统计学博士，研究方向：统计计算、教育统计与心理测量。
主持一项国家自然科学基金（青年科学基金项目），2025.01-2027.12。
学术成果：
[1] Xu P F, Shang L, Zheng Q Z, Shan N*, Tang M L. Latent variable selection in multidimensional item response theory models using the expectation model selection algorithm[J]. British Journal of Mathematical and Statistical Psychology, 2022, 75(2): 363-394. 【SCI, SSCI, JCR Q1, 中科院三区, 心理测量学权威刊】
[2] Shang L, Xu P F*, Shan N, Tang M L, Ho T S G. Accelerating L1-penalized expectation maximization algorithm for latent variable selection in multidimensional two-parameter logistic models[J]. PLoS ONE, 2023, 18(1): e0279918. 【SCI, JCR Q1, 中科院三区】
[3] Shang L, Zheng Q Z, Xu P F*, Shan N, Tang M L. A generalized expectation model selection algorithm for latent variable selection in multidimensional item response theory models[J]. Statistics and Computing, 2024, 34: article 49. 【SCI, JCR Q1, 中科院二区, 统计学权威刊】
[4] Zheng Q Z, Xu P F*, Shang L. Structure learning of Bayesian networks with latent variable via sparse and low-rank decomposition[J]. Journal of Nonlinear and Convex Analysis, 2024, 25(2), 3143-3164. 【SCI】
[5] Shang L, Xu P F*, Shan N, Tang M L, Zheng Q Z. The improved EMS algorithm for latent variable selection in M3PL model[J]. Applied Psychological Measurement, 2025, 49(1-2): 50-70. 【SSCI, JCR Q3, 中科院四区, 心理测量学权威刊】
[6] Lin S, Zheng Q Z, Shang L, Xu P F*, Tang M L. Fitting penalized estimator for sparse covariance matrix with left-censored data by the EM algorithm[J]. Mathematics, 2025, 13: 423. 【SCI】
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