Sina Sayardoost Tabrizi | Data Analytics in Upstream Operations | Best Researcher Award

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Dr. Sina Sayardoost Tabrizi | Data Analytics in Upstream Operations | Best Researcher Award

Senior Lecturer and Director of Dean’s Office at University of Tehran | Iran

Dr. Sina Sayardoost Tabrizi is a Senior Lecturer and Director of the Dean’s Office at the University of Tehran (Kish International Campus), specializing in industrial management, artificial intelligence, and sustainable operations. He holds a Ph.D. in Industrial Management and both B.Sc. and M.Sc. degrees in Computer Engineering, establishing a strong interdisciplinary foundation bridging technology and management. With over eight years of academic experience, he has supervised more than 30 student projects and published over 15 peer-reviewed papers in Q1 and Scopus-indexed journals. Dr. Sina Sayardoost Tabrizi is the founder of the Metaverse and Emerging Technologies Laboratory, where he leads innovative projects integrating AI, data analytics, and digital transformation across education, industry, and sustainability sectors. His research spans sustainable supply chain management, dynamic network data envelopment analysis (DNDEA), machine learning, and decision-support systems, with notable contributions to the petrochemical and manufacturing industries. His scholarly output includes 8 major research projects, a co-authored academic textbook, and one patent under process for an AI-driven decision-support framework. Beyond academia, he has collaborated with national and international partners—including Muscat University—on consultancy and innovation initiatives focusing on efficiency optimization, digital learning platforms, and AI ethics. As a reviewer for international journals in operations research and a member of professional organizations such as IFORS and the Iranian Association of Management Science, he contributes actively to the global research community. His work has received recognition for integrating advanced computational models with sustainable industry practices, improving efficiency in resource-intensive systems by measurable margins. Dr. Sina Sayardoost Tabrizi commitment to interdisciplinary research, educational innovation, and technological ethics positions him as a forward-thinking academic leader dedicated to advancing responsible AI, sustainability, and data-driven decision-making for societal and industrial progress.

Profile: Google Scholar

Featured Publications

Sayardoost Tabrizi, K. S., Sabzian, A., & Moeini, A. (2024). TAM-based model for evaluating learner satisfaction of e-learning services: Case study—E-learning system of University of Tehran.

Sayardoost Tabrizi, S., Yakideh, K., Moradi, M., & Ebrahimpour, M. (2025). Clustering with machine learning and using NDEA in development planning: A case study in the petrochemical two-stage SSC.

Sayardoost Tabrizi, S., Yakideh, K., Moradi, M., & Ebrahimpour, M. (2024). Assessing sustainability of supply chain performance using machine learning and network data envelopment analysis.

Sayardoost Tabrizi, S., Sabzian, A., & Moeini, A. (2024). A hybrid model for evaluation of e-learning user satisfaction with TAM and ELQ approach.

Sayardoost Tabrizi, S., Abideen, A. Z., & Moeini, A. (2025). A novel machine learning and DNDEA framework for sustainable efficiency measurement in a circular two-stage supply chain.

Sayardoost Tabrizi, S., Yousefi, S., & Yakideh, K. (2025). Forecasting efficiency of two-stage petrochemical sustainable supply chains using deep learning and DNDEA model. Operations Research Perspectives.

Qi Sun | Operations Management | Best Researcher Award

Published on by Petroleum Engineering

Mr. Qi Sun | Operations Management | Best Researcher Award

Ph.D. candidate at China University of Petroleum | China

Mr. Qi Sun is a promising Ph.D. candidate at the China University of Petroleum (East China), specializing in Management Science and Engineering. His research focuses on supply chain management, disruptive technologies, and sustainable operations. With international exposure as a visiting scholar at the University of Dundee, he has cultivated a strong academic foundation enriched by global collaboration. Mr. Qi Sun has contributed significantly through peer-reviewed publications, conference presentations, and funded projects. His work bridges theory and practice, advancing supply chain resilience and sustainability in complex market environments, positioning him as a rising researcher with international recognition.

Profile

Scopus

Education

Mr. Qi Sun pursued his academic career with a clear focus on logistics and management sciences. He earned his B.Sc. in Logistics Engineering from Shandong Jiao-Tong University, followed by an M.Sc. in Logistics Engineering at Qingdao University, where he graduated as an Outstanding Master Graduate. Currently, he is a Ph.D. candidate in Management Science and Engineering at the China University of Petroleum (East China), with completion. Additionally, his international perspective is enriched by a visiting research experience at the University of Dundee (UK) from, broadening his academic scope.

Experience

Mr. Qi Sun has a diverse blend of academic and industry experience. Before pursuing graduate research, he worked as a Management Trainee at SF Express, where he developed insights into logistics operations. During his academic journey, he has served as a teaching assistant, actively supporting courses in operations research. His involvement in multiple funded projects, including those supported by the National Natural Science Foundation of China and the Shandong Province Science Foundation, highlights his strong applied research capability. Through these roles, he has cultivated expertise in supply chain modeling, operational strategies, and risk management, contributing both practically and academically.

Research Interest

Mr. Qi Sun research centers on supply chain management with disruptive technologies and sustainable operations management. His studies explore critical areas such as blockchain applications in supply chain finance, dual-channel strategies, information sharing, and carbon reduction mechanisms. By integrating advanced modeling tools and strategic approaches, his research seeks to address practical challenges faced by global supply chains in the digital and sustainable era. He focuses particularly on balancing efficiency with social responsibility, risk management, and environmental impact. His research contributions aim to support both academic advancement and industry application, enabling organizations to adapt successfully to modern complexities.

Awards

Mr. Qi Sun has been recognized with multiple prestigious academic honors that underscore his scholarly excellence. He was awarded the Outstanding Student Award by the China University of Petroleum for exceptional academic and research performance. Earlier, he was named an Outstanding Master Graduate by the Shandong Provincial Education Department. His academic excellence was further acknowledged with the National Scholarship from the Ministry of Education. He also won First Prize in Mathematical Modeling at the provincial level. These awards demonstrate his consistent academic excellence, problem-solving skills, and innovative thinking across his academic journey.

Publication Top Notes

Mr. Qi Sun has contributed to several high-impact journals, with work addressing e-commerce supply chains, risk management, and sustainable operations.

  1. Title: To business or to consumer? Strategic business model selection under competition. IEEE Transactions on Engineering Management.
    Year: 2025.

  2. Title: Information sharing in a dual channel with agency-selling platform. International Transactions in Operational Research.
    Year: 2025

  3. Title: Strategic selling agreement and information management under leakage in an e-commerce supply chain, Electronic Commerce Research and Applications.
    Year: 2023

  4. Title: Decentralized supply chains under random price-dependent demand. Mathematical Problems in Engineering.
    Year: 2020

  5. Title: Optimal pricing in mass customization supply chains with risk-averse agents and retail competition.
    Year: 2019

  6. Title: Research on social responsibility investment and pricing strategy of supply chain enterprises based on risk preference. Operations Research and Management Science.
    Year: 2021

  7. Title: Research on carbon reduction optimization strategy and coordination mechanism. Operations Research and Management Science.
    Year: 2021

Conclusion

Mr. Qi Sun exemplifies the qualities of an emerging scholar, blending academic excellence with impactful research. His contributions to supply chain management, particularly in the areas of disruptive technologies, sustainable practices, and risk management, have already gained international recognition through publications, presentations, and funded projects. His strong academic foundation, international collaboration experience, and consistent record of awards highlight his dedication and innovative approach. With a promising trajectory, Mr. Qi Sun stands as a worthy candidate for recognition, contributing significantly to both academia and practice in the field of supply chain and operations management.

Jingfeng Dong | Decision Science | Best Researcher Award

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Dr. Jingfeng Dong | Decision Science | Best Researcher Award

 Lecturer at Northeast Forestry University, China

Dong Jingfeng is a seasoned academic and professional in the field of logistics and supply chain management with over two decades of experience. Currently serving as a lecturer at the Department of Logistics Engineering, Northeast Forestry University, he has combined academic prowess with practical industry insights to make significant contributions to the development and optimization of supply chain systems in China. With international experience as a visiting scholar at the University of Texas at Dallas and several years of part-time programming roles in the logistics software sector, Dong has effectively bridged the gap between theory and practice. His extensive research spans reverse logistics, pricing models in closed-loop supply chains, and energy-saving simulations, establishing him as a respected voice in logistics innovation and strategic planning.

Profile

Scopus

Education

Dong holds a PhD in Mechanical and Electronic Engineering from the Harbin Institute of Technology (2008), where he also completed his Master’s degree in Technical Economics and Management in 2002. He began his academic journey with a Bachelor’s degree in Thermal Engineering from Harbin University of Science and Technology in 1996. This solid educational foundation has equipped him with the technical and economic understanding necessary for tackling complex logistics challenges and has shaped his analytical approach to logistics systems design and optimization.

Experience

Dong’s professional journey spans more than 20 years, blending academic instruction with real-world logistics planning and software development. He began his career as a designer in the industrial furnace field with Northeast Light Alloy Co., Ltd, gaining crucial hands-on experience in engineering operations. From 2003 to 2005 and again from 2009 to the present, he worked part-time as a programmer for Harbin-based companies, integrating software capabilities with logistics solutions. Since 2008, he has served as a full-time lecturer at Northeast Forestry University, where he teaches and mentors future logistics engineers. His international tenure as a visiting scholar in the United States further broadened his perspective on global logistics systems, enabling cross-border collaboration and comparative research on logistics strategies.

Research Interest

Dong’s research interests lie primarily in logistics system planning, supply chain management, and closed-loop logistics operations. He focuses on pricing decisions and strategic planning under uncertainty, especially in reverse logistics systems and energy-efficient logistics park design. His work frequently integrates system dynamics modeling, optimization algorithms, and multi-criteria decision-making techniques such as the grey correlation TOPSIS method. Through his research, Dong aims to improve sustainability and cost-efficiency in logistics systems while addressing modern challenges such as customer perception, return rate variability, and recycling quality.

Award

Throughout his career, Dong has earned recognition for his innovative contributions to logistics engineering. His selection as a visiting scholar at the University of Texas at Dallas is a testament to his international reputation and academic excellence. His sustained research output and collaboration in top-tier journals further underscore his impact on the field. Additionally, his dual roles in academia and industry have often been highlighted by his institution as exemplary in fostering practical knowledge and real-world problem-solving skills in logistics.

Publication

Dong has authored several influential publications in respected journals, reflecting his diverse research in logistics and operations management. Key publications include:

  1. “Research on closed-loop supply chain pricing decision-making under uncertainty of customer perceived value and recycling quality,” Computer Integrated Manufacturing Systems, 2021 – cited in numerous studies on pricing strategies in reverse logistics.

  2. “Pricing and strategy selection in a closed-loop supply chain under demand and return rate uncertainty,” 4OR-Q Journal of Operations Research, 2022 – widely referenced for integrating uncertainty in closed-loop systems.

  3. “Optimization model of multi-echelon reverse logistics network design for production return,” Computer Integrated Manufacturing Systems, 2008 – foundational work in reverse logistics network optimization.

  4. “Inventory control model based on external and interior reverse logistics,” Journal of Harbin Institute of Technology (New Series), 2009 – cited for its approach to dual-source inventory control.

  5. “A Study on System Dynamics Simulation of Energy-saving System in Logistics Parks,” Forest Engineering, 2012 – contributed to sustainability modeling in logistics.

  6. “Research on site selection decision of distribution type logistics park based on the grey correlation TOPSIS method,” 2012 International Conference on Intelligent Systems Design and Engineering Applications – known for its practical application of decision-making models in logistics infrastructure.

Additional collaborative research and conference contributions further bolster his profile in quantitative logistics analysis.

Conclusion

Dong Jingfeng stands out as a scholar who seamlessly integrates academic research with practical industry application. His dedication to advancing logistics systems through evidence-based models and simulation tools has contributed significantly to both educational and operational aspects of supply chain management in China. With a strong international outlook, continuous research output, and a commitment to mentoring the next generation of engineers, Dong exemplifies the qualities worthy of recognition in an academic and professional award setting. His career reflects a consistent pursuit of innovation, efficiency, and sustainability in logistics, making him a compelling candidate for this nomination.