Ph.D., University of Michigan, 2003
M.S., Iowa State University, 1999
B.S., Peking University, 1997
Data Privacy and Differential privacy, Statistical Machine Learning, Bayesian Statistics, Applications of Statistics to Biology, Engineering, Medical Science, and Social Science
Dr. Liu’s research focuses on 1) development and application of modern approaches for protecting data privacy. Some recent work involves integrating the concept of differential privacy and the data synthesis techniques; privacy-preserving empirical risk minimization, statistical inferences, and location privacy; 2) statistical learning, machine learning, and complex model regularization. Some recent work includes undirected graphical model construction and differentiation, deep learning in neural networks, reinforcement learning, and tensor regression; 3) Bayesian methodologies and models to analyze data originated from medical, biological, and social sciences; 4) missing data analysis techniques and concepts; and 5) Biostatistical and epidemiological applications. Dr. Liu's work has been generously supported by NSF, NIH, and Notre Dame internal research grants. Among the first group of statisticians who came to the newly formed ACMS department in 2011, Dr. Liu has also brought her statistical expertise and rich consulting experience to various collaborations both on campus and with external organizations. Dr. Liu has served as the statistician on large-scale studies funded by Gates Foundation and UNITAID to assess the efficacy of promising malaria control methods. Dr. Liu also serves as the Notre Dame Liaison on Design and Biostatistics Program under the Indiana Clinical and Translational Sciences Institute to provide investigators centralized access to the biostatistics and bioinformatics programs among the four Indiana Research Universities.