معرفی
Albert Vexler, PhD, is a Professor in the Department of Biostatistics at the University at Buffalo, within the School of Public Health and Health Professions. He specializes in advanced statistical methodologies with applications to biomedical and health-related research. His work focuses on biomarker analysis, nonparametric testing, ROC curve methodologies, and empirical likelihood techniques.
Education: PhD in Statistics and Probability Theory from the Hebrew University of Jerusalem (2003), followed by a Postdoctoral Research Fellowship at the National Institute of Child Health and Human Development (2004–2007).
Research Interests: Dr. Vexler’s research spans biostatistical methods, including optimal designs, censored data analysis, sequential analysis, and Bayesian approaches. He develops tools for handling complex data structures such as skewed biomarker measurements and limits of detection in clinical studies. His work emphasizes robust statistical inference and practical applications in clinical trials and public health.
Publications: His recent work highlights advancements in hypothesis testing, biomarker evaluation, and statistical computing. Key areas include density-based empirical likelihood tests, multivariate dependence measures, and computational tools for analyzing biomedical data.
Professional Activities: He serves as an Associate Editor for Biometrics and Journal of Applied Statistics, and has reviewed for top-tier journals such as the Journal of the American Statistical Association and Biometrika. He contributes to statistical software development, including R packages like dbEmplikeGOF and testforDEP.
Lab/Teams: Leads a research group focused on innovative statistical methods for health sciences, collaborating on projects involving clinical trial design, epidemiological modeling, and precision medicine.
