Chen Xin

Associate Professor Department of Statistics and Data Science

Personal Profile


2005–2010: Ph.D. Statistics, University of Minnesota, Advisor: Prof. R. Dennis Cook.

2001–2003: M.S. Statistics & Applied Probability, National University of Singapore.

1994–1999: B.S. Mathematics, Nankai University, Tianjin, China.


Academic Career

August 2019 – Current. Associate Professor in Department of Statistics and Data Science, Southern University of Science & Technology, China

Jan 2019 – August 2019. Associate Professor in Department of Mathematics, Southern University of Science & Technology, China

June 2011 – Jan 2019. Assistant Professor in Department of Statistics and Applied Probability, National University of Singapore

August 2010 – June 2011. Assistant Professor in Mathematics Department, Syracuse University, USA


· Sufficient Dimension Reduction


· Variable Selection


· High Dimensional Analysis


· Complex Data Analysis


MA439 Statistical Deep Learning

Publications Read More

· Deng, L., Zou, C., Wang Z. and Chen X. (In Press) Testing Constancy of Conditional Variance in High Dimension. Sinica

· Chen, X., Sheng, W., and Yin, X. (2018). Efficient Sparse Estimate of Sufficient Dimension Reduction in High Dimension. Technometrics 60 (2), 161-168

· Chen, X., Ma, X., Wang, X. and Zhang, J. (2017). Efficient Feature Screening for Ultrahigh-dimensional Varying Coefficient Models. Statistics and Its Interface, 10 407-412

· Wen, C., Zhu, S., Chen, X. and Wang, X. (2017). Adaptive Model-free Sure Independence Screening. Statistics and Its Interface, 10 399-406

· Ma, X., Chen, X. and Zhang, J. (2016). Fast Robust Feature Screening for Ultrahigh dimensional Varying Coefficient Models. Journal of Statistical Computation and Simulation, 87, 724-732

· Su, Z., Zhu, G., Chen, X. and Yang, Y. (2016). Sparse Envelope Model: Efficient Estimation and Response Variable Selection in Multivariate Linear Regression. Biometrika, 103, 579-593

· Chen, X., Cook, R. and Zou, C. (2015). Diagnostic studies in sufficient dimension reduction. Biometrika, 102, 545-558.

· Chen, X. and Zhu L. (2015). Connecting continuum regression with sufficient dimension reduction. Statistics & Probability Letters, 98, 44-49.

· Zou, C. and Chen, X. (2012). On the consistency of coordinate-independent sparse estimation with BIC. Journal of Multivariate Analysis, 112, 248-255.

· Chen, X., Zou, C. and Cook, R. (2010). Coordinate-Independent Sparse Sufficient Dimension Reduction and Variable Selection. The Annals of Statistics, 38, 3696-3723.

· Chen, X. and Cook, R. (2010). Some Insights into Continuum Regression and its Asymptotic Properties. Biometrika, 97, 985-989.

· Prince, A., Chen, X. and Lun, K. C. (2005) Containing Acute Disease Outbreak. Methods of Information in Medicine, 44, 603-608.

News More

  • 统计与数据科学系本科生导师见面会成功举行

  • SUSTech Launches New Dept of Statistics and Data Science


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Join us

The Department of Statistics and Data Science was established in April 2019. As a newly established department, we currently have 8 faculty members including 1 Chair Professor, 2 Professors, 2 Associate Professors , 2 Tenure-track Assistant Professors and 1 Visiting Assistant Professor and anticipant to rapidly expand to a team of more than 20 members. All faculty members of the department have extensive overseas study or work experiences. One member is an invited speaker at the International Congress of Mathematicians, an IMS Medallion Lecturer and a winner of the prestigious State Natural Science Award (2nd class). The department has 2 research directions, Statistics and Data Science, which cover a broad array of research areas including Biostatistics, Financial Statistics, Experiment Design, Clinical Trials, High Dimensional Data, Time series, Probability Theory, Data Science and Big Data Technology.
At present, the department has an undergraduate program as well as two graduate programs(M.Phil and PhD). The department is in the process of developing a Major Program in Data Science and Big Data Technology. In 2019, the first batch of 38 undergraduate students in Statistics received the bachelor degree from SUSTech. 5 M.Phil students in Statistics also graduated in the same year. There are currently 9 M.Phil students, 7 PhD students in Statistics and 2 Postdoctoral Fellows. As the department grows in size and strength, the number of graduate students is expected to rise substantially from the current level and the areas of graduate studies will also expand to include Data Science and Big Data Technology.
This is the age of big data which offers exciting opportunities to researchers in Statistics and Data Science. Our department is expected to grow rapidly in the coming years. We invite outstanding scholars to join us in our journey to become a first-class department in Statistics and Data Science. We also welcome brilliant undergraduate and graduate students to apply for our programs. At the same time, we actively recruit excellent postdoctoral candidates.

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