Yanjun Xu | Blockchain | Best Researcher Award

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Dr. Yanjun Xu | Blockchain | Best Researcher Award

Senior Engineer at Tongji University, China

Yanjun Xu is a Senior Engineer and current Ph.D. candidate at Tongji University, Shanghai. With a strong foundation in operating systems and high-performance computing, he has contributed to advancing software-hardware co-simulation in robotics and optimizing kernel compilation processes. His work spans research, development, and practical innovation in virtual simulation and blockchain-integrated educational tools.

🔹Professional Profile:

Orcid Profile

🎓Education Background

  • Bachelor’s Degree – Ocean University of China, 2010

  • Master’s Degree – Xi’an Polytechnic University, 2013

  • Ph.D. Candidate – Tongji University

💼 Professional Development

Yanjun Xu currently serves as a Senior Engineer at Tongji University. He has been actively involved in high-precision software and hardware co-simulation for robot development and has led virtual simulation projects. His work includes kernel-level system optimization, compiler enhancement, and integration of emerging technologies in real-world applications.

🔬Research Focus

  • Operating Systems

  • High-Performance Computing

  • Robotic Simulation

  • Compiler Optimization

  • Blockchain Applications in Education

📈Author Metrics:

  • Citation Index: 80

  • Books Published: 1

    • ISBN: 978-7-115-55608-0

  • Key Publications (SCI/Scopus):

    • Collaborative Motivation Framework Leveraging Similar Interest Behavior in Semantic Web Applications

    • CGNet: Improving Contour-guided Capability for RGB-D Semantic Segmentation

    • GANet: Geometry-aware Network for RGB-D Semantic Segmentation

    • A Blockchain-Based Certificate Management System for Online Education

🏆Awards and Honors:

  • Active Member, Shanghai Blockchain Association

  • Contributor to the Open Atom Foundation Community

  • Recognized for contributions to open-source compiler development and system optimization

📝Publication Top Notes

📝 1. A Two-Way Dynamic Adaptive Pricing Resource Allocation Model Based on Combinatorial Double Auctions in Computational Network

  • Journal: Computer Communications

  • Publication Date: April 2025

  • Type: Journal Article

  • DOI: 10.1016/j.comcom.2025.108170

  • Contributors: Yanjun Xu, Chunqi Tian, Wei Wang, Lizhi Bai, Xuhui Xia

  • Source: Crossref

  • Summary:  This paper proposes a two-way dynamic adaptive pricing model for resource allocation using a combinatorial double auction mechanism in computational networks. The model is designed to handle the complexity of multi-party bidding and resource matching efficiently. By incorporating adaptive pricing strategies, the system dynamically balances supply and demand in real time, improving overall allocation efficiency. The method shows promising performance in cloud and edge computing scenarios, especially where resources are heterogeneously distributed and demand is volatile.

📝 2. Collaborative Motivation Framework Leveraging Similar Interest Behavior in Semantic Web Applications

  • Journal: International Journal on Semantic Web and Information Systems (IJSWIS)

  • Publication Date: December 28, 2024

  • Type: Journal Article

  • DOI: 10.4018/IJSWIS.365912

  • Contributors: Yanjun Xu, Chunqi Tian, Yaoru Sun, Haodong Zhang

  • Source: Crossref

  • Summary:  This research introduces a collaborative motivation framework that enhances user engagement in semantic web platforms by leveraging similar interest behavior. The proposed system models semantic relevance and behavioral similarity to personalize recommendations and group formation. This approach is particularly beneficial in social knowledge-sharing systems and e-learning platforms, where collaborative filtering alone may fall short. The framework shows strong potential for increasing user satisfaction and platform interactivity.

Conclusion:

Dr. Yanjun Xu exhibits all the hallmarks of an emerging global research leader. His technical depth, innovation in blockchain and systems research, publication record, and active community engagement make him a strong contender for the Best Researcher Award.

He bridges practical engineering challenges with advanced academic research, particularly in virtual simulation, semantic web systems, and blockchain-integrated education technologies. With continued growth in international collaborations and broader dissemination of his applied research, Dr. Xu is on a clear path to becoming a thought leader in computational systems and blockchain innovation.

✅ Recommendation: Highly suitable for the Best Researcher Award.

Zahra Seyedzadeh | Supply chain | Best Researcher Award

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Ms. Zahra Seyedzadeh | Supply chain | Best Researcher Award

Zahra Seyedzadeh at Iran university of science and technology, Iran.

Zahra Sadat Seyedzadeh is a dedicated researcher and analyst specializing in industrial engineering, optimization, and systems analysis. She has contributed significantly to research projects in supply chain design, emergency medical services, and machine learning applications. As a distinguished researcher under Iran’s National Elites Foundation, she has been involved in impactful studies on sustainable supply chains, data analytics, and decision-making techniques.

Professional Profile:

Scopus

Education Background

  • Ph.D. in Industrial Engineering (Optimization & Systems Analysis) – Iran University of Science and Technology (2021–Present, Exceptional Talent Admission, GPA: 18.86/20)
  • M.Sc. in Industrial Engineering (Optimization & Systems Analysis) – Iran University of Science and Technology (2017–2019, GPA: 17.79/20)
  • B.Sc. in Industrial Engineering – Ershad University (2013–2017, GPA: 18/20)

Professional Development

Zahra has gained diverse experience across research and industry. She interned at the Institute for Research and Planning in Commerce and served as an Analyst at the Customs Administration of Iran. Recognized as a Distinguished Researcher under the Shahid Ahmadi Roshan Program, she has actively contributed to research and planning initiatives in commerce, logistics, and industrial systems.

Research Focus

Her research focuses on supply chain optimization, decision-making techniques, emergency medical services network design, data mining applications, and machine learning in supply chain forecasting. She has worked extensively on designing robust and sustainable supply chain networks under uncertainty, ranking suppliers, and preprocessing methods for diverse data types.

Author Metrics:

  • Publications in High-Impact Journals, including Science of the Total Environment (IF: 8.2, Q1) and Journal of Industrial and Systems Engineering (Q3)
  • Conference Presentations, including the 17th Iranian International Industrial Engineering Conference on emergency medical services and supply chain disruption management
  • Bibliometric Analysis Expertise using VOSviewer and CiteSpace

Awards and Honors:

  • Distinguished Researcher, Shahid Ahmadi Roshan Program, Iran’s National Elites Foundation
  • Exceptional Talent Admission, Ph.D. Program, Iran University of Science and Technology\

Publication Top Notes

1. Towards a Sustainable Viticultural Supply Chain under Uncertainty: Integration of Data Envelopment Analysis, Artificial Neural Networks, and a Multi-Objective Optimization Model

  • Journal: Science of the Total Environment (Impact Factor: 8.2, Q1)
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli, Ehsan Dehghani
  • Publication Year: 2025
  • Abstract: This study integrates data envelopment analysis (DEA), artificial neural networks (ANNs), and a multi-objective optimization model to develop a sustainable viticultural supply chain under uncertainty. It provides a robust framework for improving efficiency, resilience, and environmental sustainability in the wine industry.

2.  A Robust Scenario-Based Model for Locating Emergency Medical Services Bases

  • Journal: Journal of Industrial and Systems Engineering (Impact Factor: 0.694, Q3)
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli, Ehsan Dehghani
  • Abstract: This research proposes a robust scenario-based model for optimizing emergency medical services (EMS) base locations, addressing uncertainty, demand fluctuations, and resource allocation efficiency to enhance emergency response times and service coverage.

3.  Emergency Medical Services Network Design under Uncertainty

  • Conference: 17th Iranian International Industrial Engineering Conference
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli, Saeed Yaghoubi
  • Abstract: The study focuses on designing a resilient EMS network, incorporating stochastic demand modeling and robust optimization techniques to improve emergency response effectiveness in unpredictable environments.

4. Emergency Medical Services Supply Chain Network Design and Backup Services under Disruption

  • Conference: 17th Iranian International Industrial Engineering Conference
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli
  • Abstract: This paper examines EMS network vulnerabilities and proposes a backup service strategy to ensure continuity of care and resource allocation in cases of service disruptions due to disasters or infrastructure failures.

Conclusion

Zahra Sadat Seyedzadeh is a strong candidate for a Best Researcher Award, given her exceptional research output, interdisciplinary expertise, and recognized academic achievements. She has demonstrated high-impact research in supply chain optimization, EMS design, and machine learning applications, with publications in top-tier journals.

To further strengthen her research profile, she could focus on international collaborations, real-world applications of her models, and leadership roles in large research projects. Overall, her contributions to industrial engineering and systems optimization make her a highly deserving candidate for the award.