Associate Professor, Beijing Jiaotong University, China
Zhang Yuyang is a highly competent researcher in the field of AI-driven vehicular and IoT communications, with significant contributions to multipath transmission, network coding, and resource allocation. His rapid career advancement and high-quality publications establish him as a strong candidate for the Best Researcher Award.
Publication Profile
Education :
Doctor of Engineering – Communication and Information Systems
Beijing Jiaotong University, Sep 2015 – Oct 2020
Research Focus:
Zhang Yuyang’s research is centered on Artificial Intelligence applications in IoT, Future Networks, and the Internet of Vehicles. His work focuses on enhancing vehicular communications, multipath transmission efficiency, and secure data offloading using deep learning and reinforcement learning techniques. His contributions significantly improve the reliability, stability, and efficiency of modern communication networks.
Artificial Intelligence in IoT,6G and Future Networks,Vehicular Communications,Multipath Transmission and Edge Computing,Reinforcement Learning and Deep Learning Applications in Networking,Secure and Efficient Data Offloading.Zhang Yuyang is a distinguished researcher contributing significantly to AI-driven network solutions, vehicular communication technologies, and advanced multipath transmission mechanisms.
Awards:
Best Paper Award at IEEE GLOBECOM, 2024,Wiley China Excellent Author Program, 2024,First Prize of the Science and Technology Award of the China Communications Association, 2024
- Zhang Y, Zhao W, Dong P, et al. “Improve the reliability of 6G vehicular communication through skip network coding.” Vehicular Communications, 2022, 33: 100400.
- Zhang X, Zhang Y*, Dong P, et al. “Ta2ls: A traffic-aware multipath scheduler for cost-effective QoE in dynamic HetNets.” IEEE Transactions on Mobile Computing, 2024.
- Qiao W, Zhang Y*, Dong P, et al. “An AI-Enhanced Multipath TCP Scheduler for Open Radio Access Networks.” IEEE Transactions on Green Communications and Networking, 2024.
- Zhang X, Zhang Y*, Dong P, et al. “PPORM: A PPO-assisted packet reordering mechanism of heterogeneous VANETs for enhancing goodput and stability in fog computing.” Vehicular Communications, 2025: 100894.
- Yin C, Zhang Y*, Dong P, et al. “Deep reinforcement learning‐based joint task offloading and resource allocation in multipath transmission vehicular networks.” Transactions on Emerging Telecommunications Technologies, 2024, 35(1).
Given Zhang’s cutting-edge research, publication record, and leadership in AI-driven networking solutions, he is a strong contender for the award. Strengthening funding records, global collaborations, and citation impact would further solidify his nomination.