Dr. Feixiang Li | Computer Science | Best Researcher Award

Senior Eengineer at The 15th Research Institute of China Electronics Technology Corporation, China

Feixiang Li completed his Ph.D. in Computer Science at Beijing University of Technology in June 2020. His doctoral research focused on Mobile Edge Computing and Software Defined Networks, integrating theoretical frameworks with real-world computing challenges. His academic training equipped him with a solid foundation in advanced algorithms, optimization methods, and emerging communication technologies. During his Ph.D., he began publishing in high-impact journals and enaging in collaborative research with leading scholars in the field. His academic journey reflects a strong emphasis on applied research and innovative problem-solving in the domain of network systems and intelligent computing. This solid educational background has not only shaped his technical expertise but also laid the groundwork for his ongoing contributions to both academia and industry. The combination of deep theoretical knowledge and practical insights defines his educational experience and positions him well for leading-edge research in evolving digital infrastructure and smart network systems.

Professional Experience

After earning his Ph.D., Feixiang Li joined the 15th Research Institute of China Electronics Technology Corporation as an engineer in July 2020. His role focused on the development and optimization of network systems, with a particular emphasis on edge computing solutions and SDN architecture. In November 2022, he was promoted to Senior Engineer, reflecting recognition of his technical leadership and innovative contributions. In this capacity, Feixiang has worked on high-impact projects with national relevance, integrating academic research into practical implementations that advance China’s communication technology infrastructure. His experience bridges the gap between academic innovation and industrial application, allowing him to contribute meaningfully to both spheres. With a strong command of evolving digital technologies and hands-on experience in designing and deploying scalable systems, he continues to push the boundaries of what is technically possible in his field. His professional trajectory demonstrates steady growth, leadership, and a commitment to innovation-driven development.

Research Interest

Feixiang Li’s research interests lie at the intersection of Mobile Edge Computing, Software Defined Networks (SDN), and Evolutionary Algorithms. His work addresses critical challenges in network optimization, resource allocation, and intelligent control in dense communication environments. He has published influential studies on computation offloading using game theory and auction-based models, reflecting his expertise in both algorithm design and systems thinking. Feixiang is particularly interested in how emerging network paradigms like SDN and edge computing can be made more efficient and adaptive through intelligent algorithms. His research not only contributes theoretical models but also delivers practical tools for enhancing communication systems in the era of IoT and 5G. These interests position him at the forefront of digital infrastructure innovation. As networks become more complex and data-driven, his work provides scalable, intelligent solutions to meet future demands, reinforcing his role as a vital contributor to the advancement of modern communication technologies.

Award and Honor

While specific individual awards and honors are not listed in the provided resume, Feixiang Li’s track record reflects recognition through peer-reviewed publications in high-impact journals such as IEEE Transactions on Industrial Informatics and IEEE Transactions on Mobile Computing. These publications, often co-authored with respected researchers, indicate scholarly recognition and professional credibility in the field of computer science and communication networks. His promotion to Senior Engineer at a prominent national research institute also suggests internal recognition of his expertise and leadership. Participation in major international conferences and acceptance of his work in top-tier venues serve as further evidence of his standing within the academic and professional community. Although formal awards are not explicitly mentioned, the quality, volume, and impact of his research contributions suggest a strong foundation for future honors and positions him as a valuable candidate for accolades such as the Best Researcher Award or other academic distinctions in technology and engineering.

Conclusion

Feixiang Li is a highly capable researcher and engineer whose work bridges academic innovation and real-world technology implementation. With a strong educational foundation, extensive experience in a national research institute, and a focused research agenda in high-impact areas like edge computing and SDNs, he stands out as a leader in his field. His publications in top-tier journals and his growing professional responsibilities underscore his commitment to advancing the state of digital communication systems. While there is room to expand his global research network and innovation leadership, his current achievements reflect a robust trajectory of growth, influence, and potential. Feixiang’s career exemplifies the integration of theoretical rigor with applied engineering, making him a strong candidate for awards and honors that recognize excellence in research and technological innovation. As he continues to evolve professionally and academically, he is well-positioned to make further meaningful contributions to the future of intelligent networked systems.

Publications Top Notes

1. Title: A Deep Reinforcement Learning-Based Topology Optimisation Method for Distributed Trial Networks

   • Authors: Zhuo Wang, Mingzhe Liu, Feixiang Li, Honglei Yin

   • Year: 2025

   • DOI: 10.1007/978-981-96-5318-8_18

2. Title: A Transformer-GRU-Based Edge Computing Method for Vessel Trajectory Prediction

   • Authors: Yuhao Su, Mingzhe Liu, Feixiang Li, Honglei Yin, Chao Fang

   • Year: 2025

   • DOI: 10.1007/978-981-96-5318-8_54

3. Title: Constant-Time Discrete Gaussian Sampling for Edge Computing Based on DPWGAN

   • Authors: Jingbin Shi, Ning Li, Feixiang Li, Mingzhe Liu, Xige Zhang

   • Year: 2025

   • DOI: 10.1007/978-981-96-5318-8_16

4. Title: Semi-supervised Remote Sensing Image Classification for Edge Computing via Contrastive Learning

   • Authors: Pengquan Liao, Ning Li, Mingzhe Liu, Kai Qu, Feixiang Li, Jinyi Chen

   • Year: 2025

   • DOI: 10.1007/978-981-96-5318-8_49

5. Title: Collaborative Computation Offloading and Resource Management in Space–Air–Ground Integrated Networking

   • Authors: Feixiang Li, Kai Qu, Mingzhe Liu, Ning Li, Tian Sun

   • Journal: Electronics

   • Year: 2024

   • DOI: 10.3390/electronics1310180

6. Title: Intelligent Computation Offloading Mechanism with Content Cache in Mobile Edge Computing

   • Authors: Feixiang Li, Chao Fang, Mingzhe Liu, Ning Li, Tian Sun

   • Journal: Electronics

   • Year: 2023

   • DOI: 10.3390/electronics1205125

7. Title: Auction Design for Edge Computation Offloading in SDN-Based Ultra Dense Networks

   • Authors: Feixiang Li, Haipeng Yao, Jun Du, Chunxiao Jiang, Zhu Han, Yunjie Liu

   • Journal: IEEE Transactions on Mobile Computing

   • Year: 2022

   • DOI: 10.1109/TMC.2020.3026319

8. Title: Stackelberg Game-Based Computation Offloading in Social and Cognitive IIoT

   • Authors: Feixiang Li, Haipeng Yao, Jun Du, Chunxiao Jiang, Yi Qian

   • Journal: IEEE Transactions on Industrial Informatics

   • Year: 2020

   • DOI: 10.1109/TII.2019.2961662

9. Title: Multi-Controller Resource Management for Software-Defined Wireless Networks

   • Authors: Feixiang Li, Xiaobin Xu, Haipeng Yao, Jingjing Wang, Chunxiao Jiang, Song Guo

   • Journal: IEEE Communications Letters

   • Year: 2019

   • DOI: 10.1109/LCOMM.2019.2891527

   • Citations: 18 (Scopus)

10. Title: Bat Algorithm with Principal Component Analysis

    • Authors: Zhihua Cui, Feixiang Li, Wensheng Zhang

    • Journal: International Journal of Machine Learning and Cybernetics

    • Year: 2019

    • DOI: 10.1007/s13042-018-0888-4