Vogelstein, Joshua

Assistant Professor
Biomedical EngineeringBME Profile

Clark Hall 317C
jovo@jhu.edu

Jump to:

News

About

Education
  • Ph.D. 2010, School of Medicine
  • Bachelor of Science 2002, Washington University St. Louis
Experience
  • 2015 - Present:  Joint, SOM Neuroscience

Publications

Journal Articles
  • Cohen JD, Li L, Wang Y, Thoburn C, Afsari B, Danilova L, Douville C, Javed AA, Wong F, Mattox A, Hruban RH, Wolfgang CL, Goggins MG, Molin MD, Wang T-L, Roden R, Klein AP, Ptak J, Dobbyn L, Schaefer J, Silliman N, Popoli M, Vogelstein JT, Browne JD, Schoen RE, Brand RE, Tie J, Gibbs P, Wong H-L, Mansfield AS, Jen J, Hanash SM, Falconi M, Allen PJ, Zhou S, Bettegowda C, Diaz LA, Tomasetti C, Kinzler KW, Vogelstein B, Lennon AM, Papadopoulos N (2018).  Detection and localization of surgically resectable cancers with a multi-analyte blood test.  Science.  359(6378).
  • Zheng D, Mhembere D, Vogelstein JT, Priebe CE, Burns R (2018).  FlashR: Parallelize and scale R for machine learning using SSDs.  Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP.
  • Wang Q, Zhang M, Tomita T, Vogelstein JT, Zhou S, Papadopoulos N, Kinzler KW, Vogelstein B (2017).  Selected reaction monitoring approach for validating peptide biomarkers.  Proceedings of the National Academy of Sciences of the United States of America.  114(51).
  • Durante D, Dunson DB, Vogelstein JT (2017).  Nonparametric Bayes Modeling of Populations of Networks.  Journal of the American Statistical Association.  112(520).
  • Dyer EL, Roncal WG, Prasad JA, Fernandes HL, Gürsoy D, De Andrade V, Fezzaa K, Xiao X, Vogelstein JT, Jacobsen C, Körding KP, Kasthuri N (2017).  Quantifying mesoscale neuroanatomy using X-ray microtomography.  eNeuro.  4(5).
  • Mhembere D, Zheng D, Priebe CE, Vogelstein JT, Burns R (2017).  Knor: A NUMA-optimized in-memory, distributed and semi-external-memory k-means library.  HPDC 2017 - Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing.
  • Shen C, Vogelstein JT, Priebe CE (2017).  Manifold matching using shortest-path distance and joint neighborhood selection.  Pattern Recognition Letters.  92.
  • Binkiewicz N, Vogelstein JT, Rohe K (2017).  Covariate-assisted spectral clustering.  Biometrika.  104(2).
  • Hildebrand DGC, Cicconet M, Torres RM, Choi W, Quan TM, Moon J, Wetzel AW, Scott Champion A, Graham BJ, Randlett O, Plummer GS, Portugues R, Bianco IH, Saalfeld S, Baden AD, Lillaney K, Burns R, Vogelstein JT, Schier AF, Lee WCA, Jeong WK, Lichtman JW, Engert F (2017).  Whole-brain serial-section electron microscopy in larval zebrafish.  Nature.  545(7654).
  • Kiar G, Gorgolewski KJ, Kleissas D, Roncal WG, Litt B, Wandell B, Poldrack RA, Wiener M, Vogelstein RJ, Burns R, Vogelstein JT (2017).  Science in the cloud (SIC): A use case in MRI connectomics.  GigaScience.  6(5).
  • Zheng D, Mhembere D, Lyzinski V, Vogelstein JT, Priebe CE, Burns R (2017).  Semi-external memory sparse matrix multiplication for billion-node graphs.  IEEE Transactions on Parallel and Distributed Systems.  28(5).
  • Simhal AK, Aguerrebere C, Collman F, Vogelstein JT, Micheva KD, Weinberg RJ, Smith SJ, Sapiro G (2017).  Probabilistic fluorescence-based synapse detection.  PLoS Computational Biology.  13(4).
  • Chen S, Liu K, Yang Y, Xu Y, Lee S, Lindquist M, Caffo BS, Vogelstein JT (2017).  An M-estimator for reduced-rank system identification.  Pattern Recognition Letters.  86.
  • Kutten KS, Charon N, Miller MI, Ratnanather JT, Matelsky J, Baden AD, Lillaney K, Deisseroth K, Ye L, Vogelstein JT (2017).  A large deformation diffeomorphic approach to registration of CLARITY images via mutual information.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  10433 LNCS.
  • Tomita TM, Maggioni M, Vogelstein JT (2017).  ROFLMAO: Robust oblique forests with linear MAtrix operations.  Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017.
  • Airan RD, Vogelstein JT, Pillai JJ, Caffo B, Pekar JJ, Sair HI (2016).  Factors affecting characterization and localization of interindividual differences in functional connectivity using MRI.  Human Brain Mapping.  37(5).
  • Chen L, Shen C, Vogelstein JT, Priebe CE (2016).  Robust Vertex Classification.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(3).
  • Koutra D, Shah N, Vogelstein JT, Gallagher B, Faloutsos C (2016).  DELTACON: Principled massive-graph similarity function with attribution.  ACM Transactions on Knowledge Discovery from Data.  10(3).
  • Kutten KS, Vogelstein JT, Charon N, Ye L, Deisseroth K, Miller MI (2016).  Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM.  Proceedings of SPIE - The International Society for Optical Engineering.  9896.
  • Lyzinski V, Fishkind DE, Fiori M, Vogelstein JT, Priebe CE, Sapiro G (2016).  Graph Matching: Relax at Your Own Risk.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  38(1).
  • Priebe CE, Sussman DL, Tang M, Vogelstein JT (2015).  Statistical Inference on Errorfully Observed Graphs.  Journal of Computational and Graphical Statistics.  24(4).
  • Harris KM, Spacek J, Bell ME, Parker PH, Lindsey LF, Baden AD, Vogelstein JT, Burns R (2015).  A resource from 3D electron microscopy of hippocampal neuropil for user training and tool development.  Scientific Data.  2.
  • Gray Roncal WR, Kleissas DM, Vogelstein JT, Manavalan P, Lillaney K, Pekala M, Burns R, Vogelstein RJ, Priebe CE, Chevillet MA, Hager GD (2015).  An automated images-to-graphs framework for high resolution connectomics.  Frontiers in Neuroinformatics.  9(AUGUST).
  • Kasthuri N, Hayworth KJ, Berger DR, Schalek RL, Conchello JA, Knowles-Barley S, Lee D, Vázquez-Reina A, Kaynig V, Jones TR, Roberts M, Morgan JL, Tapia JC, Seung HS, Roncal WG, Vogelstein JT, Burns R, Sussman DL, Priebe CE, Pfister H, Lichtman JW (2015).  Saturated Reconstruction of a Volume of Neocortex.  Cell.  162(3).
  • Lyzinski V, Sussman DL, Fishkind DE, Pao H, Chen L, Vogelstein JT, Park Y, Priebe CE (2015).  Spectral clustering for divide-and-conquer graph matching.  Parallel Computing.  47.
  • Vogelstein JT, Priebe CE (2015).  Shuffled Graph Classification: Theory and Connectome Applications.  Journal of Classification.  32(1).
  • Vogelstein JT, Conroy JM, Lyzinski V, Podrazik LJ, Kratzer SG, Harley ET, Fishkind DE, Vogelstein RJ, Priebe CE (2015).  Fast Approximate Quadratic programming for graph matching.  PLoS ONE.  10(4).
  • Weiler NC, Collman F, Vogelstein JT, Burns R, Smith SJ (2014).  Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.  Scientific Data.  1.
  • Burns R, Vogelstein J, Szalay AS (2014).  From cosmos to connectomes: the evolution of data-intensive science..  Neuron.  83(6).  1249-52.
  • Sweeney EM, Vogelstein JT, Cuzzocreo JL, Calabresi PA, Reich DS, Crainiceanu CM, Shinohara RT (2014).  A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.  PLoS ONE.  9(4).
  • Vogelstein J, Park Y, Ohyama T, Kerr RA, Truman JW, Priebe C, Zlatic M (2014).  Discovery of brainwide neural-behavioral maps via multiscale unsupervised structure learning..  Science.  344(6182).  386-392.
  • Priebe C, D.L.Sussman , M.Tang , Vogelstein J (2014).  Statistical inference on errorfully observed graphs.  Journal of Computational and Graphical Statistics.
  • Carlson DE, Vogelstein JT, Wu Q, Lian W, Zhou M, Stoetzner CR, Kipke D, Weber D, Dunson DB, Carin L (2014).  Multichannel electrophysiological spike sorting via joint dictionary learning and mixture modeling.  IEEE Transactions on Biomedical Engineering.  61(1).
  • Vogelstein JT, Park Y, Ohyama T, Kerr RA, Truman JW, Priebe CE, Zlatic M (2014).  Discovery of brainwide neural-behavioral maps via multiscale unsupervised structure learning.  Science.  344(6182).
  • Cornelis B, Yang Y, Vogelstein JT, Dooms A, Daubechies I, Dunson D (2013).  Bayesian crack detection in ultra high resolution multimodal images of paintings.  2013 18th International Conference on Digital Signal Processing, DSP 2013.
  • Mhembere D, Gray Roncal W, Sussman D, Priebe CE, Jung R, Ryman S, Vogelstein RJ, Vogelstein JT, Burns R (2013).  Computing scalable multivariate glocal invariants of large (brain-) graphs.  2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings.
  • Roncal WG, Koterba ZH, Mhembere D, Kleissas DM, Vogelstein JT, Burns R, Bowles AR, Donavos DK, Ryman S, Jung RE, Wu L, Calhoun V, Vogelstein RJ (2013).  MIGRAINE: MRI graph reliability analysis and inference for connectomics.  2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings.
  • Kulkarni V, Pudipeddi JS, Akoglu L, Vogelstein JT, Jacob Vogelstein R, Ryman S, Jung RE (2013).  Sex differences in the human connectome.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  8211 LNAI.
  • Priebe CE, Vogelstein J, Bock D (2013).  Optimizing the quantity/quality trade-off in connectome inference.  Communications in Statistics - Theory and Methods.  42(19).
  • Burns R, Roncal WG, Kleissas D, Lillaney K, Manavalan P, Perlman E, Berger DR, Bock DD, Chung K, Grosenick L, Kasthuri N, Weiler NC, Deisseroth K, Kazhdan M, Lichtman J, Reid RC, Smith SJ, Szalay AS, Vogelstein JT, Vogelstein RJ (2013).  The open connectome project data cluster: Scalable analysis and vision for high-throughput neuroscience.  ACM International Conference Proceeding Series.
  • Vogelstein J, Gray WR, Vogelstein RJ, Priebe C (2013).  Graph Classification using Signal Subgraphs: Applications in Statistical Connectomics.  IEEE transactions on pattern analysis and machine intelligence.  35(7).  1539-1551.
  • Vogelstein JT, Roncal WG, Jacob Vogelstein R, Priebe CE (2013).  Graph classification using signal-subgraphs: Applications in statistical connectomics.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  35(7).
  • Craddock RC, Jbabdi S, Yan CG, Vogelstein JT, Castellanos FX, Di Martino A, Kelly C, Heberlein K, Colcombe S, Milham MP (2013).  Imaging human connectomes at the macroscale.  Nature Methods.  10(6).
  • Dai D, He H, Vogelstein JT, Hou Z (2013).  Accurate prediction of AD patients using cortical thickness networks.  Machine Vision and Applications.  24(7).
  • Carlson D, Rao V, Vogelstein J, Carin L (2013).  Real-time inference for a gamma process model of neural spiking.  Advances in Neural Information Processing Systems.
  • Burns R, Roncal WG, Kleissas D, Lillaney K, Manavalan P, Perlman E, Berger DR, Bock DD, Chung K, Grosenick L, Kasthuri N, Weiler NC, Deisseroth K, Kazhdan M, Lichtman J, Reid RC, Smith SJ, Szalay AS, Vogelstein J, Vogelstein RJ (2013).  The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience..  Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management.
  • Petralia F, Vogelstein J, Dunson DB (2013).  Multiscale dictionary learning for estimating conditional distributions.  Advances in Neural Information Processing Systems.
  • Fishkind D, D.L.Sussman , M.Tang , Vogelstein J, Priebe C (2013).  Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown.  Siam Journal on Matrix Analysis and Applications.  34.  23-39.
  • Fiori M, Sprechmann P, Vogelstein J, Musé P, Sapiro G (2013).  Robust multimodal graph matching: Sparse coding meets graph matching.  Advances in Neural Information Processing Systems.
  • Priebe C, Vogelstein J, Bock D (2013).  Optimizing the Quantity/Quality Trade-Off in Connectome Inference.  Communications in Statistics-Theory and Methods.  42(19).  3455-3462.
  • Koutra D, Vogelstein JT, Faloutsos C (2013).  DeltaCon: A principled massive-graph similarity function.  SIAM International Conference on Data Mining 2013, SMD 2013.
  • Fishkind DE, Sussman DL, Tang M, Vogelstein JT, Priebe CE (2012).  Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown.  SIAM Journal on Matrix Analysis and Applications.  34(1).
  • Vogelstein B, Roberts NJ, Vogelstein JT, Parmigiani G, Kinzler KW, Velculescu VE (2012).  Response to comments on "The predictive capacity of personal genome sequencing".  Science Translational Medicine.  4(135).
  • Roberts NJ, Vogelstein JT, Parmigiani G, Kinzler KW, Vogelstein B, Velculescu VE (2012).  The predictive capacity of personal genome sequencing.  Science Translational Medicine.  4(133).
  • Gray WR, Bogovic JA, Vogelstein JT, Landman BA, Prince JL, Vogelstein RJ (2012).  Magnetic resonance connectome automated pipeline: An overview.  IEEE Pulse.  3(2).
  • Gray WR, Bogovic JA, Vogelstein J, Landman BA, Prince J, Vogelstein R (2012).  Magnetic resonance connectome automated pipeline: an overview.  IEEE Pulse.  3(2).  42-48.
  • Fishkind D, Sussman DL, Tang M, Vogelstein J, Priebe C (2012).  Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown.  SIAM Journal on Matrix Analysis and Applicationsins.  stat.ME.
  • Vogelstein JT, Vogelstein RJ, Priebe CE (2011).  Are mental properties supervenient on brain properties?.  Scientific Reports.  1.
  • Dai D, He H, Vogelstein J, Hou Z (2011).  Network-based classification using cortical thickness of AD patients.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  7009 LNCS.
  • Yuste R, MacLean J, Vogelstein J, Paninski L (2011).  Imaging action potentials with calcium indicators.  Cold Spring Harbor Protocols.  6(8).
  • Hofer SB, Ko H, Pichler B, Vogelstein J, Ros H, Zeng H, Lein E, Lesica NA, Mrsic-Flogel TD (2011).  Differential connectivity and response dynamics of excitatory and inhibitory neurons in visual cortex.  Nature Neuroscience.  14(8).
  • Ashby C, Bhatia A, Tenore F, Vogelstein J (2011).  Low-cost electroencephalogram (EEG) based authentication.  2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011.
  • Mishchenko Y, Vogelstein JT, Paninski L (2011).  A bayesian approach for inferring neuronal connectivity from calcium fluorescent imaging data.  Annals of Applied Statistics.  5(2 B).
  • Vogelstein J, Vogelstein RJ, Priebe C (2011).  Are mental properties supervenient on brain properties?.  Scientific Reports.  1.
  • Vogelstein JT, Packer AM, Machado TA, Sippy T, Babadi B, Yuste R, Paninski L (2010).  Fast nonnegative deconvolution for spike train inference from population calcium imaging.  Journal of Neurophysiology.  104(6).
  • Paninski L, Ahmadian Y, Ferreira DG, Koyama S, Rahnama Rad K, Vidne M, Vogelstein J, Wu W (2010).  A new look at state-space models for neural data.  Journal of Computational Neuroscience.  29(1-2).
  • Vogelstein J, Harshbarger S, McLoughlin M, Beaty J, Yantis S, Connor C, Thakor N, Priebe C, Etienne-Cummings R (2010).  Research Program in Applied Neuroscience.  Johns Hopkins APL technical digest.  28(3).  222-223.
  • Huys QJM, Vogelstein JT, Dayan P (2009).  Psychiatry: Insights into depression through normative decision-making models.  Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference.
  • Vogelstein J, Watson B, Packer A, Jedynak B, Yuste R, Paninski L (2009).  Model-based optimal inference of spike times and calcium dynamics given noisy and intermittent calcium-fluorescence imaging.  Biophysical Journal.  97.  636-655.
  • Vogelstein JT, Watson BO, Packer AM, Yuste R, Jedynak B, Paninskik L (2009).  Spike inference from calcium imaging using sequential Monte Carlo methods.  Biophysical Journal.  97(2).
  • Vogelstein J, Watson BO, Packer AM, Yuste R, Jedynak B, Paninski L (2009).  Spike inference from calcium imaging using sequential Monte Carlo methods.  Biophysical journal.  97(2).  636-655.
  • Pouliquen P, Vogelstein J, Etienne-Cummings R (2008).  Practical considerations for the use of a Howland current source for neuro-stimulation.  2008 IEEE-BIOCAS Biomedical Circuits and Systems Conference, BIOCAS 2008.
  • Vogelstein RJ, Mallik U, Vogelstein JT, Cauwenberghs G (2007).  Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses.  IEEE Transactions on Neural Networks.  18(1).
  • Greenspan DL, Connolly DC, Wu R, Lei RY, Vogelstein JTC, Kim YT, Mok JE, Muñoz N, Bosch FX, Shah K, Cho KR (1997).  Loss of FHIT expression in cervical carcinoma cell lines and primary tumors.  Cancer Research.  57(21).
  • Vogelstein J, Priebe C (2013).  Shuffled Graph Classification: Theory and Connectome Applications.  Journal of Classification.
  • Priebe C, Sussman DL, Tang M, Vogelstein J (2014).  Statistical inference on errorfully observed graphs.  Journal of Computational and Graphical Statistics.
Books
  • Vogelstein J, Zhang K, Jedynak B, Paninski L (2007).  Inferring the structure of populations of neurons using a sequential Monte Carlo EM algorithm.  COSYNE.
Book Chapters
  • Ashby C, Etienne-Cummings R, Vogelstein J (2014).  Locomotion Motor Control.  Event-Based Neuromorphic Systems.
  • Mazurek K, Vogelstein J, Etienne-Cummings R (2009).  Neuromorphic Hardware for Control.  Biohybrid Systems: Nerves, Interfaces, and Machines.
Conference Proceedings
  • Mhembere D, Gray Roncal W, Sussman D, Priebe C, Jung R, Ryman S, Vogelstein RJ, Vogelstein J, Burns R (2013).  Computing Scalabal Multiavriate Global Invariants of Large (Brain-) Graphs.  Global Conference on Signal and Information Processing (GlobalSIP).  297-300.
  • Gray Roncal W, Koterba ZH, Mhembere D, Kleissas DM, Vogelstein J, Burns R, Bowles AR, Donavos DK, Ryman S, Jung RE, others (2013).  MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics.  Global Conference on Signal and Information Processing (GlobalSIP).  313-316.
  • Gray WR, Bogovic JA, Vogelstein J, Ye C, Landman BA, Prince J, Vogelstein RJ (2011).  Magnetic resonance connectome automated pipeline and repeatability analysis.  Annual Meeting of the Society for Neuroscience.
  • Vogelstein J, Gray W, Vogelstein RJ, Bogovic J, Resnick S, Prince J, Priebe C (2011).  Connectome classification: statistical graph theoretic methods for analysis of MR-connectome data.  Annual Meeting of the Organization for Human Brain Mapping.
  • Vogelstein J, Gray WR, Martin J, Coppersmith G, Dredze M, Bogovic J, Prince J, Resnick SM, Priebe C, Vogelstein RJ (2011).  Connectome classification using statistical graph theory and machine learning.  Annual Meeting of the Society for Neuroscience.
  • Vogelstein J, Bogovic J, Carass A, Gray WR, Prince J, Landman B, Pham D, Ferrucci L, Resnick SM, Priebe C, others (2010).  Graph-Theoretical Methods for Statistical Inference on MR Connectome Data.  Annual Meeting of the Organization for Human Brain Mapping, Barcelona.
Back to top