Julie Zhou

I am a statistician with strong research interests in robust statistics and optimal design of experiments. Robust statistical procedures are not sensitive to small deviations from model assumptions. When there are possible outliers in the data, robust procedures can identify outliers and perform estimation or hypothesis testing at the same time. I have developed robust estimators and applied robust procedures for various applications.

Optimal designs can be used in many research fields, where experiments are performed to develop new theories and/or improve the quality of processes and services, such as medical, natural and social sciences as well as engineering. For example, experiments are continually conducted to study and improve manufacturing processes, evaluate environmental damages, and develop new drugs for patients. Using optimal designs can not only save the cost of experiments including the cost of labour, time and materials, but also provide accurate statistical inferences. I have been developing new design theories and numerical algorithms for finding optimal designs.

Interests

• Optimal regression design
• Robust statistics
• Fractional factorial design
• Statistical computing
• Applied statistics
• Optimization algorithm

Courses

• Fall 2024: STAT 456: Multivariate Analysis  STAT 457: Time Series Analysis  STAT 553: Multivariate Analysis  STAT 554: Time Series Analysis 
• Spring 2025:
• Summer 2025: STAT 556: Topics in Statistics 

Current Projects

Selected Publications

• Yin, Y. and J. Zhou (2015). ``Minimax design criterion for fractional factorial designs", Annals of the Institute of Statistical Mathematics, 67, 673-685.
• Gao, L.L. and J. Zhou (2014). ``New optimal design criteria for regression models with asymmetric errors", Journal of Statistical Planning and Inference, 149, 140-151.
• Lin, D.K.J. and J. Zhou (2013). ``D-optimal minimax fractional factorial designs", Canadian Journal of Statistics, 41, 325-340.
• Wilmut, M. and J. Zhou (2011). ``D-optimal minimax design criterion for two-level fractional factorial designs", Journal of Statistical Planning and Inference, 141, 576-587.
• Ou, B. and J. Zhou (2009). ``Minimax robust designs for field experiments", Metrika, 69, 45-54.
• Tang, B. and J. Zhou (2009). ``Existence and construction of two-level orthogonal arrays for estimating main effects and some specified two-factor interactions", Statistica Sinica, 19, 1193-1201.
• Zhu, H., F. He and J. Zhou (2008). ``Auto-multicategorical regression model for the distribution of vegetation", Statistics and Its Interface, 1, 63-73.
• Shi, P., J. Ye and J. Zhou (2007). ``Discrete minimax designs for regression models with autocorrelated MA errors", Journal of Statistical Planning and Inference, 137, 2721-2731.
• Tsao, M. and J. Zhou (2001). ``On the robustness of empirical likelihood ratio confidence intervals for location", Canadian Journal of Statistics, 29, 129-140.
• Wiens, D.P. and J. Zhou (1997). ``Robust designs based on the infinitesimal approach", Journal of the American Statistical Association, 92, 1503-1511.