梦旅人的科研之家

My name is Jianping Cai, an Assistant Professor in Faculty of Data Science at City University of Macau. I hold a Ph.D. from Fuzhou University, awarded in 2024, where I also earned my Master's degree in 2016. My academic journey has been driven by a relentless pursuit of knowledge and innovation in the realm of data science.

My research explores the forefront of modern data science, with a focus on critical areas such as differential privacy, federated learning, matrix analysis and optimization theory, big data technologies, recommender systems, and the mathematical underpinnings of machine learning. These disciplines form the foundation of my commitment to advancing both theoretical and practical understanding in the field.

With a deep passion for bridging theoretical concepts with real-world applications, I am dedicated to fostering innovation that transcends the boundaries of academia and industry alike. For further insights into my work, I invite you to visit my faculty page: City University of Macau.

My Papers

[1] J. Cai, Q. Ye, H. Hu, X. Liu, and Y. Fu, "Boosting Accuracy of Differentially Private Continuous Data Release for Federated Learning," in IEEE Transactions on Information Forensics and Security, doi: 10.1109/TIFS.2024.3477325. [Paper][Proof][Code]

[2] J. Cai, X. Liu, Q. Ye, Y. Liu and Y. Wang, "A Federated Learning Framework Based on Differentially Private Continuous Data Release," in IEEE Transactions on Dependable and Secure Computing, doi: 10.1109/TDSC.2024.3364060. [Paper][Proof][Code]

[3] J. Cai, X. Liu, J. Li and K. -K. R. Choo, "Differentially Private Non-Negative Consistent Release for Large-Scale Hierarchical Trees," in IEEE Transactions on Dependable and Secure Computing, vol. 21, no. 1, pp. 388-402, Jan.-Feb. 2024, doi: 10.1109/TDSC.2023.3253520. [Paper][Proof][Code]

[4] J. Cai, X. Liu, J. Li and S. Zhang, "Generation matrix: An embeddable matrix representation for hierarchical trees," Theoretical Computer Science, doi: 10.1016/j.tcs.2023.114180. [Paper][Award][Slide]

[5] Jianping Cai, Ximeng Liu, Zhiyong Yu, Kun Guo, Jiayin Li, "Efficient Vertical Federated Learning Method for Ridge Regression of Large-Scale Samples", IEEE Transactions on Emerging Topics in Computing(TETC), 2022. https://doi.org/10.1109/TETC.2022.3215986. [Paper][Code]

[6] Cai J P, Lei Y Q, Chen M M, et al. Efficient solution of SVD recommendation model with implicit feedback (in Chinese). Sci Sin Inform, doi: 10.1360/SSI-2019-0107.
蔡剑平, 雷蕴奇, 陈明明, 等. 带有隐式反馈的SVD推荐模型高效求解算法. 中国科学: 信息科学, doi: 10.1360/SSI-2019-0107 [Paper] [Code] [Report]

[7] Jianping CAI, Ximeng LIU, Jinbo XIONG, Zuobin YING, Yingjie WU. Approximation method of multiple consistency constraint under differential privacy[J]. Journal on Communications, 2021, 42(6): 107-117.
蔡剑平, 刘西蒙, 熊金波, 应作斌, 吴英杰. 差分隐私下多重一致性约束问题的逼近方法[J]. 通信学报, 2021, 42(6): 107-117. [Paper]

[8] Cai, J., Liu, Y., Liu, X., Li, J. & Zhuang, H. (2023). Privacy-Preserving Federated Cross-Domain Social Recommendation. In: Goebel, R., Yu, H., Faltings, B., Fan, L. & Xiong, Z. (Eds.). Trustworthy Federated Learning. Lecture Notes in Artificial Intelligence, vol. 13448, pp. 145-160. Springer, Cham. https://doi.org/10.1007/978-3-031-28996-5_11
Jianping Cai, Yang Liu, Ximeng Liu, Jiayin Li, Hongbin Zhuang, "Privacy-Preserving Federated Cross-Domain Social Recommendation", FL-IJCAI'22, 2022. [Paper] [PDF]

[9] Jianping Cai, Ximeng Liu, and Yingjie Wu. 2020. SVM Learning for Default Prediction of Credit Card under Differential Privacy. In Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice (PPMLP'20). Association for Computing Machinery, New York, NY, USA, 51–53. DOI:https://doi.org/10.1145/3411501.3419431. [Paper]

[10] CAI Jianping, WU Yingjie, WANG Xiaodong. Method Based on Matrix Mechanism for Differential Privacy Continual Data Release. Journal of Frontiers of Computer Science and Technology, 2016, 10(4): 481-494.DOI:10.3778/j.issn.1673-9418.1507074.
蔡剑平，吴英杰，王晓东. 基于矩阵机制的差分隐私连续数据发布方法[J]. 计算机科学与探索, 2016, 10(4): 481-494.DOI:10.3778/j.issn.1673-9418.1507074. [Paper] [Code]

[11] J. Cai, M. Chen, S. Zhang, C. Hong and Y. Lu, "A Fast Algorithm for Solving a Kind of Gauss Hypergeometric Functions in Wireless Communication Based on Pfaff Transformation," 2019 International Conference on Networking and Network Applications (NaNA), Daegu, Korea (South), 2019, pp. 85-89, doi: 10.1109/NaNA.2019.00024. [Paper] [Code]

[12] Puwei Lian, Xiao Ke, Zhou Tan, Jianping Cai, and Ximeng Liu. Achieving Zero‑Glance Unlearning with Data‑Free Inversion and Selective Parameters Suppression. In Proceedings of the 2025 IEEE International Conference on Multimedia and Expo (ICME ’25). IEEE, Article 3084, 9 pages.
[Paper]

[13] Changxiang Zhao, Jianping Cai, Ximeng Liu, Qi Zhong, and Zuobin Ying. A Speech Steganography Privacy Protection Scheme Based on Secret Sharing, 2025. International Journal of Network Security (IJNS). In press. [Paper]

[14] Yongjian Jia, Jianping Cai, and Ximeng Liu. Entropy‑Guided Tree of Thoughts: A Dynamic Approach to Diverse Path Generation in LLM Reasoning. In Proceedings of the 2025 3rd International Conference on Big Data and Privacy Computing (BDPC ’25). IEEE, In press.

[15] X. You, X. Liu, X. Lin, Cai, J. and S. Chen, "Accuracy Degrading: Towards Participation-Fair Federated Learning," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2023.3238038. [Paper]

[16] Xianyao You, Ximeng Liu, Nan Jiang, Jianping Cai, Zuobin Ying, "Reschedule Gradients: Temporal Non-IID Resilient Federated Learning", IEEE Internet of Things Journal, 2022. https://doi.org/10.1109/JIOT.2022.3203233. [Paper]

[17] ZHANG Shuangyue, CAI Jianping, TIAN Feng, WU Zhenqiang. Trajectory Flow Releasing Method with Consistency Constraint under Differential Privacy. Journal of Frontiers of Computer Science and Technology, 2018, 12(12): 1903-1913.DOI:10.3778/j.issn.1673-9418.1710041.
张双越，蔡剑平，田丰，吴振强. 差分隐私下满足一致性的轨迹流量发布方法[J]. 计算机科学与探索, 2018, 12(12): 1903-1913.DOI:10.3778/j.issn.1673-9418.1710041. [Paper] [Code]

[18] Sun Lan, Jinxin Hong, Junya Chen, Jianping Cai, Yilei Wang, "Equation Chapter 1 Section 1 Differentially Private High-Dimensional Binary Data Publication via Adaptive Bayesian Network", Wireless Communications and Mobile Computing, vol. 2021, Article ID 8693978, 11 pages, 2021. https://doi.org/10.1155/2021/8693978. [Paper]

[19] Chen Shaoquan, CAI Jianping, Sun Lan. Differential privacy generative adversarial network algorithm for dynamic gradient threshold clipping. Journal of Computer Applications, 2022.
陈少权，蔡剑平，孙岚. 动态梯度阈值裁剪的差分隐私生成对抗网络算法[J]. 计算机应用, 2022. [Paper]

[20] Chen Shaoquan, CAI Jianping, Sun Lan. Self-regularization method for Non-IID data in federated learning. Journal of Computer Applications, 2022.
蓝梦婕，蔡剑平，孙岚. 非独立同分布数据下的自正则化联邦学习优化方法[J]. 计算机应用, 2022. [Paper]

[21] Hongyi Cai, Jianping Cai, and Lan Sun. 2023. An Adaptive Gradient Privacy-Preserving Algorithm for Federated XGBoost. In Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning (CACML '23). Association for Computing Machinery, New York, NY, USA, 277–282. https://doi.org/10.1145/3590003.3590051 [Paper]

[22] Jinxin Hong, Yingjie Wu, Jianping CAI, Lan Sun. Differentially Private High-Dimensional Binary Data Publication via Attribute Segmentation[J/OL]. Journal of Computer Research and Development,{3},{4}{5}:1-15[2021-07-15].
洪金鑫,吴英杰,蔡剑平,孙岚.基于属性分割的高维二值数据差分隐私发布[J/OL].计算机研究与发展,{3},{4}{5}:1-15[2021-07-15]. [Paper]

[23] Zhang S Y, Cai J P. The method for financial markets' short-term development Analysis based on exponential regression model. sp.
张双越, 蔡剑平. 基于指数回归模型的金融市场行业短期发展分析方法. 计算机产品与流通. [Paper]

[24] Chengxi Hong, Jianping Cai, The Growth Pattern of Pterosaurs Based on Logistic Growth Model. Academic Journal of Computing & Information Science (2019) Vol. 2: 142-147. https://doi.org/10.25236/AJCIS.010028. [Paper] [Code]

[25] WU Yingjie, CHEN Jinglin, CAI Jianping, WANG Yilei. Error Analysis of Differential Privacy Data Publishing Method with Matrix Mechanism. Journal of Frontiers of Computer Science and Technology, 2018, 12(7): 1075-1086.DOI:10.3778/j.issn.1673-9418.1705046.
吴英杰，陈靖麟，蔡剑平，王一蕾. 矩阵机制下差分隐私数据发布方法的误差分析[J]. 计算机科学与探索, 2018, 12(7): 1075-1086.DOI:10.3778/j.issn.1673-9418.1705046. [Paper]

[26] Wu Yingjie, Lu Qing, Cai Jianping, Wang Xiaodong. Differential privacy two-dimensional data partitioning publication algorithm based on quad-tree[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 2016, 44(3):99-104.
吴英杰, 卢清, 蔡剑平, et al. 基于四分树的差分隐私二维数据划分发布算法[J]. 华中科技大学学报(自然科学版), 2016, 44(3):99-104. [Paper]

My Blogs

[1] 网络追踪器介绍

[2] 如何瓜分会缩水的蛋糕？

[3] MyJupyter，一款支持Python和Java的可移动Jupyter软件包

[4] 关于被3个搞物理的“颠覆”了且数学天才陶哲轩“开始压根不相信”的数学常识的算法实现与理解