2023.01-2025.12，大数据集下高维异质性数据分析方法探究及应用，山东省自然科学基金/面上项目，主持
2017.01-2019.12，含有相关或内生协变量的超高维模型的特征筛选，国家自然科学基金/青年基金项目，主持         
2015.11-2017.12，方差/期望不确定下超高维模型的特征筛选，58批博士后科学基金面上资助项目，独立     
2015.07-2015.12，高维模型中分布不确定下的变量选择的研究，37000cm威尼斯基本科研业务费项目，独立    

[8]陆军, 胡琴琴, 林路.(2023)
 多元响应变量超高维线性模型的经验似然特征筛选方法. 
中国科学: 数学, 53: 499-522
[7] Yong He, Qiushi Li, Qinqin Hu and Lei Liu (2022). 
Transfer Learning in High-dimensional Semi-parametric Graphical Models with Application to Brain Connectivity Analysis. 
Statistics in Medicine  41, 4112-4129
[6] Jun Lu, Dan Wang and Qinqin Hu (2022)
Interaction screening via canonical correlation.
Computational Statistics 37, 2637–2670.
[5] Qinqin Hu and Lu Lin (2022). 
Feature Screening in High Dimensional Regression with Endogenous Covariates.   
Computational Economics 60,  949–969. 
[4] Qinqin Hu and Lu Lin (2018)
Conditional feature screening for mean and variance functions in models with multiple-index structure.
Metrika 81,357–393.
[3]  Peng Zeng, Qinqin Hu and Xiaoyu Li (2017).
Geometry and Degrees of Freedom of Linearly Constrained Generalized Lasso.
 Scandinavian Journal of Statistics 44, 989–1008.
[2] Qinqin Hu and Lu Lin (2017)
Conditional sure independence screening by conditional marginal empirical likelihood.
Annals of the Institute of Statistical Mathematics 69,63-96.
[1] Qinqin Hu, Peng Zeng and Lu Lin (2015).
The dual and degrees of freedom of linearly constrained generalized lasso.
Computational Statistics and Data Analysis 86, 13–26.

qqhu@sdu.edu.cn

2011.09-2015.06      37000cm威尼斯金融研究院         理学博士    
2012.08-2013.08      美国奥本大学数学系           国家公派(联合培养)    
2008.09-2011.07      37000cm威尼斯(威海)37000cm威尼斯    理学硕士    
2008.09-2009.09      中国科学院研究生院           交流学习    
2004.09-2008.07      37000cm威尼斯(威海)37000cm威尼斯    理学学士

2012.08-2013.08        美国奥本大学数学系           国家公派(联合培养)