付光辉，男，中共党员，博士，教授，博士生导师

Email: ghuifu@126.com

2001/09-2005/07，云南大学，数学与统计学院，学士

2005/09-2008/07，云南大学，数学与统计学院，硕士

2008/09-2011/06，中南大学，数学与统计学院，博士

2017/08-2018/07，英国曼彻斯特大学，访问学者

本科生：《概率论与数理统计》，《线性代数》

研究生：《数理统计》，《高等数理统计》，《统计科学计算》

  主要研究方向

不平衡数据统计建模；变量选择；统计学习；应用统计；化学计量学

承担科研项目及完成情况

1.国家自然科学地区基金,11261052,连续型不平衡数据的统计学习理论、方法及其在稀有值预测中的应用,2013/1-2026/12,29万元,在研,主持

2.云南省自然科学基金面上项目，202201AT070109，基于封顶-L1惩罚的组变量选择建模及其在生物标记物识别中的应用研究，2022/6-2025/6,10万元,在研,主持

3. 国家自然科学地区基金,11761041,类不平衡高维数据的统计建模及在代谢组学中的应用,2018/1-2021/12,36.5万元,已结题,主持

4. 国家自然科学面上项目基金,21775058,代谢组学应用于冠心病临床诊断的关键问题研究,2018/1-2021/12,64万元,已结题,参与

5. 国家自然科学地区基金,21465016,代谢组学数据的多层次融合和模型评价方法研究,2015/1-2018/12,49万元,已结题,参与

6. 国家自然科学青年基金,11201200,含有缺失的散度偏大计数数据的有限混合建模研究,2013/1-2015/12,23万元,已结题,参与

7. 国家自然科学数学天元基金,11226220,高维小样本数据的稀疏模型及其在近红外光谱分析上的应用,2013/01-2013/12,3万元,已结题,主持

获奖情况：

1.2020年入选云南省“兴滇英才支持计划”

2.2020年获云南省自然科学奖三等奖

3.2015年获“红云园丁奖”

代表性论文：

1.Ying Guan, Guang-Hui Fu*(通讯作者). A Double-Penalized Estimator to Combat Separation and Multicollinearity in Logistic Regression, Mathematics, 10, 3824, 2022. https://doi.org/10.3390/math10203824

2.Guang-Hui Fu*, Jia-Bao Wang, Min-Jie Zong, Lun-Zhao Yi*. Feature Ranking and Screening for Class-Imbalanced Metabolomics Data Based on Rank Aggregation Coupled with Re-Balance, Metabolites, 11(6), 389, 2021. https://doi.org/10.3390/metabo11060389

3.Jia-Bao Wang, Chun-An Zou, Guang-Hui Fu* (通讯作者). AWSMOTE: An SVM-Based Adaptive Weighted SMOTE for Class-Imbalance Learning, Scientific Programming, vol. 2021, 2021. https://doi.org/10.1155/2021/9947621

4.Guang-Hui Fu*, Yuan-Jiao Wu, Min-Jie Zong, Jianxin Pan. Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data, BMC Bioinformatics, 21(1), 121, 2020. https://doi.org/10.1186/s12859-020-3411-3

5.Guang-Hui Fu, Yuan-Jiao Wu, Min-Jie Zong, Lun-Zhao Yi*. Feature selection and classification by minimizing overlap degree for class-imbalanced data in metabolomics, Chemometrics and Intelligent Laboratory Systems, 196, 2020. https://doi.org/10.1016/j.chemolab.2019.103906

6.Guang-Hui Fu, Lun-Zhao Yi, Jianxin Pan*. LASSO-based false-positive selection for class-imbalanced data in metabolomics, Journal of Chemometrics, 33 (10), 2019.  https://doi.org/10.1002/cem.3177

7.Guang-Hui Fu, Min-Jie Zong, Feng-Hua Wang, Lun-Zhao Yi*. A Comparison of Sparse Partial Least Squares and Elastic Net in Wavelength Selection on NIR Spectroscopy Data. International Journal of Analytical Chemistry, vol. 2019, 2019. https://doi.org/10.1155/2019/7314916

8.Guang-Hui Fu, Lun-Zhao Yi, Jianxin Pan*. Tuning model parameters in class-imbalanced learning with precision-recall curve. Biometrical Journal, 61(3), 652-664, 2019. https://doi.org/10.1002/bimj.201800148

9.Guang-Hui Fu, Feng Xu, Bing-Yang Zhang, Lun-Zhao Yi*. Stable variable selection of class-imbalanced data with precision-recall criterion. Chemometrics and Intelligent Laboratory Systems, 171, 241-250, 2017. https://doi.org/10.1016/j.chemolab.2017.10.015

10.Guang-Hui Fu, Bing-Yang Zhang, He-Dan Kou, Lun-Zhao Yi*. Stable biomarker screening and classification by subsampling-based sparse regularization coupled with support vector machines in metabolomics. Chemometrics and Intelligent Laboratory Systems, 160, 22-31, 2017.  https://doi.org/10.1016/j.chemolab.2016.11.006

11.Guang-Hui Fu*, Wen-Ming Zhang, Lin Dai, Ying-Zi Fu. Group variable selection with oracle property by weight fused adaptive elastic net model for strongly correlated data, Communications in Statistics-Simulation and Computation, 43(10), 2468-2481, 2014. https://doi.org/10.1080/03610918.2012.752841

12.Guang-Hui Fu, Qing-Song Xu^*. Grouping variable selection by weight fused elastic net for multi-collinear data, Communications in Statistics-Simulation and Computation (SCI), 41(2), 205-221, 2012. https://doi.org/10.1080/03610918.2011.579369

13.Guang-Hui Fu, Qing-Song Xu^*, Hong-Dong Li, Dong-Sheng Cao, Yi-Zeng Liang. Elastic Net Grouping Variable Selection Combined with Partial Least Squares Regression (EN-PLSR) for the Analysis of Strongly Multi-collinear Spectroscopic Data, Applied Spectroscopy (SCI), 65(4), 402-408, 2011. https://doi.org/10.1366/10-06069

14.Guang-Hui Fu, Dong-Sheng Cao, Qing-Song Xu^*, Hong-Dong Li, Yi-Zeng Liang. Combination of kernel PCA and linear support vector machine for modeling a nonlinear relationship between bioactivity and molecular descriptors, Journal of Chemometrics (SCI), 25(2), 92-99, 2011. https://doi.org/10.1002/cem.1364