Frank Zou
Professor Zou's research focuses on financial time series and spatial statistics with applications to epidemiology, public health and climate change. His most recent research on statistical theory and methodology addressed a wide range of challenges including high dimensionality, complex dependencies, and space and time variations. His research in high-frequency financial data tackled problems with high dimensionality, which is currently a hot topic in statistics. He also works on developing novel spatio-temporal models that provide early and accurate detection of disease outbreaks using syndrome (collection of clinical symptoms) data that are monitored as indicators of potential disease outbreaks. These models can also be applied to threats such as biological weapon attacks.
Zou plans to continue to focus on these two areas of research at WPI. In financial statistics, “I will focus on developing novel methods for large volatility matrix estimation and inference, asset allocation and risk analysis, and evaluate its performance based on high frequency financial data,” Zou said. “I anticipate of my research on models that handle patterns of space-time correlation will be numerous and diverse, because a more accurate statistical model for large data sets has immediate relevance to many problems in finance, epidemiology and public health. I would like to explore opportunities of collaborations with scientists from different areas such as physical sciences, engineering, biological and clinical research. I believe that combining all the talented mind of different expertise, we can make our lives much better.”
Dr. Zou enjoys teaching at all levels and wide ranges of statistics courses. He has been enthusiastically involved in student advising and mentoring. He believes that the objectives of teaching are to give to the students the best possible preparation for their future studies and for their future employments, to make them able to master the concepts they are learning, and to give them the ability to use it creatively in more complex contexts as well as develop it further to suit more general problems.
Frank Zou
Professor Zou's research focuses on financial time series and spatial statistics with applications to epidemiology, public health and climate change. His most recent research on statistical theory and methodology addressed a wide range of challenges including high dimensionality, complex dependencies, and space and time variations. His research in high-frequency financial data tackled problems with high dimensionality, which is currently a hot topic in statistics. He also works on developing novel spatio-temporal models that provide early and accurate detection of disease outbreaks using syndrome (collection of clinical symptoms) data that are monitored as indicators of potential disease outbreaks. These models can also be applied to threats such as biological weapon attacks.
Zou plans to continue to focus on these two areas of research at WPI. In financial statistics, “I will focus on developing novel methods for large volatility matrix estimation and inference, asset allocation and risk analysis, and evaluate its performance based on high frequency financial data,” Zou said. “I anticipate of my research on models that handle patterns of space-time correlation will be numerous and diverse, because a more accurate statistical model for large data sets has immediate relevance to many problems in finance, epidemiology and public health. I would like to explore opportunities of collaborations with scientists from different areas such as physical sciences, engineering, biological and clinical research. I believe that combining all the talented mind of different expertise, we can make our lives much better.”
Dr. Zou enjoys teaching at all levels and wide ranges of statistics courses. He has been enthusiastically involved in student advising and mentoring. He believes that the objectives of teaching are to give to the students the best possible preparation for their future studies and for their future employments, to make them able to master the concepts they are learning, and to give them the ability to use it creatively in more complex contexts as well as develop it further to suit more general problems.
Scholarly Work
A Spatio-Temporal Absorbing State Model for Disease and Syndromic Surveillance 2012
Large Volatility Matrix Inference via Combining Low-Frequency and High-Frequency Approaches. Journal of the American Statistical Association. 2011