2013年7月于北京大学光华管理学院取得经济学博士学位，2013年9月至2017年2月在澳大利亚墨尔本大学数学与36365路检测中心-官网(36365路检测中心)任研究员，2017年3月开始全职在西南财经大学36365路检测中心-官网(36365路检测中心)工作。现为西南财经大学数据科学与商业智能联合实验室执行主任、教授、博士生导师、四川省特聘专家、四川省统计专家咨询委员会委员。主要从事“超高维数据分析”和“高频金融数据分析”两个领域的研究。

教授课程

概率论与数理统计

学术成果

代表性论文

1.Chang, J., Tang, C. Y. & Wu, T. T. (2018). A new scope of penalized empirical likelihood with high-dimensional estimating equations, The Annals of Statistics, Vol. 46, pp. 3185-3216.

2.Chang, J., Guo, B. & Yao, Q. (2018). Principal component analysis for second-order stationary vector time series, The Annals of Statistics, Vol. 46, pp. 2094-2124.

3.Chang, J., Qiu, Y., Yao, Q. & Zou, T. (2018). Confidence regions for entries of a large precision matrix, Journal of Econometrics, Vol. 206, pp. 57-82.

4.Chang, J., Delaigle, A., Hall, P. & Tang, C. Y. (2018). A frequency domain analysis of the error distribution from noisy high-frequency data, Biometrika, Vol. 105, pp. 353-369.

5.Chang, J., Zheng, C., Zhou, W.-X. & Zhou, W. (2017). Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity, Biometrics, Vol. 73, pp. 1300-1310.

6.Chang, J., Zhou, W., Zhou, W.-X. & Wang, L. (2017). Comparing large covariance metrices under weak conditions on the dependence structure and its application to gene clustering, Biometrics, Vol. 73, pp. 31-41.

7.Chang, J., Yao, Q. & Zhou, W. (2017). Testing for high-dimensional white noise using maximum cross-correlations, Biometrika, Vol. 104, pp. 111-127.

8.Chang, J., Shao, Q.-M. & Zhou, W.-X. (2016). Cramer-type moderate deviations for Studentized two-sample U-statistics with applications, The Annals of Statistics, Vol. 44, pp. 1931-1956.

9.Chang, J., Tang, C. Y. & Wu, Y. (2016). Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood, The Annals of Statistics, Vol. 44, pp. 515-539.

10.Chang, J., Guo, B. & Yao, Q. (2015). High dimensional stochastic regression with latent factors, endogeneity and nonlinearity, Journal of Econometrics, Vol. 189, pp. 297-312.

11.Chang, J. & Hall, P. (2015). Double-bootstrap methods that use a single double-bootstrap simulation, Biometrika, Vol. 102, pp. 203-214.

12.Chang, J., Chen, S.-X. & Chen, X. (2015). High dimensional generalized empirical likelihood for moment restrictions with dependent data, Journal of Econometrics, Vol. 185, pp. 283-304.

13.Chang, J., Tang, C. Y. & Wu, Y. (2013). Marginal empirical likelihood and sure independence feature screening, The Annals of Statistics, Vol. 41, pp. 2123-2148.

14.Chang, J. & Chen, S.-X. (2011). On the approximate maximum likelihood estimation for diffusion processes, The Annals of Statistics, Vol. 39, pp. 2820-2851.

综述与讨论文章

1.Chang, J., Guo, J. & Tang, C. Y. (2018). Peter Hall's contribution to empirical likelihood, Statistica Sinica, Vol. 28, pp. 2375-2387.

项目

1.2019.01-2022.12：国家自然科学基金面上项目《高维高频数据中若干问题的研究》

2.2019.01—2019.12：中央高校基本科研业务费专项基金年度培育项目《超高维高频金融数据中市场微观结构噪音的协方差估计》

3.2018.03-2021.03：霍英东教育基金会第十六届高等院校青年教师基金项目《超高维估计方程模型的理论与实践》

4.2018.01-2018.12：中央高校基本科研业务费专项基金年度培育项目《高频数据中微观结构噪音的统计推断》

5.2017.07-2019.06：中央高校基本科研业务费专项基金重大基础理论研究项目《超高维数据分析的模型、理论与实践》

6.2017.01-2017.12：中央高校基本科研业务费专项基金青年教师成长项目《超高维经验似然的理论与应用》

7.2016.01-2018.12：国家自然科学基金青年基金项目《高维时间序列的降维与建模》

8.2016.01-2016.12：中央高校基本科研业务费专项基金青年教师成长项目《超高维白噪声序列的检验》

学术兼职

2018年9月—至今：Journal of Business & Economic Statistics副主编

2017年10月—至今：Journal of the Royal Statistical Society Series B副主编

2017年8月—至今：Statistica Sinica副主编