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Ciprian M. Crainiceanu, PhD

  • Professor

Departmental Affiliations

Center & Institute Affiliations

Contact Information

615 N. Wolfe Street
Room E3636
Baltimore, Maryland 21205

410-955-3505

http://www.ciprianstats.org

View Current Courses

Education

PhD, Cornell University, 2003
MS, Cornell University, 2002
MS, University of Bucharest, 1998

Overview

My research is centered around Statistical methods for new technologies used in

public health and medical studies. These technologies provide new types of data that are

increasing both in size and complexity. I am interested in developing analytic tools that

are tailored to specific applications, address the particular subtleties of the problem,

and then find the common thread that eventually becomes Statistical methodology. My

current scientific research interest centers around sleep research (EEG, polysomnograms),

wearable computing (accelerometers, heart monitors), and multimodality brain imaging

(SPECT, MRI, CT) with applications to Alzheimer, Multiple Sclerosis, traumatic brain

injury, and cancer. My statistical expertise centers around inferential methods for ultra

high dimensional data, mixed effects modeling, Bayesian inference, and smoothing.

Honors and Awards

Please see my CV for more details

  • Biostatistics
  • Neuroimaging
  • Wearable computing
  • Activity
  • Sleep
  • Multiple Sclerosis
  • Multilevel (hierarchical) Bayesian Inference
  • MCMC
  • Longitudinal Modeling
  • Nonparametric Statistics
  • Smoothing
  • Measurement Error

Selection of recent papers

  • Measurement Error in Nonlinear Models (with R.J. Carroll, D. Ruppert, L.A. Stefanski), Second Edition, 2006
  • Methods in Biostatistics with R, https://leanpub.com/biostatmethods/
  • The upstrap. Crainiceanu CM, Crainiceanu A. Biostatistics. 2018
  • Neuroconductor: an R platform for medical imaging analysis. Muschelli J, Gherman A, Fortin JP, Avants B, Whitcher B, Clayden JD, Caffo BS, Crainiceanu CM. Biostatistics. 2018
  • Longitudinal High-Dimensional Principal Components Analysis with Application to Diffusion Tensor Imaging of Multiple Sclerosis. Zipunnikov V, Greven S, Shou H, Caffo B, Reich DS, Crainiceanu C. Annals of Applied Statistics, 2014, 8(4):2175-2202