Kebiao Yuan | Strategic Decision-Making | Best Researcher Award

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Dr. Kebiao Yuan | Strategic Decision-Making | Best Researcher Award 

Lecturer at Ningbo University of Technology | China 

Dr. Kebiao Yuan is a scholar specializing in logistics engineering and transportation management. He completed his doctoral studies in logistics engineering and management and holds a master’s degree in transportation planning and management, along with a bachelor’s degree in traffic engineering. His research focuses on port cluster development, collaborative governance, sustainable logistics, and the integration of digital technologies in supply chains. Throughout his academic career, he has actively contributed to numerous national and provincial research projects, including studies on regional port integration, air pollutant emission governance, port cooperation mechanisms, and the modernization of China’s port and shipping industries. Yuan’s work has accumulated 33 citations across 30 documents, with an h-index of 4, underscoring his growing influence in the field of logistics and transportation research. His work often employs evolutionary game theory, bibliometric analysis, and system modeling to address challenges in transportation planning, port governance, and supply chain resilience. In addition to research, he has gained practical experience through internships in transportation planning and urban design, contributing to projects in public transport optimization, highway ecological zones, tourism passenger flow forecasting, and rural revitalization. Yuan has published extensively as a first author or corresponding author in leading journals, including Transport Policy, Sustainability, Mathematics, Ocean & Coastal Management, and Transportation Research Record, with his research covering port cooperation, emission reduction, infrastructure effects on urban growth, and sustainable logistics practices. His contributions have earned recognition in academic competitions and scholarships, reflecting both his research excellence and commitment to advancing sustainable and collaborative approaches in transportation and port logistics.

Profiles : Scopus | ORCID 

Featured Publications : 

Yuan, K., Xu, X., Xu, Z., & Fu, H. (2025). Research on the impact mechanism of digital technology on the new-quality productivity of port logistics. PLOS ONE.

Xue, C., Chao, Y., Xie, S., & Yuan, K. (2025). Will road infrastructure become the new engine of urban growth? A consideration of the economic externalities. Sustainability, 17(15), 6813.

Xue, C., Chao, Y., Xie, S., & Yuan, K. (2025). The health effects of economic growth: Evidence from PM2.5-attributable mortality in China. Economies, 13(7), 192.

Feng, X., Chen, Y., Pan, H., Chao, Y., Yuan, K., & Yue, Z. (2025). Inter-port relationships management: A bibliometric analysis and a systematic review of influencing factors of port co-opetition patterns. Ocean & Coastal Management, 265, 107656.

Yuan, K., Ma, L., & Wang, R. (2025). Research on collaborative governance mechanism of air pollutant emissions in ports: A tripartite evolutionary game analysis with evidence from Ningbo-Zhoushan Port. Mathematics, 13(12), 2025.

Reza Khalili | Strategic Decision-Making | Best Researcher Award

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Mr. Reza Khalili | Strategic Decision-Making | Best Researcher Award 

Research Assistant at Stony Brook University | United States 

Mr. Reza Khalili is a graduate student in Electrical and Computer Engineering at Stony Brook University, where he is pursuing a Ph.D. in Electrical Engineering with a strong academic record. His educational background also includes a master’s degree in Electrical Engineering from Amirkabir University of Technology and a bachelor’s degree in Electrical Engineering from the University of Isfahan. His research primarily focuses on power systems optimization, renewable energy integration, electricity markets, and the application of advanced computational and machine learning methods in energy systems. His scholarly impact is reflected in 81 citations across 78 documents, with 6 publications and an h-index of 4. Khalili has contributed to several peer-reviewed journals and conferences, publishing impactful works on topics such as robust multi-objective optimization for electricity markets, socio-economic energy hub design, peer-to-peer energy trading, and uncertainty management in renewable energy integration. His co-authored works have appeared in respected journals including Applied Energy, Journal of Energy Storage, and Energy & Buildings, and he has contributed a book chapter published by Taylor & Francis. His conference papers include research on security-constrained optimal power flow and distribution network resilience, one of which was recognized as a best paper finalist at IEEE SmartGridComm. In his academic career, Khalili has gained valuable research experience as a graduate research assistant, working on advanced optimization techniques, contingency prediction in power systems, and uncertainty quantification methods.

Profiles : Scopus | ORCID | Google Scholar 

Featured Publications: 

Khalili, R., Khaledi, A., Marzband, M., Nematollahi, A. F., Vahidi, B., & Siano, P. (2023). Robust multi-objective optimization for the Iranian electricity market considering green hydrogen and analyzing the performance of different demand response programs. Applied Energy, 334, 120737.

Darvishi, A., Ranjbar, B., Gharibi, R., Khalili, R., & Dashti, R. (2024). Multi-objective optimization of a socio-economic energy hub with demand response program and considering customer satisfaction. Journal of Energy Storage, 100, 113624.

Gharibi, R., Khalili, R., Vahidi, B., Nematollahi, A. F., Dashti, R., & Marzband, M. (2025). Enhancing energy hub performance: A comprehensive model for efficient integration of hydrogen energy and renewable sources with advanced uncertainty management strategies. Journal of Energy Storage, 107, 114948.

Gharibi, H., Gharibi, R., Khalili, R., Dashti, R., Marzband, M., & Rawa, M. (2025). Optimizing multi-objective peer-to-peer energy trading in green homes: Robust strategies to address non-probabilistic uncertainty using IGDT with integrated demand response. Energy and Buildings, 116435.

Gharibi, R., Vahidi, B., Dashti, R., & Khalili, R. (n.d.). From electrons to solutions: Power-to-X strategies for energy systems integration. In Power-to-X in regional energy systems (pp. 201–227). Taylor & Francis.

Blessing Guembe | Innovation Strategy | Best Researcher Award

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Dr. Blessing Guemb – Innovation Strategy – Best Researcher Award

 

University of Milano | Italy

Profiles 

Scholar

📍Current Position

Since April 2024, he has been serving as a Research Fellow at the University of Milan. In this role, she focuses on developing explainable knowledge-based solutions to address critical issues related to privacy and information security. Her research aims to empower users to manage their personal data and access reliable content while safeguarding freedom of expression. She is actively involved in the KURAMi Project under the guidance of Prof. Giovanni Livraga, working on innovative solutions in privacy protection and data security.

📝Publication Achievements 

“Trustworthy Machine Learning Approaches for Cyberattack Detection: A Review” Computational Science and Its Applications – ICCSA 2022 Workshops, doi:10.1007/978-3-031-10548-7_20. “The Emerging Threat of AI-Driven Cyber Attacks: A Review” Applied Artificial Intelligence, 36(1) doi:10.1080/08839514.2022.2037254 “Cloud Applications Management – Issues and Developments. Computational Science and Its Applications – ICCSA 2018 doi:10.1007/978-3-319-951713_54

 

🔍Ongoing Research 

Explainable AI: Developing methods to make AI systems more interpretable and understandable to users. Federated Learning: Enhancing privacy and security in distributed learning environments. Misinformation: Tackling the spread of false information on social media platforms. Privacy: Ensuring that users’ personal data is protected and managed effectively.

 

🔬Research Interests 

Explainable AI: Techniques that make machine learning models transparent and understandable. Federated Learning: Collaborative learning methods that maintain data privacy and security. Misinformation: Strategies to detect and mitigate false information in digital media. Privacy and Security: Protecting personal data and ensuring compliance with privacy regulations.

🎓Academic Background 

Doctor of Philosophy (PhD) in Computer Science Covenant University, 2023 . Master of Science (MSc) in Computer Science
Covenant University, 2019.  Bachelor of Science (BSc) in Computer Science Niger Delta University, 2012

🏆Scholarships and Awards 

Throughout his academic and professional career, Blessing has been recognized for her contributions to computer science and technology. His achievements are indicative of her commitment to advancing knowledge and innovation in her field.

🌐Professional Associations 

Association for Computing Machinery (ACM). IEEE Computer Society . International Association for Privacy Professionals (IAPP)

 📚Training & Workshops 

Advanced Machine Learning Techniques, Federated Learning and Privacy-Preserving Technologies , Cybersecurity and Privacy Protection

🎤Oral Presentations 

He has delivered presentations at numerous conferences and workshops, sharing insights on her research in AI, cybersecurity, and privacy. These presentations have contributed to her reputation as a thought leader in her field.

🧑‍🔬Tasks Completed as a Researcher 

Implemented Federated Learning Models: Developed and deployed federated learning models for healthcare applications. Applied Homomorphic Encryption: Secured research datasets through advanced encryption techniques. Conducted Privacy Risk Assessments: Evaluated privacy risks associated with social media platforms and proposed protective measures.

🚀Success Factors 

His success can be attributed to her dedication to research, her ability to stay abreast of technological advancements, and her collaborative approach to problem-solving..

🧪Publications & Laboratory Experience

His publications highlight her contributions to the fields of machine learning and cybersecurity. Her laboratory experience includes working on innovative projects related to data security, federated learning, and privacy-preserving techniques.

📚Publications: