Rashed Sahraeian | Sustainability in Oil and Gas | Best Scholar Award

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Prof. Dr. Rashed Sahraeian | Sustainability in Oil and Gas | Best Scholar Award

Professor at Shahed University, Iran

Professor Rashed Sahraeian is a distinguished full professor in the Department of Industrial Engineering at Shahed University, Tehran, Iran. His career reflects a deep dedication to the fields of optimization, supply chain management (SCM), facility location problems (FLP), and location-routing problems (LRP). Professor Sahraeian is widely recognized for his extensive contributions to academia through impactful research, prolific publications, mentorship of graduate students, and active participation in peer reviewing for top international journals. His scholarly excellence and commitment to industrial engineering have made him a prominent figure both nationally and internationally.

Profile

Google Scholar

Education

Professor Sahraeian’s educational foundation is rooted in industrial engineering, where he specialized in operations research and optimization methodologies. Throughout his academic training, he developed a keen interest in complex decision-making models, quantitative analysis, and supply chain design. His formal education provided him with advanced competencies in mathematical modeling, computational techniques, and logistics systems, setting a robust stage for his future contributions to the domain.

Experience

With an academic career spanning over two decades, Professor Sahraeian has amassed extensive experience in teaching, research, and supervision. He has taught specialized courses including Facility Layout and Location, Supply Chain Management, Scheduling and Sequencing, and Integer Programming. As a dedicated mentor, he has supervised over 55 Master’s theses and 12 Ph.D. dissertations, nurturing the next generation of engineers and researchers. His practical involvement extends beyond academia, where he applies his research findings to real-world industrial problems, emphasizing sustainable and resilient supply chain solutions. Furthermore, his active role as a reviewer for high-impact journals underscores his expertise and reputation in the global academic community.

Research Interest

Professor Sahraeian’s primary research interests encompass optimization in industrial systems, closed-loop supply chain design, facility location under uncertainty, and robust scheduling. He is particularly passionate about solving multi-objective optimization problems in logistics and production environments, employing innovative methods such as hybrid evolutionary algorithms, constraint programming, and grey system theory. His recent work also extends into sustainable supply chain network design, considering environmental factors and resilience against disruptions, aligning closely with contemporary industrial needs and global sustainability goals.

Award

Throughout his academic journey, Professor Sahraeian has been recognized for his outstanding research and educational contributions. He has earned awards and acknowledgments for his significant role in advancing industrial engineering, particularly for his impactful publications and excellence in student supervision. His recognition as a leading figure in optimization and supply chain management is further evidenced by his continuous invitations to review papers for prestigious journals such as the Journal of Cleaner Production, Computers & Industrial Engineering, and Applied Mathematical Modelling.

Publication

Among his many publications, seven notable works illustrate his influential contributions.

(1) In 2012, he co-authored “An interactive possibilistic programming approach for a multi-objective closed-loop supply chain network under uncertainty” in Applied Mathematical Modelling (cited by 340 articles).

(2) In 2013, he published “The hierarchical hub covering problem with an innovative allocation procedure covering radiuses” in Scientia Iranica (cited by 85 articles).

(3) In 2014, his study on “Dynamic multi-commodity inventory and facility location problem in steel supply chain network design” appeared in the International Journal of Advanced Manufacturing Technology (cited by 110 articles).

(4) In 2015, he explored “Optimal modeling and evaluation of job shops with a total weighted tardiness objective” in Applied Mathematical Modelling (cited by 92 articles).

(5) That same year, he co-authored “Augmented ε-constraint method in multi-objective flow shop problem with past sequence setup times” in the International Journal of Production Research (cited by 70 articles).

(6) In 2016, he contributed “MULTI-OBJECTIVE OPTIMIZATION OF INTEGRATED LOT-SIZING AND SCHEDULING PROBLEM IN FLEXIBLE JOB SHOPS” to RAIRO Operations Research (cited by 60 articles).

(7) In 2024, he published “Decision-Making Approach to Design a Sustainable Photovoltaic Closed-Loop Supply Chain Considering Market Share for Electric Vehicle Energy” in Sustainability (garnering growing citations). These selected publications emphasize his research depth and broad application impact.

Conclusion

In conclusion, Professor Rashed Sahraeian has made outstanding contributions to the advancement of industrial engineering, particularly in optimization and supply chain network design. His research innovations, leadership in education, and strong publication record position him as a leading figure in his field. Through a combination of theoretical rigor and practical relevance, he continues to influence the discipline of industrial engineering, inspiring students and colleagues alike. His career trajectory exemplifies academic excellence, practical relevance, and a deep commitment to solving real-world industrial challenges through advanced research methodologies.

Tahir Cetin Akinci | Data Analytics in Upstream Operations | Best Research Article Award

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Dr. Tahir Cetin Akinci | Data Analytics in Upstream Operations | Best Research Article Award

Scientist at University of California Riverside, United States

Dr. Tahir Çetin Akıncı is a distinguished academician and researcher in electrical engineering, particularly known for his impactful work in artificial intelligence, renewable energy, and advanced signal processing. With a professional trajectory that spans over two decades, he has consistently contributed to advancing knowledge and innovation in intelligent systems and power electronics. His commitment to both academic excellence and real-world problem-solving has earned him global recognition, positioning him as a thought leader in his field.

Profile

Orcid

Education

Dr. Akıncı began his academic journey at Klaipeda University in Lithuania, earning his undergraduate degree in electrical engineering in 2000. He later pursued graduate studies at Marmara University, where he completed his master’s degree in 2005 and Ph.D. in 2010. These formative academic experiences laid the groundwork for his future research directions, particularly in the domains of energy systems and machine learning applications. His educational path is marked by a solid foundation in electrical systems theory, enriched by practical insights into data-driven methodologies.

Experience

His professional career commenced as a Research Assistant at Marmara University, where he served from 2003 to 2010. He then joined Istanbul Technical University (ITU), advancing through academic ranks to become a full professor by 2020. Currently, Dr. Akıncı serves at the University of California, Riverside, contributing to international collaborations and high-impact research initiatives. Throughout his tenure in academia, he has mentored students, led research projects, and collaborated across disciplines to address critical engineering challenges.

Research Interest

Dr. Akıncı’s research interests are both broad and deep, encompassing renewable energy systems, artificial neural networks, deep learning, machine learning, cognitive systems, signal processing, and data analysis. His multidisciplinary approach allows him to tackle complex problems—ranging from optimizing photovoltaic systems to diagnosing electrical motor faults using AI. His work in renewable energy technologies and smart systems not only enhances system efficiencies but also aligns with global sustainability goals. He is particularly passionate about the integration of AI in diagnostics, predictive maintenance, and energy management, striving to create systems that are not only intelligent but also resilient and sustainable.

Award

His contributions have been recognized through multiple prestigious awards, most notably the International Young Scientist Excellence Award and the Best Researcher Award in 2022. These accolades reflect his pioneering work and the high regard he holds within the scientific community. In addition to these honors, Dr. Akıncı has played critical roles as editor and guest editor for leading journals and serves on scientific committees of several high-profile international conferences, further underscoring his influence in shaping future directions in electrical engineering and AI.

Publication

Among his extensive list of publications, several recent papers stand out for their innovative approaches and significant citations. For instance:

“Sustainable pathways for hydrogen production: Metrics, trends, and strategies for a zero-carbon future,” Sustainable Energy Technologies and Assessments, 2025 – cited for its strategic insights on green hydrogen.

“Revealing GLCM Metric Variations across Plant Disease Dataset,” Electronics, 2024 – contributes to deep learning applications in agriculture.

“Optimization of Neuro-controller Application for MPPT in Photovoltaic Systems,” Electric Power Components and Systems, 2024 – enhances energy efficiency using AI.

“Time Series Forecasting Utilizing AutoML,” Information, 2024 – applies automated ML for forecasting in diverse datasets.

“Advanced Dual RNN Architecture for Electrical Motor Fault Classification,” IEEE Access, 2023 – highly cited for its innovation in motor diagnostics.

“Machine Learning-Based Error Correction Codes and Communication Protocols for Power Line Communication,” IEEE Access, 2023 – strengthens smart grid reliability.

“Effect of LED Light Frequency on an Object in Terms of Visual Comfort,” Electric Power Components and Systems, 2024 – explores visual ergonomics in energy-efficient lighting.

Conclusion

In conclusion, Dr. Tahir Çetin Akıncı exemplifies the ideal candidate for this award through his unwavering commitment to scientific advancement, innovation in engineering education, and leadership in multidisciplinary research. His work bridges the gap between theory and application, aiming to develop technologies that not only solve current engineering problems but also anticipate future challenges. Through his dedication, he continues to inspire the next generation of engineers and scientists, fostering a more intelligent and sustainable world.