growth in academia through innovative research, interdisciplinary collaborations, and active journal reviewing . He has reviewed articles for top-tier journals such as European Journal of Operational Research, Transportation Research Part E, Soft Computing, and Optimization Methods and Software . He is a member of the Iranian Mathematical Society, Iranian Operations Research Society, and Iranian Statistics Society , reflecting his deep involvement in the academic community. His ability to integrate fuzzy logic, graph theory, and metaheuristic algorithms into practical models has enhanced decision-making strategies across industries . Prof. Fathali has also co-developed numerous hybrid algorithms involving genetic algorithms, ant colony optimization, and variable neighborhood search for solving complex problems . His active mentorship, editorial contributions, and research collaborations are key indicators of a career deeply committed to academic excellence, growth, and innovation .

🔬 Research Focus

Professor Jafar Fathali’s research is firmly rooted in Operations Research, with an emphasis on location theory , combinatorial optimization, and scheduling problems . He specializes in designing algorithms for complex decision-making models such as the p-median, p-center, and core location problems across graphs and trees . His methods employ heuristic techniques, metaheuristics (e.g., genetic algorithms , particle swarm optimization , and fuzzy logic  to model real-world uncertainties in logistics, network design, and resource allocation. Prof. Fathali has also explored inverse and semi-obnoxious location problems, expanding the scope of location models to account for service inefficiencies and backup facilities . His works address both theoretical and applied aspects, blending mathematical rigor with practical implementation . With continuous innovations in modeling and optimization, his contributions have significantly advanced the field of applied mathematics and operations research .

🏆 Awards & Honors

While specific awards and honors for Professor Jafar Fathali are not individually listed, his academic reputation is underscored by the impact and volume of his scholarly work . Having published in high-impact journals like European Journal of Operational Research and Soft Computing, his research has earned wide recognition and citation 🏆. Being a referee for over a dozen international journals and collaborating with well-known scholars such as R.E. Burkard, indicates peer acknowledgment and respect . His sustained publication record, editorial engagements, and frequent invitations to review complex mathematical models highlight his research excellence and international credibility . His contributions have helped define solutions for complex logistics and scheduling challenges, securing his place among Iran’s most influential operations research . With ongoing recognition from both academic institutions and scholarly circles, Prof. Fathali continues to be a role model for aspiring mathematicians and OR specialists globally .

🔹Publication of Top Notes

1.Convexity and sensitivity analysis of the median line location problem

Authors: Mehdi Golpayegani, Jafar Fathali
Year: 2025
Journal: International Journal of Systems Science: Operations & Logistics
DOI: 10.1080/23302674.2025.2529967

2.Greedy algorithms for the inverse center line location problem

Authors: Mehdi Golpayegani, Jafar Fathali
Year: 2025
Journal: Expert Systems with Applications
DOI: 10.1016/j.eswa.2025.129064

3.Fuzzy balanced allocation problem with efficiency on facilities

Authors: Azam Azodi, Jafar Fathali, Mojtaba Ghiyasi, Tahereh Sayar
Year: 2023
Journal: Soft Computing
DOI: 10.1007/s00500-022-07695-4

4.The balanced 2-median and 2-maxian problems on a tree

Authors: Jafar Fathali, Mehdi Zaferanieh
Year: 2023
Journal: Journal of Combinatorial Optimization
DOI: 10.1007/s10878-023-00997-9

5.Finding the absolute and vertex center of a fuzzy tree

Authors: Fatemeh Taleshian, Jafar Fathali, Nemat Allah Taghi-Nezhad
Year: 2022
Journal: Transportation Letters
DOI: 10.1080/19427867.2021.1909797

6.The minimum information approach to the uncapacitated p-median facility location problem

Authors: Mehdi Zaferanieh, Maryam Abareshi, Jafar Fathali
Year: 2022
Journal: Transportation Letters
DOI: 10.1080/19427867.2020.1864595

7.Fuzzy Balanced Allocation Problem with Efficiency on Servers

Authors: Azam Azodi, Jafar Fathali, Mojtaba Ghiyasi, Tahereh Sayar
Year: 2021
Type: Preprint
DOI: 10.21203/rs.3.rs-444116/v1

8.Inverse and reverse balanced facility location problems with variable edge lengths on trees

Authors: Shahede Omidi, Jafar Fathali, Morteza Nazari
Year: 2020
Journal: OPSEARCH
DOI: 10.1007/s12597-019-00428-6

9.Finding an optimal core on a tree network with M/G/c/c state-dependent queues

Authors: Mehrdad Moshtagh, Jafar Fathali, James MacGregor Smith, Nezam Mahdavi-Amiri
Year: 2019
Journal: Mathematical Methods of Operations Research
DOI: 10.1007/s00186-018-0651-3

10.The Stochastic Queue Core problem, evacuation networks, and state-dependent queues

Authors: Mehrdad Moshtagh, Jafar Fathali, J. MacGregor Smith
Year: 2018
 Journal: European Journal of Operational Research
 DOI: 10.1016/j.ejor.2018.02.026

🏁Conclusion

Professor Fathali’s research stands out due to its mathematical rigor, practical relevance, and algorithmic innovation. His work significantly advances the optimization and decision sciences field, contributing both theoretical frameworks and practical solutions. These qualities, combined with his sustained academic output, collaborative spirit, and international impact, make him an ideal candidate for the Best Researcher Award.

Dr. Vahideh Bafandegan Emroozi | Maintenance | Women Researcher Award

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Dr. Vahideh Bafandegan Emroozi | Maintenance | Women Researcher Award

Author , Ferdowsi university of Mashhad , Iran

Vahideh Bafandegan Emroozi is a passionate Iranian researcher specializing in industrial management and optimization. 🎓 With a Ph.D. from Ferdowsi University of Mashhad, her work bridges technology and human-centric approaches. 📊 Her research spans supply chain innovation, IoT applications, and human error analysis. 🤖🧠 She has published in esteemed journals and held research fellowships at Ferdowsi and Sanabad Universities. 📚✍️ Known for her analytical skills and academic dedication, Vahideh continues to contribute significantly to industrial systems and decision sciences. 🔍📈 Her collaborative spirit and teaching experience further highlight her dynamic role in academia. 👩‍🏫🌐

Professional Profile:

SCOPUS

Education & Experience:

Vahideh earned her Ph.D. in Industrial Management (2019–2024) 🎓 from Ferdowsi University, where her thesis focused on IoT-based maintenance and human error modeling. 📡🛠️ She also completed an M.Sc. in Industrial Management (2014–2017) with a high GPA of 18.96/20 📚 and a B.Sc. in Industrial Engineering (2008–2012). 🏗️ Her academic journey led to research fellow roles at Ferdowsi University (2021–2023) and Sanabad University (2023–2024). 🔬🏛️ In addition to research, she has taught Operations Research, Strategic Management, and Multi-Criteria Decision Making. 👩‍🏫 Her experience reflects a strong foundation in both theory and application. 💼🧮

Professional Development:

Vahideh continually builds her academic and technical skills through professional development. 📈💡 She has mastered analytical and modeling tools such as Python, MATLAB, GAMS, LINGO, LaTeX, and Vensim. 💻📐 Her commitment to research excellence is evident in her publications in Scopus-indexed journals 📄🔍 and her work on complex topics like green supply chain management and pandemic response strategies. 🌍📦 She actively contributes to knowledge dissemination through teaching, collaborative research, and methodological innovation. 📊🧠 Her engagement with multidisciplinary topics ensures she remains at the forefront of industrial and systems engineering. 🚀📘

Research Focus:

Vahideh’s research spans across multiple domains in industrial management. 🏭🔍 Her core interests include supply chain management, optimization, and maintenance planning. 🧾🛠️ She also explores the effects of human error, reliability analysis, and inventory control systems. ⚙️🧠📦 A significant part of her work integrates the Internet of Things (IoT) 🌐 with system dynamics and mathematical modeling 📊📉 to improve industrial decision-making. Her goal is to create smarter, more resilient, and sustainable industrial systems. 🌱💡 Her innovative contributions are driving progress in operational efficiency and risk reduction. 🚚📈

Awards & Honors:

While specific awards were not listed, Vahideh’s academic record speaks to her excellence. 🌟 She achieved outstanding GPAs in both her Ph.D. (19.49/20) and M.Sc. (18.96/20) programs. 🥇📘 Her research has been recognized with publications in high-impact international journals like Process Integration and Optimization for Sustainability and Journal of Industrial and Management Optimization. 📚✨ She has contributed novel methodologies in green supplier selection, VIKOR optimization, and system dynamics during COVID-19. 🧪🌐 Her roles as research fellow at top Iranian universities also reflect her academic merit and potential. 🏛️🔬

Publication Top Notes

1. Markov Chain-Based Model for IoT-Driven Maintenance Planning with Human Error and Spare Part Considerations

Authors: Bafandegan Emroozi, Vahideh; Doostparast, Mahdi
Journal: Reliability Engineering and System Safety
Year: 2025
Access: Open Access
Citations: 0 (as of now)

🔍 Summary:
This article introduces a novel Markov chain-based framework that integrates the Internet of Things (IoT) into industrial maintenance planning. The model accounts for human error probabilities and spare part availability, creating a dynamic and realistic approach to predictive maintenance. 📈 The use of Markov chains enables the system to model stochastic transitions between equipment states, improving decision-making accuracy. 🤖📦 The study enhances reliability and safety in industrial systems by aligning IoT data with probabilistic risk and resource planning, offering a scalable tool for real-time maintenance strategy optimization. 🛠️📊

2. Enhancing Industrial Maintenance Planning: Optimization of Human Error Reduction and Spare Parts Management

Authors: Bafandegan Emroozi, Vahideh; Kazemi, Mostafa; Doostparast, Mahdi
Journal: Operations Research Perspectives
Year: 2025
Access: Open Access
Citations: 0 (as of now)

🔍 Summary:
This paper proposes an optimization model aimed at improving maintenance planning by focusing on human error mitigation and efficient spare parts management. 👷⚙️ It applies advanced operations research techniques to identify cost-effective strategies for minimizing failures and delays due to incorrect human actions or resource shortages. The model bridges the gap between human factors engineering and logistical planning, integrating real-time data and decision analysis. 🧠📦 It offers a comprehensive framework suitable for modern industries aiming to balance cost, reliability, and safety. 🧾📉

Conclusion

Vahideh Bafandegan Emroozi exemplifies the qualities celebrated by Women in Research Awards: innovation, impact, leadership, and academic excellence. 🌟 Her work addresses critical industrial challenges through smart technologies and rigorous modeling, while her dedication to teaching and mentoring amplifies her influence. As a pioneering female researcher in a highly technical and traditionally male-dominated field, she is not only technically accomplished but also a role model for aspiring women in STEM. 🧠🔬👩‍🏫 She is highly deserving of recognition through a Women Researcher Award.