Research Interests

My research interests include time series, spatio-temporal statistics, biostatistics, Bayesian statistics, functional data analysis, econometrics, machine learning, point processes, semi-parametrics and non-parametrics. I am particularly interested in high dimensional data analysis, which has become one of the most important areas of statistical research, with applications in many fields. While many recent efforts have attempted to incorporate mathematical and contextual constraints into analysis, most work on these difficult problems has focused on independent observations. I have found dependence to be a valuable source of additional information, not merely an additional complexity, and I endeavor to make major contributions to this exciting new field.

As a statistician interested in applications, my primary research focus has involved the analysis of dependent data and the development of accompanying statistical methodology. My research has been heightened by biological, environmental, economic and operational applications. My collaborations with scientists and other professionals continue to be mutually rewarding and personally enjoyable. Below are some comments on recent research, and many recent manuscripts are available here:arXiv.

  • Multivariate Time Series
  • Signal Processing
  • Spatio-Temporal Modeling
  • Functional Data Analysis
  • Multivariate Statistics
  • Machine Learning
  • Dimension Reduction
  • Bayesian Analysis
  • Semiparametrics
  • Nonparametrics
  • Disability
  • Biostatistics
  • Sustainable Energy
  • Emergency Medical Services
  • Financial Econometrics

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