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Pediatrics - Neurology/

Houston, Texas

Pediatrics - Neurology and Developmental Neuroscience
Pediatrics - Neurology/
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Genevera Allen, Ph.D.

Assistant Genevera Allen, Ph.D.Professor
Statistician- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital

Contact Information:
Genevera Allen, Ph.D.
Jan and Dan Duncan Neurology Research Institute
at Texas Children's Hospital
1250 Moursund St., Suite N1365.16
Houston, TX 77030-2399
Tel: 832-824-8879
Fax: 832-825-1251


Ph.D. - Stanford University

Research Interests

  • Statistical methodology for dependencies in high-dimensional data. I develop models to understand the relationships among entities in large data sets. For example, functional MRIs take three-dimensional images of the brain over time. Each entity in the image, the voxel, represents a specific location in the brain. Thus, the voxels have both spatial (location) dependencies and temporal (time) dependencies. My research goals are to make sense of these relationships so that we can better understand the signal in the data. (In fMRIs, for example, the signal is which regions in the brain activate in response to stimuli.) Specifically, my research interests are statistical learning, applied multivariate analysis, high-dimensional data, convex optimization and applications to bioinformatics and neuroimaging

Professional Memberships

  • American Statistical Association
  • Institute of Mathematical Statistics
  • International Biometrics Society
  • Organization for Human Brain Mapping.

Recent Publications

Statistical Theory and Methods

  • G. I. Allen and R. Tibshirani, “Transposable regularized covariance models with an applicationto missing data imputation”, Annals of Applied Statistics, 4:2, 764-790, 2010.
  • G. I. Allen, “Comment on Article by Hoff”, Bayesian Analysis, 6:2, 197-202, 2011.
  • G. I. Allen and M. Maletic-Savatic , “Sparse Non-negative Generalized PCA with Applications
    to Metabolomics”, (To Appear) Bioinformatics, 2011.
  • G. I. Allen, “Automatic Feature Extraction via Weighted Kernels and Regularization”,
    (arXiv:0906.4391), 2010.
  • G. I. Allen and R. Tibshirani, “Inference with Transposable Data: Modeling the Effects of
    Row and Column Correlations”, (arXiv:0906.3465), 2010.
  • G. I. Allen, L. Grosenick and J. Taylor, “A Generalized Least Squares Matrix Decomposition”,
    (arXiv:1102.3074, Rice University Technical Report No. TR2011-03), 2011.
  • G. I. Allen, “A Sparse Higher-Order SVD”, (Submitted), 2011.

Book Chapters

  • G. I. Allen and P. O. Perry, “Singular value decomposition for high-dimensional data”,
    Article to appear in Encyclopedia of Environmetrics, 2nd Edition.


  • L.C. Harshman, G. Bepler, Z. Zheng, J.P. Higgins, G. I. Allen, S. Srinivas, “RRM1 expression
    in resectable, muscle invasive urothelial cancer correlates with survival in younger patients”,
    British Journal of Urology International, 106:11,1805-1811, 2010.
  • L.C. Harshman, R.J. Yu, G. I. Allen, S. Srinivas, H.S. Gill, B.I. Chung, “Surgical outcomes
    and complications associated with presurgical tyrosine kinase inhibition for advanced renal
    cell carcinoma (RCC)”, Urologic Oncology, (In press), 2010.

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