Faculty

Research Areas: Bayesian modeling, theory, and computation, Statistical learning methods, High-dimensional methods, Bioinformatics and computational biology, Statistical missing data problems, Imputation methodology, Causal inference, Gibbs sampling and other MCMC methods

Research Areas:Inference for High Dimensional Data; High-Resolution Data Assimilation; Mathematical Geophysics; Statistical Methods of Climate Change; Econometrics; Demographic Statistics

Research Areas:Statistical inference for time series data, functional data, high dimensional data and sample survey data, especially the theory and methodology of oracally efficient estimation and simultaneous confidence region; Applications of statistics in econometrics, finance, agronomy, food science, geography, genetics, neuroscience and management science

Research Areas: Non-parametric/semi-parametric estimation, longitudinal data analysis, survival analysis, biostatistics, spatial statistics

Research Areas:statistical modeling, statistical computation, bioinformatics, text mining, social network analysis

Research Areas:financial econometrics, nonlinear time series analysis, network and big data

Research Areas:statistical genetics, bioinformatics, applied statistics

Research Areas:text-based artificial intelligence in medicine, including large language models, information retrieval, question answering, and knowledge graph construction

Research Areas: Causal Infenrece, High-dimensional Statistics, Big Data, and Machine Learning

Research Areas:statistical computation, high dimensional statistics

Research Interests：Non-stationary Time Series, High-dimensional Time Series, Functional Time Series, Multiscale Inference, Change Point Problem, Statistical Network Analysis, Nonparametric Method, Forecasting, M-estimation.

Research Areas:theory and algorithms for high-dimensional statistics, mathematical data science, statistical machine learning, optimization

Research Areas: High-dimensional statistics, statistical foundations for machine learning and AI, causal inference.

Research Areas: Tensor data, High-dimensional statistical inference, Time series analysis, Dimension reduction, Network analysis, Functional data analysis, Portfolio management, Analysis of observational studies and causal inference, Business analytics in finance, economics, and operations management.

Research Areas: Statistical genetics and genomics, Multi-omics data integration analysis, High dimensional statistics.

Research Areas: Large language model, Autonomous intelligent agent, Automated data analysis.

Research Areas: conformal prediction, clinical trial design, neuroimaging data analysis

Research Areas: Probabilistic Forecasting, Nonparametric Shape Constrained Regression, Sequential Hypothesis Testing

Research Areas：Data Fusion,Large-scale Data Analysis,Causal Identification and Inference,Two-phase Sampling,Mendelian Randomization,Machine Learning Theory

She teaches Applied Statistics at the graduate level and a range of undergraduate courses, including Experimental Design and Analysis, Statistical Computing and Software, Linear Regression Analysis, and Introduction to Nonparametric Statistics.