石方，女，博士，副教授，硕士生导师。主要研究方向包括人工智能、边缘智能、联邦学习、机器学习，目前已在IEEE Transactions on Mobile Computing、IEEE Transactions on Wireless Communications、IEEE Transactions on Fuzzy Systems、ACM Computing Surveys、IEEE Transactions on Industrial Informatics、计算机研究与发展、软件学报等核心期刊、会议上发表学术论文二十余篇，担任多个期刊会议审稿人。

2019.09-2023.09 华南理工大学 计算机科学与技术 博士

2016.09-2019.06 广州大学 计算机技术 硕士

2012.09-2016.06 海南师范大学 教育技术学 学士

2024.01-至今 华南农业大学 首聘副教授

办公室：华南农业大学数学与信息学院609
邮箱：csshifang@scau.edu.cn

[1]. Shi Fang, Lin Weiwei*, Wang Xiuming, Li Keqin, Zomaya, Albert Y.. The Analysis and Optimization of Volatile Clients in Over-the-Air Federated Learning.  IEEE Transactions on Mobile Computing, 2024, 23(12), 13144-13157. (CCF A, IF：7.7)

[2]. Shi Fang, Lin Weiwei*, Fan Lisheng, Lai Xiazhi, Wang Xiuming. Efficient client selection based on contextual combinatorial multi-arm bandits[J]. IEEE Transactions on Wireless Communications, 2023, 22(8),5265-5277. (JCR-Q1, IF：8.9)

[3]. Shi Fang, Lin Weiwei, Peng Chaoda, Zhong Cankun, Wang Dong, Cheng Mingyue*. Dynamic Client Selection for Over-the-Air Federated Learning Network[J]. IEEE Internet of Things Journal, 2025, doi: 10.1109/JIOT.2024.3523947. (JCR-Q1，IF：8.2)

[4]. Shi Fang, Hu Chunchao, Lin Weiwei*, Fan Lisheng, Huang Tiansheng, Wu Wentai. VFedCS: Optimizing client selection for volatile federated learning[J]. IEEE Internet of Things Journal, 2022, 9(24): 24995-25010. (JCR-Q1，IF：8.2)

[5]. Lin Weiwei, Shi Fang*, Wu Wentai, Li Keqin, Wu Gangxin, MOHAMMED A. A. A taxonomy and survey of power models and power modeling for cloud servers[J]. ACM Computing Surveys, 2020, 53(5): 1-41. (JCR-Q1, IF：23.8) 唯一通信

[6]. Wu Haijie, Lin Weiwei*, Chen Yuehong, Shi Fang*, Shen, Wangbo, Chen, C. L. philip. Adaptive Incremental Broad Learning System Based on Interval Type-2 Fuzzy Set with Automatic Determination of Hyperparameters[J]. IEEE Transactions on Fuzzy Systems. 2025, doi: 10.1109/TFUZZ.2025.3530458. (JCR-Q1, IF：10.7) 共同通信

[7]. Shi Fang, Fan Lisheng, Lai Xiazhi, Chen Yuehong, Lin Weiwei*. A hierarchical caching strategy in content delivery network[J]. Computer Communications. 2021, 179: 92-101. (JCR-Q1)

[8]. Haijie Wu, Weiwei Lin*, Haotong Zhang, Fang Shi, Wangbo Shen, and Keqin Li, Albert Y. Zomaya. Container Scheduling Strategy Based on Image Layer Reuse and Sequential Arrangement in Mobile Edge Computing. IEEE Transactions on Mobile Computing (2025). (CCF A, IF：7.7)

[9]. Shi Fang, Junjuan Xia*, Na, Zhenyu, Liu, Xin, Ding Yunfei, Wang Zhi. Secure probabilistic caching in random multi-user multi-UAV relay networks[J]. Physical Communication, 2019, 32: 31-40. (JCR-Q2)

[10]. Li, Dongdong, Liu Bo, Yang Chunqiao, Shi Fang, Peng, Yunfei, Lin, Weiwei*. K-Core Structure Feature Encoding-Based Enhanced Federated Graph Learning Framework[J]. IEEE Transactions on Emerging Topics in Computational Intelligence. 2025, doi: 10.1109/TETCI.2025.3526278. (JCR-Q1)

[11]. Lin Weiwei, Xiong Chennian, Wu Wentai, Shi Fang, Li Keqin, Xu Minxian. Performance Interference of Virtual Machines: A Survey[J]. ACM Computing Surveys, 2023, 55(12): 1-37. (JCR-Q1)

[12]. Shen Wangbo, Lin Weiwei*, Wu Yulei, Shi Fang, Wu Wentai, Li Keqin. Evolving deep multiple kernel learning networks through genetic algorithms[J]. IEEE Transactions on Industrial Informatics, 2022, 19(2): 1569-1580. (JCR-Q1)

[13]. Zhou Naqin, Lin Weiwei, Feng Wei, Shi Fang, Pang Xiongwen. Budget-deadline constrained approach for scientific workflows scheduling in a cloud environment[J]. Cluster Computing, 2023, 26(3): 1737-1751. (JCR-Q1)

[14]. You Deguang, Lin Weiwei, Shi Fang, Li Jianzhuo, Qi Deyu, Fong Simon. A novel approach for CPU load prediction of cloud server combining denoising and error correction[J]. Computing, 2023: 1-18. (JCR-Q1)

[15]. Lin Weiwei, Xu Yinhai, Liu Bo, Li, Dongdong, Huang, Tiansheng, Shi Fang. Contribution-based Federated. Learning client selection[J]. International Journal of Intelligent Systems, 2022, 37(10): 7235-7260. (JCR-Q1)

[16]. Lin Weiwei, Huang Tiansheng, Li Xin, Shi Fang, Wang, Xiuming, and Hsu, Ching-Hsien. Energy-efficient computation offloading for UAV-assisted MEC: A two-stage optimization scheme[J]. ACM Transactions on Internet Technology, 2021, 22(1): 1-23. (JCR-Q1)

[17]. 林伟伟; 石方; 曾岚; 李董东; 许银海; 刘波. 联邦学习开源框架综述[J]. 计算机研究与发展, 2023, 60(7): 1551-1580. (CCF A中文期刊)

[18]. 李俊祺, 林伟伟, 石方, 李克勤. 基于混合群智能的节能虚拟机整合方法[J]. 软件学报, 2022, 33(11): 3944-3966. (CCF A中文期刊)

[19]. 林伟伟, 石方. 面向不稳定联邦学习场景的客户端选择优化方法及装置，2022.04.，ZL202210426304.9

[20]. 范立生，石方，林晓升，夏隽娟，谭伟强. 一种安全概率缓存策略及其生成方法，2021-3-30, 中国, ZL201810913309.8.

[21]. 林伟伟, 许银海, 石方, 王江涛, 上官栋栋. 面向X86和ARM混合云计算的节能调度系统、方法和存储介质, 2023-5-30, 中国, ZL202110452258.5.