Deqian Fu | Data Science and Analytics | Best Researcher Award

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Prof. Dr. Deqian Fu | Data Science and Analytics | Best Researcher Award

Professor | Linyi University | China

Prof. Dr. Deqian Fu is a prominent researcher at Linyi University, China, with a strong focus on logistics, data exchange, and trust management in supply chain and intermodal transport systems. His research explores innovative methods for secure and efficient data sharing in the logistics industry, integrating advanced technologies such as blockchain, edge computing, and ontology-based frameworks. Fu has made notable contributions in developing trusted data access control mechanisms and non-intrusive data exchange models that enhance collaboration and operational efficiency across complex logistics networks. He has authored 39 publications, which have collectively garnered 127 citations, reflecting the growing impact of his work in the fields of applied sciences and industrial informatics. His research outputs demonstrate a commitment to advancing the intersection of information technology and logistics, emphasizing both theoretical development and practical applications. With an h-index of 7, Fu’s scholarly contributions have been recognized for their relevance and innovation, particularly in promoting secure and intelligent data-sharing frameworks within the logistics sector. Selected works include “Trusted Data Access Control Based on Logistics Business Collaboration Semantics” in Applied Sciences (2024), alongside conference papers such as “Data Exchange and Sharing Framework for Intermodal Transport Based on Blockchain and Edge Computing” and “Trusted Non-intrusive Data Exchange based on Ontology in Logistics Industry,” underscoring his focus on reliable, technology-driven logistics solutions.

Profiles : ORCID | Scopus 

Featured Publications

1. Wang, W., Li, Q., Jiang, Z., Fu, D., & Camacho, D. (2025). An efficient framework for general long-horizon time series forecasting with Mamba and diffusion probabilistic models. Engineering Applications of Artificial Intelligence.

2.Liu, Z., Shi, Z., Wang, W., Kong, R., Fu, D., & Qiu, J. (2025). Research on data ownership and controllable sharing schemes in the process of logistics data flow.

3.Wang, L., Zhang, X., Xu, L., Fu, D., & Qiu, J. (2024). Data exchange and sharing framework for intermodal transport based on blockchain and edge computing. In Communications in Computer and Information Science. Springer.

4.Zhang, X., Jing, C., Chen, Y.-C., Wang, L., Xu, L., & Fu, D. (2024). Trusted data access control based on logistics business collaboration semantics.

5.Zhang, X., Wang, L., Xu, L., & Fu, D. (2023). A distributed logistics data security sharing model based on semantics and CP-ABE. In Proceedings of the ACM International Conference (pp. 1–8).

Jingsheng Feng | Decision Sciences | Best Paper Award

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Mr. Jingsheng Feng | Decision Sciences | Best Paper Award

Research Assistant | Hefei University of Technology | China

Dr. Jingsheng Feng, a distinguished researcher at Hefei University of Technology, China, focuses on advanced logistics network optimization, supply chain resilience, and intelligent decision-making systems. His research integrates mathematical modeling, fuzzy logic, and multi-objective optimization to tackle complex challenges in customized logistics and industrial engineering. Notably, his work published in Computers & Industrial Engineering presents a reliable logistics network design model incorporating demand sensitivity to correlated disruptions, enhancing system robustness under uncertainty. In the International Journal of Systems Science: Operations & Logistics (, he co-developed disruption response strategy models for supplier selection and order allocation to support firms in maintaining operational stability during disruptions. His study in Expert Systems with Applications proposed fuzzy multi-objective team decision models for customer order decoupling point (CODP) and supplier selection, facilitating collaborative and data-driven decision-making in customized logistics supply chains. Additionally, his  work in Computers & Industrial Engineering explored battery swapping service network deployment, addressing behavioral factors such as driver range anxiety and impatience. Through his interdisciplinary contributions, Dr. Feng bridges theory and practice in logistics and supply chain engineering, promoting demand responsiveness, risk mitigation, and intelligent system design to advance sustainable, adaptive, and human-centered logistics strategies for modern industrial ecosystems. Her research impact is evident from 15 citations across 4 documents with an h-index of 2.

Profiles : ORCID | Scopus 

 

Featured Publications


1 .Feng, J., Hu, X., Xu, L., Luo, S., & Chen, J. (2025). Reliable logistics network design joint optimization problem applying demand sensitivity to correlated disruptions. Computers & Industrial Engineering.

2. Xu, L., Hu, X., Wu, Z., Luo, S., Feng, J., & Zhang, X. (2025). Disruption response strategy models for supplier selection and order allocation in customised logistics service supply chain. International Journal of Systems Science: Operations & Logistics.

3. Xu, L., Hu, X., Zhang, Y., Feng, J., & Luo, S. (2024). A fuzzy multiobjective team decision model for CODP and supplier selection in customized logistics service supply chain. Expert Systems with Applications, 213, 121387.

4. Hu, X., Zhang, X., Xu, L., Feng, J., & Luo, S. (2024). The battery swapping service network deployment problem: Impact of driver range anxiety and impatience. Computers & Industrial Engineering, 172, 110189.