【联系方式】

通讯地址：先进制造学院

Email： johnlee@fzu.edu.cn

【主要学历及工作经历】

1998.09-2002.06 台湾科技大学，电机工程博士

【主要学术及社会兼职】

福建省通信学会高级会员,福建省电机工程学会专委会委员,福建省电子学会智能信息专委会副主任,福建大数据联盟副理事长,国际期刊 Mathematics 客座主编、International Journal of Fuzzy System副主编, 台湾人工智能、信息管理学会永久会员, 软件质量协会理事。

【研究领域】

人工智能、机器学习、数据挖掘、多模态大模型应用

【承担科研课题情况】

1. 福建省科技厅,面上项目, 2023J011130,降雨诱发红黏土新滑坡二次滑动机理及其稳定性评价方法, 2023-08 至 2026-08, 在研、参与。

2. 2022年省科协科技创新智库课题研究，FJKX-2022XKB032，两岸共建基于生成式对抗网络和深度学习的智能碳排放计算平台的研究，结题、主持。

3. 2020 年教育部产学合作协同育人项目202002100011，R程序语言应用于智能学习案例, 结题、主持。

4. 2020年省福建省终身教育研究课题,ZS20048, 两岸老年教育学习满意度的研究, 2020.6.20-2021.10.31、结题, 主持。

5. 2020年省级新工科研究与改革实践项目, 闽台合力校企联动新时代民办高校大数据高素质应用型人才培养模式探索与实践, 2020.5-2022.5, 结题, 参与。

6. 2020年福建省本科高校教育教学改革重大研究项目, FBJG20200371, 海峡两岸民办本科大学内部治理体系比较研究, 2020.12-2021.5, 结题, 参与。

7. 2019年度第二批福州市科技计划项目, 2019-SG-6, 一种新型混合智能型信息安全风险评估, 2019.10.17-2021.10.17, 结题、主持。

8. 福建省本科高校教育教学改革研究项目, FBJG20190284, (十三五”教育科学规划本科高校教改专项)-大数据背景下基于新文科建设的福州外语外贸学院创新创业教育研究与实践, 2019.10.01-2021.10.01, 结题、参与。

【出版著作和论文】

1. 发表论文260余篇，其中 SSCI、SCI、EI等收录110余篇次；获国际期刊 Expert System With Applications高被引论文；发表的论文多次获得最佳论文奖及优秀论文奖，编写专著九部。节录部份成果如下:

2. 零基础学R语言数据分析:从机器学习、数据挖掘、文本挖掘到大数据分析, 清华大学出版社 [第二版], 2019. ( ISBN: 9787302510802)

3. R语言数据分析从入门到实战，清华大学出版社, 2025.7.1. (ISBN: 9787302586340)

4. R语言数据分析从入门到实践，清华大学出版社, 2025-07-01 (ISBN：9787302693970)

5. Wang, X., Li, F. Y., Wang, L. H., & Lee, Z. J. (2026). The Prediction of Building Energy Consumption Using Feature Selection and Ensemble Deep Learning with Improved Rafflesia Optimization Algorithm. In Artificial Intelligence and Human-Computer Interaction: Proceedings of the 3rd International Conference (ArtInHCI 2025), Nanning, China, 21-23 October 2025 (pp. 294-309). 1 Oliver's Yard, 55 City Road, London, EC1Y 1SP: SAGE Publications.

6. Wang, X., Li, F., Wang, L., & Lee, Z. (2026, April). An improved artificial bee colony-based approach for fraud detection of credit cards. In Fifth International Conference on Computer Technology, Information Engineering, and Electron Materials (CTIEEM 2025) (Vol. 14139, pp. 334-339). SPIE.

7. Wang, X., Li, F. Y., Wang, Y., Wang, L. H., Wu, W. Y., Lee, Z. J. & Lin, C. Y. (2026). A Novel K-Means with SHAP Feature Selection and ROA-Optimized SVM for Sleep Monitoring from Ballistocardiogram Signals. Mathematics, 14(8), 1262.

8. Liu, H., Li, W., Lin, Y., & Lee, Z. J. (2026). Causal Identification of Artificial Intelligence Effects on Enterprise Labor Structure via a Partially Linear Double Machine Learning Estimator: Evidence from High-Dimensional Panel Data. Mathematics.

9. Cai, J., Lee, Z. J., Lin, Z., & Yang, M. R. (2025). A Novel SHAP-GAN Network for Interpretable Ovarian Cancer Diagnosis. Mathematics, 13(5), 882. (SCI)

10. Wang L-H, Zhang Z-N, Xie C-X, Jiang H, Yang T, Ran Q-P, Fan M-H, Kuo I-C, Lee Z-J, Chen J-B, et al. A Novel Real-Time Threshold Algorithm for Closed-Loop Epilepsy Detection and Stimulation System. Sensors. 2025; 25(1):33. https://doi.org/10.3390/s25010033

11. Cai, J., Lee, Z. J., Lin, Z., Hsu, C. H., & Lin, Y. (2024). An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer. Mathematics, 12(24), 4041.

12. Lee, Z. J., Cai, J. X., Wang, L. H., & Yang, M. R. (2024). Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification. Diagnostics, 14(24), 2772. (SCI)

13. Liang-Hung Wang, Chao-Xin Xie, Tao Yang, Hong-Xin Tan, Ming-Hui Fan, I-Chun Kuo, Zen-Jung Lee, Tsung-Yi Chen, Pao-Cheng Huang, Shih-Lun Chen and Patricia Angela R. Abu (2024). Recorded ECG Digitization Method with Automatic Reference Voltage Selection for Telemonitoring and Diagnosis. Diagnostics, 14(17), 1910. (SCI)

14. Lee, Z. J., Yang, M. R., & Hwang, B. J. (2024). A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm. Diagnostics, 14(7), 723. (SCI)

15. Pan, J. S., Zhang, Z., Chu, S. C., Lee, Z. J., & Li, W. (2023). Application of Diversity-Maintaining Adaptive Rafflesia Optimization Algorithm to Engineering Optimisation Problems. Symmetry, 15(11), 2077. (SCI)

16. Lee, Z. J., & Luo, X. (2023). Predicting Rainfall-induced Landslide Using Bee Colony Algorithm Based on Support Vector Regression. Recent Advances in Computer Science and Communications (Formerly: Recent Patents on Computer Science), 16(1), 33-37. (EI)

17. Chen, Y. F., Guo, X. Y., Chai, H. D., Lin, Y. T., Zhu, Y. W., Huang, J. H., & Lee, Z. J. (2023, October). A building safety inspection system with modified ResNet50. In Third International Conference on Signal Image Processing and Communication (ICSIPC 2023) (Vol. 12916, pp. 241-246). SPIE. (EI)

18. Lee, Z. J., Lin, Y., Chen, Z. Y., Yang, Z., Fang, W. G., & Lee, C. H. (2023, February). Ensemble Deep Learning Applied to Predict Building Energy Consumption. In 2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI) (pp. 339-341). IEEE. (EI)

19. Lee, Z. J., Lin, Y., Yang, Z., Chen, Z. Y., Fan, W. G., & Lee, C. H. (2023, February). Novel Automatic Feature Engineering for Carbon Emissions Prediction Base on Deep Learning. In 2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI) (pp. 203-206). IEEE. (EI)

20. Liang, Q., Chu, S. C., Song, P. C., Zhao, J., Lee, Z. J., & Pan, J. S. (2024, July). A Multi-objective Evolutionary Algorithm based on Hierarchical Grouping for Large-scale Multi-objective Optimization. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 343-346). (CCF C类)

【获奖情况】

1. 2026年获选 Vebleo Fellow

2. 2020-2025年获选全球前2%顶尖科学家终身科学影响力排行榜

3. 入选福建省普通高等学校“十四五”规划教材建设项目

4. 2024年获选桐江学者讲座教授

5. 2024年获选The international academic organization ScienceFather awarded the "Best Researcher Award"

6. 2021年获选福州市长乐区第三届优秀人才

7. 2019-2020年全国高等院校计算机基础教育研究会学术成果推优《零基础学R语言数据分析:从机器学习、数据挖掘、文本挖掘到大数据分析》入选优秀教材奖

8. 2019年获选福州市试验区“外专百人计划”领军人才

9. 2018年获选福建省高层次人才C 类

【指导硕士生研究方向】

人工智能、机器学习、多模态语言大模型(LLM)。惟碍于规定不能担任硕士生第一导师