Research

 

Duke Statistical Science is distinguished by its leadership in the development of theory and methodology of modern, stochastic model-based statistical analysis and Bayesian methods,  their integration with research in advanced scientific computation, and collaborative inter-disciplinary applications in many fields.  See the current list of Major Disciplinary/Core Research Areas and associated faculty under Faculty Research Areas.

  

Methodological research is synergistic with inter-disciplinary applications - key current areas include:

Computational Biology & Statistical Genetics

  • Cancer genetics, risk modeling, genetic epidemiology
  • Imaging in systems biology
  • Stochastic modeling in molecular biochemistry and biophysics
  • Statistical modeling in systems biology: inference in dynamic stochastic cellular and genetic networks

Biomedical Statistics:

  • Biostatistics and health care policy
  • Spatial epidemiology
  • Large-scale genetic profiling in clinical studies
  • Neuroscience

Computing, Natural and Engineering Sciences

  • Computer simulation and applied inverse problems
  • Signal processing/communications, and network traffic
  • High-energy physics, physical chemistry, and materials science
  • Applications in Astronomy

Environmental and Ecological Sciences:

  • Ecological forecasting, biodiversity/abundance
  • Pollutant modeling and monitoring, spatial statistics, remote sensing
  • Atmospheric sciences -- computer model evaluation

Social and Economic Sciences:

  • Finance and financial time series: multivariate volatility models and portfolio selection
  • Macro-economic time series: multi-variate and matrix-variate models
  • Causal inference and disclosure avoidance
  • Statistics in government and policy.