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

Mohammad Taghilou | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Mohammad Taghilou | Engineering | Best Researcher Award

Associate professor | University of Zanjan | Iran

Dr. Mohammad Taghilou is an Associate Professor in the Department of Mechanical Engineering at the University of Zanjan, Iran. His research expertise lies in heat transfer, phase change problems, energy storage, and porous media, with an emphasis on the lattice Boltzmann method (LBM) and its applications in thermal systems. Over his academic career, he has authored impactful studies published in leading journals such as Applied Thermal Engineering, Computers & Mathematics with Applications, and the International Journal of Thermal Sciences. His most cited works explore PCM solidification, nanofluid-based heat exchangers, and the thermal behavior of energy storage systems. Dr. Taghilou’s studies significantly contribute to advancing thermal management technologies, including applications in lithium-ion batteries, heat sinks, and double-pipe exchangers, with an aim to enhance energy efficiency and system reliability. His collaborations with international scholars from institutions such as the University of Tehran, Aalto University (Finland), and the University of Technology Sydney have expanded the interdisciplinary reach of his research. With 541 total citations, an h-index of 15, and an i10-index of 16, his work demonstrates both academic impact and global relevance. Through innovative numerical modeling and experimental approaches, Dr. Taghilou continues to advance understanding in phase-change thermal systems and nanomaterial-enhanced heat transfer, fostering sustainable energy applications and modern engineering solutions.

Profiles: ORCID | Scopus | Google Scholar | ResearchGate | LinkedIn

Featured Publications

1.Sajedi, R., Osanloo, B., Talati, F., & Taghilou, M. (2016). Splitter plate application on the circular and square pin fin heat sinks.  Cited by : 70

2.Taghilou, M., & Rahimian, M. H. (2014). Investigation of two-phase flow in porous media using lattice Boltzmann method. Cited By : 49

3.Talati, F., & Taghilou, M. (2015). Lattice Boltzmann application on the PCM solidification within a rectangular finned container. Cited By : 44

4.Taheri, A. A., Abdali, A., Taghilou, M., Alhelou, H. H., & Mazlumi, K. (2021). Investigation of mineral oil-based nanofluids effect on oil temperature reduction and loading capacity increment of distribution transformers.
Cited By : 40

5.Taghilou, M., & Khavasi, E. (2020). Thermal behavior of a PCM filled heat sink: The contrast between ambient heat convection and heat thermal storage. Cited By : 36

Sakshi Dua | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Sakshi Dua | Engineering | Best Researcher Award

Associate Professor | Lovely Professional University | India

Dr. Sakshi Dua is an accomplished academic and researcher currently serving as Associate Professor at the School of Computer Applications, Lovely Professional University, Jalandhar-Phagwara, Punjab, India. She holds a Ph.D. in Computer Science and has over 14 years of professional experience as Assistant Professor before her current role. Her research interests span artificial intelligence, Internet of Things, Arduino, machine learning, fuzzy systems, network operating systems, and database management systems. She has contributed as Guest Editor for reputed ABDC and Scopus-indexed journals, authored book chapters with CRC Press, Taylor & Francis, and IGI Global, and is actively involved in book editorial projects with CRC Press and Emerald. She has published widely in SCIE, Scopus, ABDC, and UGC-indexed journals, as well as in IEEE and Springer conferences, and has presented her research internationally. Her contributions extend to applied innovation with patents and copyrights in diverse areas such as smart healthcare, ICT, and IoT-based solutions. She has chaired sessions at IEEE conferences, delivered workshops and FDPs, and guided students through impactful academic and research projects. Her skills include advanced data analysis, algorithm design, applied AI and IoT development, research writing, and academic leadership. Dr. Sakshi Dua has earned recognition through her impactful scholarly work, editorial leadership, and strong community engagement. She has received 71 citations by 9 documents with an h-index of 1.

Profile :  Scopus

Featured Publication

1. Dua, S. (2025). Blockchain-based node authentication algorithm for securing electronic health record data transmission.

Vahideh Bafandegan Emroozi| Engineering | Women Researcher Award

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Dr. Vahideh Bafandegan Emroozi| Engineering | Women Researcher Award

Corresponding Author, Ferdowsi university of Mashhad,Iran

Dr. Vahideh Bafandegan Emroozi is a rising academic with a robust publication record, collaborative outlook, and applied interdisciplinary focus. Her work on supply chain optimization, IoT integration, and human reliability is timely and contributes to both industrial efficiency and sustainable development.

Professional Profile:

Scopus

Google scholar

🎓 Education

Vahideh Bafandegan Emroozi holds a Ph.D. in Industrial Management from Ferdowsi University of Mashhad, Iran (2019–2024), with a remarkable GPA of 19.49 out of 20. Her doctoral thesis focuses on developing a maintenance planning model using the Internet of Things (IoT) while accounting for human error. She earned her M.Sc. in Industrial Management from the same university in 2017, graduating with a GPA of 18.96. She began her academic journey with a B.Sc. in Industrial Engineering at Ferdowsi University, graduating in 2012.

Professional Experience

Dr. Bafandegan Emroozi has served as a research fellow at Sanabad University (2023–2024) and Ferdowsi University of Mashhad (2021–2023). In these roles, she has contributed to various multidisciplinary projects focusing on optimization, reliability, and maintenance strategies within industrial systems.

Skills

She brings a strong technical toolkit that includes programming and modeling in Python, MATLAB, GAMS, Vensim, LINGO, LaTeX, UCINET, and Minitab. She is also proficient in MICMAC and Microsoft Office applications, reflecting a solid foundation in both qualitative and quantitative analysis.

Research Interests

r research spans multiple domains, including supply chain management, optimization, maintenance and reliability, human error analysis, inventory control, system dynamics, and mathematical modeling. Her work often explores the intersection of advanced technologies (e.g., IoT) with human-centered decision-making.

✅ Conclusion

Women Researcher Award: Strongly Recommended. Her academic output, innovative scope, and relevance to modern global challenges make her an excellent candidate. Best Researcher Award: Recommended with Reservations. She is well on her way, but continued growth in citations, funding, and global recognition would strengthen her case in the future.

Publication Top Notes:

  • Modares, A., Kazemi, M., Bafandegan Emroozi, V., & Roozkhosh, P. (2023). A new supply chain design to solve supplier selection based on internet of things and delivery reliability. Journal of Industrial and Management Optimization, 19(11), 7993–8028. Cited by: 39

  • Modares, A., Motahari Farimani, N., & Bafandegan Emroozi, V. (2023). A vendor-managed inventory model based on optimal retailers selection and reliability of supply chain. Journal of Industrial and Management Optimization, 19(5), 3075–3106. Cited by: 32

  • Modares, A., Motahari Farimani, N., & Bafandegan Emroozi, V. (2023). A new model to design the suppliers portfolio in newsvendor problem based on product reliability. Journal of Industrial and Management Optimization, 19(6), 4112–4151. Cited by: 25

  • Bafandegan Emroozi, V., Roozkhosh, P., Modares, A., & Roozkhosh, F. (2023). Selecting green suppliers by considering the internet of things and CMCDM approach. Process Integration and Optimization for Sustainability, 7(5), 1167–1189. Cited by: 19

  • Bafandegan Emroozi, V., & Fakoor, A. (2023). A new approach to human error assessment in financial service based on the modified CREAM and DANP. Journal of Industrial and Systems Engineering, 14(4), 95–120. Cited by: 19

  • Bafandegan Emroozi, V., Kazemi, M., Doostparast, M., & Pooya, A. (2024). Improving industrial maintenance efficiency: A holistic approach to integrated production and maintenance planning with human error optimization. Process Integration and Optimization for Sustainability, 8(2), 539–564. Cited by: 18

  • Modares, A., Motahari, N., & Bafandegan Emroozi, V. (2022). Developing a newsvendor model based on the relative competence of suppliers and probable group decision-making. Industrial Management Journal, 14(1), 115–142. Cited by: 18

  • Bafandegan Emroozi, V., Modares, A., & Roozkhosh, P. (2024). A new model to optimize the human reliability based on CREAM and group decision making. Quality and Reliability Engineering International, 40(2), 1079–1109. Cited by: 16

  • Modares, A., Motahari Farimani, N., & Bafandegan Emroozi, V. (2023). Applying a multi-criteria group decision-making method in a probabilistic environment for supplier selection (Case study: Urban railway in Iran). Journal of Optimization in Industrial Engineering, 16(1), 129–140. Cited by: 15

  • Emroozi, V. B., Kazemi, M., Modares, A., & Roozkhosh, P. (2024). Improving quality and reducing costs in supply chain: the developing VIKOR method and optimization. Journal of Industrial and Management Optimization, 20(2), 494–524. Cited by: 1