Fang Liu, Ph.D.
CV (last updated: Dec 12, 2016)

Huisking Foundation, Inc. Assistant Professor of Statistics
Department of Applied and Computational
Mathematics and Statistics
University of Notre Dame


My methodological research focuses on the following areas. You may refer to my CV for my publications on these topics.

  • Data confidentialtiy and differential privacy
  • Statistical learning in big data
  • Bayesian methods and modelling
  • Statistical analysis of missing data
  • Statistical analysis of clustered and correlated data
  • Epidemiological and biostatistical applications

I also serve as the statistician on a Gates Foundation funded project to assess the efficacy of promising malaria control methods. I collaborate with the research teams to optimize the study design and prepare the statistical analysis plan to ensure the efficiency and validity of final data analysis. I am also the Notre Dame liason on the Design and Biostatistics Program in the Indiana Clinical and Translational Sciences Institute to provide investigators centralized access to the biostatistics and bioinformatics programs among the four Indiana Research Universities.


I teach the following courses at Notre Dame. The course descriptions can be found here. Students who are registered for my courses can view the course materials in Sakai .

  • ACMS 30600 Statistical Methods and Data Analysis
  • ACMS 40852/60852 Advanced Biostatistical Methods
  • ACMS 60784/60785: Applied Regression Models I/II
  • ACMS 60885 Applied Bayesian Statistics
My Students

  • Bide Xiong (Ph.D. candidate): works on Gaussian graphical models; 2012 -
  • Claire Bowen (Ph.D.candidate): works on differentially private data sythesis; 2013 -
  • Evercita Eugenio (Ph.D. candidate): works on differentially private data sythesis; 2014 -
  • Yinan Li (Ph.D. student): works on statistical learning and deep learning; 2016 -
  • Xin Mu (Research M.S.; Ph.D. in Aerospace and Mechanical Engineering), 2016
  • Nathanael Sumaktoyo (Research M.S.; Ph.D. in Political Science), 2016
  • Han Du (Research M.S.; Ph.D. in Quantative Psychology), 2015
  • Patrick Miller (Research M.S.; Ph.D. in Quantative Psychology), 2015
  • Rachel Baird (Research M.S.; Ph.D. in Quantative Psychology), 2015
  • Daniel McArtor (Research M.S.; Ph.D. in Quantative Psychology), 2015
  • Evan Claudeanos (Research M.S.; Ph.D. in Philosophy), 2015
  • Ling Sun (Research M.S.; Ph.D. in Quantative Psychology), 2014
  • Lu Li (Professional M.S.), 2013
  • Ashley Ahimbisibwe (undergraduate researcher), 2016
  • Zhaoyu Cai (undergraduate researcher), 2016
  • Yilan He (undergraduate researcher), 2016
  • Bojia Qiu (undergraduate researcher), 2016
  • Nick Troetti (undergraduate researcher), 2015
  • Colleen Pinkleman (undergraduate researcher), 2014
  • Kunchuan Kong (undergraduate researcher), 2013
  • Software & Tools

    R package "zoib" for Bayesian Inference of zero-one inflated beta regression


    R package "gset" for group sequential designs of equivalence studies


    Construction of ROC and Calculatio of AUC (as referenced in "Controversies and Conundrums in Hydrogen Sulfide Biology" by Olsen, DeLeon, and Liu; Nitric Oxide (2014) doi: 10.1016/j.niox.2014.05.012.)


    Supplemental materials to "Model-based Differentially Private Data Synthesis" by Liu (2016), arxiv:1606.08052


    Supplemental materials to "Statistical Properties of Sanitized Results from Differentially Private Laplace Mechanisms with Noninformative Bounding" by Liu (2016), arxiv:1607.08554v2


    Supplemental materials to "A Bayesian “fill in” method for correcting for publication bias in meta-analysis" by Du, Liu, and Wang (2016)


    Supplemental materials to "Assessment of Bayesian Expected Power via Bayesian Bootstrap" by Liu (2017)

    Office: 173B Hurley


    Office phone: 574-631-0895