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.
