Ph.D. Student in Industrial Edge Intelligence
Time-Sensitive Networking · Industrial Edge Computing · Distributed RL · Edge LLM/LMM Systems
South China University of Technology · Pengcheng Laboratory
I am a Ph.D. student with the School of Future Technology at South China University of Technology (SCUT), and I also conduct research with the Department of Networked Intelligence at Pengcheng Laboratory.
My research lies at the intersection of deterministic networking and intelligent edge systems. I study how communication, computing, and learning can be jointly designed for industrial workloads that require bounded latency, reliability, fairness, and efficient use of heterogeneous resources.
- Time-Sensitive Networking (TSN): deterministic communication, traffic shaping and scheduling, and industrial AI agent communication
- Industrial edge computing: computation offloading, joint compute-network scheduling, and distributed collaborative control
- Distributed reinforcement learning: multi-agent decision-making for latency-, fairness-, and QoS-aware resource allocation
- Industrial communication systems: containerized virtual PLCs, EtherCAT, DPDK, and real-time packet processing
- Edge AI systems: QoS-aware distributed LLM/LMM inference, heterogeneous batching, pipeline parallelism, and runtime resource protection
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Yingfei Yao, Nan Zhou, Shunchun Yao, Xiaojun Liang, Wenfeng Deng, Chunhua Yang, and Weihua Gui, “Fairness-Aware Deterministic Joint Offloading and Scheduling for Industrial Edge Computing,” IEEE Transactions on Industrial Informatics, 2026. DOI: 10.1109/TII.2026.3654608
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Nan Zhou, Yingfei Yao, Xiaojun Liang, Shunchun Yao, Jiafu Wan, Chunhua Yang, Weihua Gui, and Wen Gao, “Convergence of Reinforcement Learning and Time-Sensitive Networking for Future Industrial AI Agent Communication: Fundamentals, Challenges, and Opportunities,” IEEE Communications Surveys & Tutorials, 2026. DOI: 10.1109/COMST.2026.3690893
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Nan Zhou, Yingfei Yao, Xiaojun Liang, Shunchun Yao, Chunhua Yang, and Weihua Gui, “Optimization and Evaluation of Container-Based EtherCAT Communication in Virtual PLCs,” IEEE Transactions on Industrial Electronics, 2026. DOI: 10.1109/TIE.2026.3670311 Link: https://github.com/morthlee/vplc-realtime-benchmark
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Yingfei Yao, Shunchun Yao, Nan Zhou, Xiaojun Liang, Chunhua Yang, and Weihua Gui, “Distributed Deep Reinforcement Learning Based Deterministic Task Offloading in End-Edge-Cloud Collaborative Computing Networks,” in Cyberspace Simulation and Evaluation, Springer, 2024, pp. 90–103. DOI: 10.1007/978-981-96-4503-9_7
- Edge-computing task scheduling method, apparatus, device, storage medium, and product — CN 118069317 A, first inventor
- Industrial-network latency-error compensation method, apparatus, device, and storage medium — CN 118199778 A, co-inventor
- Network-transmission parameter optimization method, apparatus, electronic device, and storage medium — CN 119629056 A, first inventor
- EdgeCluster-LMM: communication- and QoS-aware distributed inference serving for large multimodal models over heterogeneous IoT edge clusters
- Deterministic multi-flow industrial communication: combining TSN with container-native EtherCAT for virtualized PLCs
- Compute-network co-design: learning-based joint offloading, scheduling, and resource management for industrial edge intelligence
C/C++ · Python · CUDA · DPDK · EtherCAT · TSN · Linux/PREEMPT_RT · Docker · CMake · ZeroMQ · llama.cpp
我是华南理工大学未来技术学院博士研究生，并在鹏城实验室网络智能部开展研究工作。研究聚焦于确定性网络与智能边缘系统的交叉领域，包括时间敏感网络（TSN）、工业边缘计算、分布式强化学习、任务卸载与计算网络协同调度、虚拟化 PLC/EtherCAT，以及异构边缘集群上的大语言模型与多模态大模型分布式推理。
The best way to reach me is through yaoyfbox@163.com.