Associate Professor, Adjunct Associate Professor of Biostatistics at Indiana University School of Medicine, Director of Graduate Studies in ACMS at the University of Notre Dame
University of Notre Dame
Dr. Liu’s statistical methodological research focuses on the development and application of 1) modern approaches for protecting data privacy. Some recent work involves integrating the concept of differential privacy and the data synthesis techniques in the framework of statistical disclosure limitation; 2) Statistical learning in big data. Some recent work includes Gaussian Graphical model estimation and differentiation, and regularization of deep learning in neural networks; 3) Bayesian models for correlated and clustered data originated from medical, biological, and social sciences. Recent work focuses on Bayesian models of non-Gaussian repeated measures; 4) Missing data analysis techniques and concepts; One recent work proposes a Bayesian method dealing with not-missing-at-random mechanism in meta-analysis; 5) Biostatistical and epidemiological applications.