معرفی
Lingxiao Wang is an Assistant Professor at the University of Virginia, specializing in advanced statistical methodologies for complex survey designs and epidemiologic research. His work bridges survey statistics, statistical learning, and public health applications, with a focus on improving population inference accuracy and developing representative risk models.
- Ph.D., Survey Statistics and Methodology, University of Maryland, College Park
- M.A., Applied Statistics, University of California, Santa Barbara
- B.S., Mathematics and Statistics, Shandong University
His research centers on enhancing efficiency in regression analyses for two-phase sampling, integrating data from surveys/registries for minority subgroup risk estimation, and leveraging statistical learning to improve external validity in nonprobability samples. Recent work explores gene-environment independence in case-control studies and pharmaceutical effects on cancer risk.
Key article trends include: calibration methods for complex surveys, kernel weighting techniques for nonprobability samples, haplotype-based genetic inferences, and risk modeling for public health applications. His 2025 publications highlight improved lung cancer risk models and calibration strategies for pooled samples.
