Faculty Research

Current research by members of the Boston University Probability and Statistics group includes work in the following areas:

  • Time series analysis (spectral, multiscale, long-memory)
  • Multiscale methods (wavelets, adaptive partitioning)
  • Non-parametric and semi-parametric estimation
  • Statistical learning theory (neural networks, complexity)
  • Network analysis (internet, biological networks, etc.)
  • Functional Data Analysis (remote Sensing Data)
  • Mixture Models and analysis of high-dimensional Data
  • Bayesian Statistics
  • Stochastic simulation and optimization

Much of the above research is done in conjunction with various inter-disciplinary applications, including:

  • Biomedical Statistics (D’Agostino)
    • Longitudinal analysis of cardiovascular data
    • Genetic factors in cardiovascular disease
    • Physician practice patterns for hypertensive & diabetic patients
  • Computational Biology (Carvalho, Kolaczyk, Kon, Ray)
    • Gene Networks
    • Protein Classification and Cancer immunotherapy
    • Analysis of Flow Cytometry Data
  • Image Processing and Geo-spatial analysis (Kolaczyk, Ray)
    • Image classification, deconvolution, and segmentation
    • Remote sensing image analysis
    • Analysis of Climate Ecosystem Dynamics
    • Modes of Variations of Vegetation Indices
  • Analysis of Neural Data (Eden)
    • Point process models of neural spike train data
    • Filtering, smoothing, and prediction from spike
  • Computer Network Traffic Data (Taqqu, Kolaczyk)
    • Scaling properties
    • Traffic characterization and anomaly detection
  • Actuarial Science (Gangophadyay, Lam)
    • Credibility theory
    • Risk Analysis
  • Mathematical Finance (Guasoni, Kardaras)