معرفی
Jianxuan Liu is an Assistant Professor in the Department of Mathematics at Syracuse University, affiliated with the Applied Statistics program within the College of Arts and Sciences. His research focuses on semiparametric methods, causal inference, measurement error models, and high-dimensional data analysis. He holds a Ph.D. in Statistics from the University of South Carolina (2017), with prior degrees in Statistical Science (Indiana University, 2012), Economics (East Carolina University, 2010), and a B.S. in Economics from Capital University of Economics and Business (2007).
Dr. Liu’s scholarly work emphasizes statistical methodologies for complex data structures, including recent contributions on beta regression for high-dimensional covariates, causal effects of violence exposure on juvenile crime, and longitudinal substance abuse analysis using machine learning. His publications appear in journals like Stat, Journal of Data Science, and Annals of Statistics.
He has received grants for projects such as fusion of semiparametric methods with machine learning in causal inference and statistical analysis of error-prone data. Notable awards include an NSF Travel Grant (2022). Dr. Liu is actively involved in academic service, including supervising the MAT 222 course, chairing statistics hiring committees, and advising the Syracuse University ASA Chapter in Statistics and Data Science.
