معرفی
Dr. Xin Dang is a Professor of Mathematics at the University of Mississippi, affiliated with the Department of Mathematics within the College of Liberal Arts. His research focuses on robust statistics, data mining, outlier identification, and high-dimensional statistical analysis, with a particular emphasis on developing novel methods like Gini correlations and robust statistical computing techniques. He has contributed extensively to areas such as correlation analysis, classification, and clustering algorithms.
Dr. Dang holds a B.S. in Applied Mathematics from Chongqing University (1991), an M.S. in Natural Sciences from the University of Texas at Dallas (2003), and a Ph.D. in Statistics from the University of Texas at Dallas (2005). He teaches a wide range of courses including Elementary Statistics, Calculus, and Advanced Statistics, reflecting his expertise in both theoretical and applied statistical methodologies.
His recent work emphasizes methodological advancements in Gini-based correlations, high-dimensional feature screening, and computational statistics. Notable contributions include the development of the Maximum Projection Gini Correlation (MaGiC) and the Gini covariance matrix. His research bridges theoretical statistics with practical applications in economics, data science, and computational algorithms.
Dr. Dang’s publications span over two decades, with a focus on robust statistical techniques, dependence modeling, and algorithmic efficiency. He has collaborated on projects involving economic growth prediction, nonparametric testing, and optimization methods. His work often addresses challenges in handling complex data structures and improving predictive accuracy through novel statistical frameworks.
