Education

• Ph.D. in Electrical and Computer Engineering
  University of Dayton (UD), Dayton, OH - 2022
• M.S. in Electrical and Computer Engineering
  University of Dayton (UD), Dayton, OH - 2015
• B.S. in Automation
  Dalian JiaoTong University, Dalian, Liaoning, China - 2012

Research Interests

• Next-Generation Networking
• Network Security
• Wireless Communications
• Artificial Intelligence

Representative Publications

Refereed Journals (Under submission):

• Fuhao Li, Daidong Ying, Dalyana Mercado-Perez, Jielun Zhang, Feng Ye, Rose Q. Hu, and Qian Yi, “A Systematic Approach for Simplifying Deep Learning based CSI Feedback Process” under submission, IEEE Transactions on Wireless Communications, 2025.
• Fuhao Li, and Jielun Zhang, "A Comprehensive Study on Lightweight Convolution Techniques for Malicious Traffic Synthesis in Diffusion Models", under submission, IEEE Access, 2025.
• Jielun Zhang, Fuhao Li, and Feng Ye, Towards Quality-Explainable Data Synthesis for AI-based Network Intrusion Detection System, under submission, IEEE Transactions on Network Science and Engineering, 2025.

Refereed Journals (Published/Accepted):

• Fuhao Li and Feng Ye, "Adaptive and Lightweight Network Traffic Classification for Edge Devices," in IEEE Transactions on Green Communications and Networking, doi: 10.1109/TGCN.2022.3165221.
• Jielun Zhang, Fuhao Li and Feng Ye, "Sustaining the High Performance of AI-Based Network Traffic Classification Models," in IEEE/ACM Transactions on Networking, doi: 10.1109/TNET.2022.3203227.
• Jielun Zhang, Fuhao Li, and Feng Ye, "Network traffic clustering with QoS-awareness," in IEEE/CIC China Communications, doi: 10.23919/JCC. 2022.03.015
• Venkat Kumar, Fuhao Li, Feng Ye and G. Subramanyam, "Autonomous Wireless Technology Detection in Seamless IoT Applications," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2022.317362.
• Venkat Kumar, Jiahui Yu, Fuhao Li, Jielun Zhang, Feng Ye, Sanjeevi Karri, and Guru Subramanyam. "Seamless Wireless Communication Platform for Internet of Things Applications." in IEEE Wireless Communications, doi: 10.1109/MWC.006.2200097.

Patent

"Predicting classification labels for bioelectric signals using a neural network." U.S. Patent Application No. 18/609,211.