现任福建师范大学计算机与网络空间安全学院副院长，民革第十四届福建省委会常委。

1. 1989.9~1993.6, 电子科技大学，计算机及应用专业，工学学士

2. 1993.7~1996.1, 福建省电子计算机研究所，职工

3. 2001.2~2004.1, 清华大学，计算机技术专业，工程硕士

4. 2005.9~2008.6, 厦门大学，基础数学专业，理学博士

5. 2008.7~今, 福建师范大学，教学科研

1. 中国人工智能学会机器学习专业委员会委员2. 福建省人工智能学会常务理事3. 福建省高层次人才（B类）

1. 国家自然科学基金-海峡联合基金重点项目：面向大学生心理安全大数据的预警模型及应用研究，编号U1805263，项目负责人，2019-2022

2. 国家自然科学基金-面上项目：高维序列数据的核学习方法及应用研究，编号61672157，项目负责人，2017-2020

3. 国家自然科学基金-面上项目：面向软件行为鉴别的事件序列挖掘方法研究，编号61175123，项目负责人，2012-2015

4. 福建省自然科学基金-面上项目：细粒度行为数据的预测性模型及其学习，编号2015J01238，项目负责人，2015/4-2018/4

5. 福建省自然科学基金-面上项目：基于模型的投影聚类分析及其应用研究，编号2009J01273，项目负责人，2009/3-2011/3

6. 福建省省属高校科研专项重点项目：有向图聚类的若干问题研究，编号JK2009006，项目负责人，2009/7-2012/6。

1. Lifei Chen, Haiyan Wu, Wenxuan Kang, Shengrui Wang. Symbolic sequence representation with Markovian state optimization, Pattern Recognition, 2022, 131: 108849

2. Kunpeng Xu, Lifei Chen, Shengrui Wang. A multi-view kernel clustering framework for categorical sequences, Expert Systems with Applications, 2022, 197:116637

3.  Jianfei Zhang, Lifei Chen, Yanfang Ye, Gongde Guo, Rongbo Chen, Alain Vanasse, Shengrui Wang. Survival neural networks for time-to-event prediction in longitudinal study. Knowledge and Information Systems, 2020, 62(9): 3727-3751

4. 徐鲲鹏,  陈黎飞,  孙浩军,  王备战. 类属型数据核子空间聚类算法，软件学报，2020, 31(11):3492-3505

5.  Liang Yuan, Wenjian Wang, Lifei Chen. Two-stage pruning method for gram-based categorical sequence clustering, International Journal of Machine Learning and Cybernetics. 2019, 10(4):631-640

6. Jianfei Zhang, Shengrui Wang, Lifei Chen, Gongde Guo, Rongbo Chen, Alain Vanasse. Time-dependent survival neural network for remaining useful life. In: Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2019, pp. 441-452 （获最佳应用论文奖）

7. Gongde Guo, Lifei Chen, Yanfang Ye, Qingshan Jiang. Cluster validation method for determining the number of clusters in categorical sequences, IEEE Transactions on Neural Networks and Learning Systems, 2017,28(12): 2936-2948

8. Jianfei Zhang, Shengrui Wang, Lifei Chen, Patrick Gallinari. Multiple Bayesian discriminant functions for high-dimensional massive data classification. Data Mining and Knowledge Discovery, 2017, 31(2): 465-501

9. Lifei Chen, Shengrui Wang, Kaijun Wang, Jianping Zhu. Soft subspace clustering of categorical data with probabilistic distance. Pattern Recognition, 2016, 51:322-332

10. Lifei Chen, Yanfang Ye, Gongde Guo, Jianping Zhu. Kernel-based linear classification on categorical data. Soft Computing, 2016, 20(8): 2981-2993

11. Jianfei Zhang, Lifei Chen, Alain Vanasse, Josiane Courteau, Shengrui Wang. Survival prediction by an integrated learning criterion on intermittently varying healthcare data. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016, pp.72-78

12. Jianfei Zhang, Shengrui Wang, Josiane Courteau, Lifei Chen, Aurélien Bach, Alain Vanasse. Predicting COPD failure by modeling hazard in longitudinal clinical data. In: Proceedings of the 16th IEEE International Conference on Data Mining (ICDM), 2016, pp.639-648

13. Lifei Chen. A probabilistic framework for optimizing projected clusters with categorical attributes. Science China-Information Sciences, 2015, 58: 072104(15)

14. Lifei Chen, Shengrui Wang. Central clustering of categorical data with automated feature weighting. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013, pp.1260-1266

15. 陈黎飞, 郭躬德. 属性加权的类属型数据非模聚类. 软件学报, 2013, 24(11):2628-2641

16. Lifei Chen, Shengrui Wang. Automated feature weighting in naive Bayes for high-dimensional data classification. In: Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM), 2012, pp.1243-1252

17. Lifei Chen, Qingshan Jiang, Shengrui Wang. Model-based method for projective clustering. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(7):1291-1305

18. Lifei Chen, Shengrui Wang, Xuanhui Yan. Centroid-based clustering for graph datasets. In: Proceeding of the 21st International Conference on Pattern Recognition (ICPR),  2012, pp.2144-2147

19. 陈黎飞, 郭躬德. 最近邻分类的多代表点学习算法. 模式识别与人工智能, 2011, 24(6): 882-888

20. 陈黎飞, 吴涛. 数据挖掘中的特征约简, 科学出版社, 2016

21. 2014年2月, 获福建省第七届高等教育教学成果一等奖（排名第三）

22. 2014年11月，获2013-2014年度福建师范大学统一战线优秀教师奖