Junshu Bao is a Teaching Associate Professor in the Department of Statistics at the University of Pittsburgh. She obtained her Ph.D. in Statistics from the University of South Carolina in 2016. Her research focuses on Bayesian nonparametric multivariate modeling. Her teaching interests include data science, machine learning, statistical computing, and mathematical statistics.
Courses
- STAT 0200 Basic Applied Statistics
- STAT 1000 Applied Statistical Methods
- STAT 1060 Data Science Foundations
- STAT 1152 Introduction to Mathematical Statistics
- STAT 1261/2260 Principles of Data Science
- STAT 1281/2280 Data Science with Python
- STAT 1293/2292 Topics in Applied Statistics II
- STAT 1301/2300 Statistical Packages
- Ph.D. in Statistics, University of South Carolina, 2016
Education & Training
Recent Publications
- Bao, J. and Hanson, T. (2015). Bayesian Nonparametric Multivariate Ordinal Regression. Canadian Journal of Statistics, 43, 337-357.
- Bao, J. and Hanson, T. (2016). A Mean-Constrained Finite Mixture of Normals. Statistics & Probability Letters, 117, 93-99.
- Bao, J., Hanson, T., McMillan, G. P. and Knight, K. (2016). Assessment of DPOAE Test-retest Deference Curves via Hierarchical Gaussian Processes. Biometrics, doi:10.1111/biom.12550.
- Abdelfatah, K., Bao, J. , and Terejanu, G. (2018) Geospatial Uncertainty Modeling Using Stacked Gaussian Processes. Environmental Modelling and Software 109: 293-305.
