Xiao Xuefeng is an accomplished researcher and academic affiliated with the Business School at Beijing Information Science and Technology University (BISTU), Beijing, China. At BISTU, a university recognized for its emphasis on information technology, engineering, and interdisciplinary innovation, he contributes to the intersection of business management and data-driven systems

His publication record spans critical areas such as Data Engineering, Energy Systems, and Structural Engineering. On ResearchGate, “Xuefeng Xiao” is credited with eight significant papers and 71 citations, underscoring his active engagement in the academic community. His peer-reviewed works explore advanced topics including vehicular fog computing, D2D communications for content delivery, and traffic-sourced computational frameworks—highlighting his dedication to leveraging emerging data communication paradigms.

Notably, in July 2019, Xiao co-authored two influential papers: “Accelerating Content Delivery via Efficient Resource Allocation for Network Coding Aided D2D Communications” and “JamCloud: Turning Traffic Jams into Computation Opportunities—Whose Time Has Come.” Both works reflect his innovative approach to addressing network efficiency and urban mobility challenges.

Within the IgMin Research community, his author profile has garnered over 3,700 views and 500+ downloads, reaffirming the global reach and impact of his scholarly output . His contributions highlight a growing expertise in harnessing data engineering principles for complex, real-world infrastructure and communication systems.

In summary, Xiao Xuefeng is a forward-thinking scholar whose research straddles data engineering and applied systems—making purposeful strides in integrating theoretical insights with practical technological innovations. His work positions him as a leading voice in his fields within both national and international academic arenas.

Dr. Xiao Xuefeng’s research interests lie at the intersection of data engineering, intelligent communication systems, and energy-efficient network infrastructures. He focuses on emerging technologies such as vehicular fog computing, device-to-device (D2D) communication, and network coding, aiming to improve content delivery and resource allocation in dynamic environments. His work often explores how urban mobility patterns and real-time traffic data can be utilized to optimize computational resources, exemplified by models like JamCloud. He is also interested in edge computing, cloud-based architecture, and the development of scalable algorithms for smart cities and sustainable transportation systems. His current research includes optimizing computational load balancing, minimizing latency in mobile networks, and integrating artificial intelligence in network management. By combining theoretical frameworks with practical applications, Dr. Xiao contributes to the advancement of smart infrastructure, bridging the gap between business systems and data-driven engineering for real-world impact. His interdisciplinary approach supports innovations in business technology and urban informatics.