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Joshua Vogelstein, Visiting Assistant Professor

Joshua Vogelstein

Please note: Joshua has left the Mathematics department at Duke University; some info here might not be up to date.

Contact Info: 
Office Location:  122A Old Chemistry
Office Phone:  (919) 660-2823
Email Address: send me a message
Web Pages:  http://jovo.me
http://openconnecto.me

Education:

PhDJohns Hopkins University2009
MSJohns Hopkins University2009
Specialties:

Applied Math
Research Interests: My primary research aim is to contribute to explaining the mind in terms of the brain in ways that lead to both qualitative insight and quantitative predictions. A significant motivating factor is that all humans have brains, and therefore these developments could directly benefit all of humankind. In alignment with this aim, all of our research products are freely available to all from my webpage.

Keywords:

Complex Hierarchical and Latent Variable Modelling • Decision Theory • High Dimensional Problems • Machine Learning • Manifold Learning • Model Selection • Nonparametric Statistical Modeling

Recent Publications   (More Publications)

  1. Fishkind, Donniell E. and Sussman, Daniel L. and Tang, Minh and Vogelstein, Joshua T. and Priebe, Carey E., Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown, Arxiv preprint (May, 2012), pp. 20, submitted, arXiv:1205.0309v1 [0309]  [abs]
  2. Roberts, N. J. and Vogelstein, Joshua T. and Parmigiani, Giovanni and Kinzler, K. W. and Vogelstein, Bert and Velculescu, Victor E, The Predictive Capacity of Personal Genome Sequencing, Science Translational Medicine (April, 2012), ISSN 1946-6234 [scitranslmed.3003380], [doi]
  3. Joshua T. Vogelstein, William R. Gray, R. Jacob Vogelstein, and Carey E. Priebe, Graph Classification using Signal Subgraphs: Applications in Statistical Connectomics., IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. in press (Accepted, 2012) [1427]
  4. Dai E, He H, Vogelstein JT, Hou Zengguag, Accurate Prediction of AD Patients using Cortical Thickness Networks., Machine Vision and Applications. (Accepted, 2012)
  5. CE Priebe, DL Sussman, M Tang, JT Vogelstein, Statistical inference on errorfully observed graphs, JASA (Submitted, 2012)

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320