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个人简介
My research aims at developing new statistical and machine learning methods and theory for SOCIAL DATA SCIENCE. With the emerging of high-dimensional data in social sciences and due to the high noise level in such data, we need more computationally efficient algorithms and statistical inference methods to make more reliable and reproducible findings.
My current research focuses on three interrelated topics including (1) large-scale item response data analysis, (2) measurement and predictive modeling based on dynamic behavioral data and (3) sequential design of dynamic systems. The first topic focuses on large-scale item response data from educational and psychological testing that are more and more commonly encountered these days. Due to the high-dimensionality and complexity of such data, the traditional statistical models, estimation methods, and computational algorithms are no longer very suitable. I have developed several new statistical models for applications including psychological and psychiatric measurement, detection of aberrant behavior in educational testing, and analysis of large-scale educational survey. In addition, new estimation methods have been proposed and numerical and stochastic optimization algorithms have been developed that are more suitable for large-scale item response data, for which statistical theory has been developed.
My current research focuses on three interrelated topics including (1) large-scale item response data analysis, (2) measurement and predictive modeling based on dynamic behavioral data and (3) sequential design of dynamic systems. The first topic focuses on large-scale item response data from educational and psychological testing that are more and more commonly encountered these days. Due to the high-dimensionality and complexity of such data, the traditional statistical models, estimation methods, and computational algorithms are no longer very suitable. I have developed several new statistical models for applications including psychological and psychiatric measurement, detection of aberrant behavior in educational testing, and analysis of large-scale educational survey. In addition, new estimation methods have been proposed and numerical and stochastic optimization algorithms have been developed that are more suitable for large-scale item response data, for which statistical theory has been developed.
研究兴趣
论文共 53 篇作者统计合作学者相似作者
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Psychometrikapp.1-29, (2024)
arxiv(2023)
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY (2023)
arxiv(2023)
STATISTICA SINICAno. 1 (2023): 453-474
JOURNAL OF MACHINE LEARNING RESEARCH (2023): 95:1-95:66
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Journal of the Royal Statistical Society Series B: Statistical Methodologyno. 4 (2023): 1082-1084
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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGYno. 4 (2023)
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Psychometrikano. 2 (2023): 527-553
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