Educational Background：

• 2006-2010: The Chinese University of Hong Kong, Department of Information Engineering, Doctoral Degree (Full-time)
• 2003-2006: Tsinghua University, Department of Electrical Engineering, Master Degree (Full-time)
• 1999-2003: Xiamen University, Department of Electrical Engineering, Bachelor Degree (Full-time) 

Work Experience：

• 2017-Present: School of Informatics, Xiamen University, Professor
• 2015-2016: School of Information Science and Technology, ShanghaiTech University, Assistant Professor
• 2013-2015: Access Linnaeus Centre, KTH Royal Institute of Technology, Postdoctoral Researcher
• 2011-2013: Institute of Network Coding, The Chinese University of Hong Kong, Postdoctoral Researcher

Fu Liqun, Full Professor of the School of Informatics at Xiamen University, China. She received her Ph.D. Degree in Information Engineering from The Chinese University of Hong Kong and served as a visiting Professor at Stanford University from 2023-2024. Prof. Fu has been elected to national-level youth talent programs. Her research interests are mainly in intelligent networks and network intelligence. She leads key project and general project of NSFC. She has published over 100 papers in top-tier journals and conferences such as IEEE JSAC, IEEE TMC, and IEEE INFOCOM. Cooperation in AI and intelligent networking fields and applications from outstanding students are welcome.

1. Yandong Shi, Lixiang Lian, Yuanming Shi, Zixin Wang, Yong Zhou, **Liqun Fu**, Lin Bai, Jun Zhang, and Wei Zhang, “Machine Learning for Large-Scale Optimization in 6GWireless Networks,” IEEE Communications Surveys and Tutorials, vol. 25, no. 4, pp. 2088-2132, fourth quarter, 2023. (SCI Q1, DOI: [10.1109/COMST.2023.3300664](https://doi.org/10.1109/COMST.2023.3300664))
2. Zhibin Wang, Jiahang Qiu, Yong Zhou*, Yuanming Shi, **Liqun Fu***, Wei Chen, and Khaled B.Letaief, “Federated Learning via Intelligent Reflecting Surface,” IEEE Transactions on Wireless Communications, vol. 21, no. 2, pp. 808-822, Feb. 2022 (SCI Q1, ESI highly cited paper, DOI: [10.1109/TWC.2021.3099505](https://doi.org/10.1109/TWC.2021.3099505)).
3. Jingwen Tong, Zhenzhen Chen, **Liqun Fu***, Jun Zhang and Zhu Han, “From Learning to Analytics: Improving Model Efficacy with Goal-Directed Client Selection,” IEEE Transactions on Mobile Computing, vol. 23, no. 12, pp. 10803-10817, Dec. 2024. (SCI Q1, DOI: [10.1109/TMC.2024.3383038](https://doi.org/10.1109/TMC.2024.3383038))
4. Lizhao You, Xinbo Zhao, Rui Cao, Yulin Shao, and **Liqun Fu***, “Broadband Digital Over-the-Air Computation for Wireless Federated Edge Learning,” IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 5212-5228, May 2024. (SCI Q1, DOI: [10.1109/TMC.2023.3304652](https://doi.org/10.1109/TMC.2023.3304652))