2013年本科毕业于北京师范大学数学科学学院，获学士学位。2018年毕业于美国宾夕法尼亚州立大学，获统计学博士学位。2018年至2021年在美国从事对冲基金量化研究工作。2021年9月加入中国人民大学统计与大数据研究院，任助理教授、博士生导师。研究兴趣包括高维数据分析，模型算法优化，机器学习以及统计模型在金融学、生理学和心理学中的应用。

Publications:

Bao, L., Li, C., Li, R., and Yang, S. (2022). Causal structural learning on MPHIA individual dataset. Journal of the American Statistical Association. Accepted.

Tong, Z., Cai, Z., Yang, S., and Li, R. (2022). Model-Free conditional feature screening with FDR control. Journal of the American Statistical Association. In press. DOI 10.1080/01621459.2022.2063130

Cai, Z., Li, C., Wen, J., and Yang, S. (2022). Asset splitting algorithm for ultrahigh dimensional portfolio selection and its theoretical property. Journal of Econometrics. In press.

Huang, Y., Li, C., Li, R., and Yang, S. (2022). An overview of tests on high-dimensional means. Journal of Multivariate Analysis, 104813. DOI 10.1016/j.jmva.2021.104813

Yang, S., Wen, J., Eckert, S. T., Wang, Y., Liu, D. J., Wu, R., Li, R., and Zhan, X. (2020). Prioritizing genetic variants in GWAS with lasso using permutation-assisted tuning. Bioinformatics, 36(12), 3811-3817.

Trucco, E. M., Yang, S., Yang, J. J., Zucker, R. A., Li, R., and Buu, A. (2020). Time-varying effects of GABRG1 and Maladaptive peer Behavior on externalizing behavior from childhood to adulthood: testing gene× environment× development effects. Journal of youth and adolescence, 49(7), 1351-1364.

Buu, A., Yang, S., Li, R., Zimmerman, M. A., Cunningham, R. M., & Walton, M. A. (2020). Examining measurement reactivity in daily diary data on substance use: results from a randomized experiment. Addictive behaviors, 102, 106198.

Yang, G., Yang, S., and Li, R. (2020). Feature screening in ultrahigh dimensional generalized varying-coefficient models. Statistica Sinica 30 (2): 1049-1067.

Yao, Y. W., Liu, L., Worhunsky, P. D., Lichenstein, S., Ma, S. S., Zhu, L., Shi, X.H., Yang, S., Zhang, J.T., and Yip, S. W. (2020). Is monetary reward processing altered in drug-naïve youth with a behavioral addiction? Findings from internet gaming disorder. NeuroImage: Clinical, 26, 102202.

Yang, S., Wen, J., Zhan, X., and Kifer, D. (2019). ET-lasso: a new efficient tuning of lasso-type regularization for high-dimensional data. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 607-616).

Yang, G., Yang, S., and Zhou, W. (2019). Adjacency matrix comparison for stochastic block models. Random Matrices: Theory and Applications, 8(03), 1950010.

Yang, S., Cranford, J. A., Li, R., Zucker, R. A., and Buu, A. (2017). A time-varying effect model for studying gender differences in health behavior. Statistical methods in medical research, 26(6), 2812-2820.

Yang, S., Cranford, J. A., Jester, J. M., Li, R., Zucker, R. A., and Buu, A. (2017). A time‐varying effect model for examining group differences in trajectories of zero‐inflated count outcomes with applications in substance abuse research. Statistics in medicine, 36(5), 827-837.

Yang, S., Yang, X. H., Jiang, R., & Zhang, Y. C. (2012). New optimal weight combination model for forecasting precipitation. Mathematical Problems in Engineering, 2012.

Songshan Yang currently is an Assistant Professor in Institute of Statistics and Big Data, Renmin University of China. He holds a bachelor degree in Statistics from School of Mathematical Sciences, Beijing Normal University, and doctoral degree in Statistics from Department of Statistics, The Pennsylvania State University. His research interests include high dimensional data analysis, statistical optimization, machine learning and applications of statistical models in finance, physiology and psychology.