Other: Events Press Awards Funding Talks Posters Publication type: Invited Other Talks Invited J. Chung. Statistical Methods for Population of Connectomes . Organization of Human Brain Mapping , 2019. J. T. Vogelstein. Open Access to the Brain: a Computer "Connectome" Links Brain Images in Fine Detail . JHM Boot Camp , 2019. J. T. Vogelstein. Statistical Foundations For Connectomics . Max Planck / HHMI Connectomics Meeting , 2019. J. T. Vogelstein. Big Biomedical Data Science . Sol Goldman International Conference , 2019. J. T. Vogelstein. Connectal Coding . Dipy Workshop , 2019. J. T. Vogelstein. Connectome Coding . Society for Neuroscience , 2018. J. T. Vogelstein. A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data . Princeton , 2018. E. W. Bridgeford. A High-Throughput Pipeline Identifies Robust Connectomes but Troublesome Variability . Organization of Human Brain Mapping , 2018. E. Perlman. NeuroData: Embracing Open Source for Big Data Neuroscience . NSF NeuroNex Workshop on Super 3DEM , 2018. J. T. Vogelstein. Using Big Data Science to Understand What Goes On in our Heads . SOHOP Faculty Spotlight , 2018. J. T. Vogelstein. Discovering Relationships and their Geometry Across Disparate Data Modalities . Yale , 2018. J. T. Vogelstein. Discovering Relationships and their Geometry Across Disparate Data Modalities . Stanford , 2017. J. T. Vogelstein. Using Big Data Science to Understand What Goes on in Our Heads . SOHOP Faculty Spotlight , 2017. J. T. Vogelstein. Challenges and Opportunities in Big Data for Neuroscientists . Society for Neuroscience: DC Metro Area Chapter Keynote Address , 2017. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience . Society for Neuroscience , 2017. J. T. Vogelstein. Using Big Data Science to Understand What Goes on in Our Heads . SOHOP Faculty Spotlight , 2016. J. T. Vogelstein. NeuroData: Enabling Terascale Neuroscience for Everyone . Keystone Symposia: State of the Brain , 2016. J. T. Vogelstein. The International Brain Station (TIBS) . Kavli Foundation , 2016. J. T. Vogelstein. The International Brain Station (TIBS) . United Nations Global Brain Workshop Meeting , 2016. J. T. Vogelstein and L. Paninski. Spike inference from calcium imaging using sequential Monte Carlo methods . AMSI Program on Sequential Monte Carlo , 2015. J. T. Vogelstein. Top Challenges of Big Data Neuroscience . BRAIN Initiative Workshop , 2014. J. T. Vogelstein. Big (Neuro) Statistics . Kavli Salon , 2014. J. T. Vogelstein. Open-Science Platform for Heterogeneous Brain Data: Opportunities and Challenges . Kavli , 2014. J. T. Vogelstein. Beyond Little Neuroscience . Beyond Optogenetics workshop at Cosyne , 2013. J. T. Vogelstein. Statistical Inference on Graphs. University of Michigan , 2013. J. T. Vogelstein. Statistical Inference on Graphs. Scientific Computing Institute, University of Utah , 2013. J. T. Vogelstein. BIG NEURO . Theory and Neurobiology, Duke University , 2012. J. T. Vogelstein. Connectome Classification: Statistical Graph Theoretic Methods for Analysis of MR-Connectome Data . Organization for Human Brain Mapping , 2011. J. T. Vogelstein. Consistent Connectome Classification . Math/Bio Seminar, Duke University , 2011. J. T. Vogelstein. Once we get connectomes, what the \%\#* are we going to do with them? Krasnow Institute for Advanced Study at George Mason Univeristy , 2011. J. T. Vogelstein. Once we get connectomes, what the \%\#* are we going to do with them? Institute of Neuroinformatics , 2011. J. T. Vogelstein. Statistical Connectomics . Harvard University Connectomics Labs , 2011. J. T. Vogelstein. What can Translational neuroimaging Research do for Clinical Practice. Child Mind Institute , 2011. J. T. Vogelstein. Inferring Spike Trains Given Calcium-Sensitive Fluorescence Observations. Statistical Analysis of Neural Data , 2008. J. T. Vogelstein. Inferring spike trains from Calcium Imaging . Redwood Center for Theoretical Neuroscience, University of California, Berkeley , 2008. J. T. Vogelstein. Inferring spike trains from Calcium Imaging . Cambridge University, Gatsby Unit, and University College London , 2008. J. T. Vogelstein. Model based optimal inference of spike times and calcium dynamics givern noisy and intermittent calcium-fluorescence observations. Neurotheory Center of Columbia University , 2007. Other J. T. Vogelstein. Ailey in an Hour: (A "Soup-to-Nuts" Pipeline for Analysis of Whole Cleared Brain Data) . NeuroNex , 2019. J. T. Vogelstein, H. Helm, R. Mehta, C. E. Priebe, and R. Arora. A Theory and Practice of the Lifelong Learnable . L2M , 2019. J. T. Vogelstein and R. Burns. Data Science Core . Harvard University , 2019. J. Browne. Forest Packing: Fast Parallel, Decision Forests . SIAM International Conference on Data Mining , 2019. D. Tward. Brain mapping tools for neuroscience research . NeuroNex , 2019. J. T. Vogelstein. Big Data and the Life Sciences . Sloan Foundation , 2019. J. T. Vogelstein. Journey to Here . JHU BMES talks , 2019. J. T. Vogelstein. NeuroData (Science) . Kavli , 2019. J. T. Vogelstein. Lifelong Learning Forests . L2M , 2019. J. T. Vogelstein. NeuroData Tools . NeuroData Hackashop , 2019. J. T. Vogelstein. Biomedical Big Data and Data Science . JHU BME , 2019. J. T. Vogelstein. NeuroData: A Community-developed open-source computational ecosystem for big neuro data . NeuroNex , 2018. C. Shen. The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing. Joint Statistical Meeting , 2018. J. T. Vogelstein. Multiscale Graph Correlation: A Knowledge Representation System for Discovering Latent Geometric Structure . DARPA SIMPLEX PI Review Meeting , 2018. J. T. Vogelstein and V. Chandrashekhar. NeuroNex + Stanford . NeuroNex-Stanford , 2018. G. Kiar. Connectome Coding: what is it, how do we do it, and why do we care? Data science in Neuroscience Symposium , 2018. J. T. Vogelstein. Data Intensive Brain Science . Kavli Neuroscience Discovery Institute , 2018. J. T. Vogelstein. Lifelong Learning Forests . Darpa L2M PI Meeting , 2018. J. T. Vogelstein. Engineering the Future of Medicine: Data Intensive Biomedical Science . Johns Hopkins University Biomedical Engineering , 2018. D. Mhembere. knor: a NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means library . HPDC , 2017. G. Kiar. Science in the Cloud (SIC): A use-case in MRI Connectomics. Open Science Special Interest Group , 2017. Y. Lee. Network Dependence Testing via Diffusion Maps and Distance-Based Correlations . Joint Statistical Meetings , 2017. D. Mhembere. knor: K-means NUMA Optimized Routines Library . High-Performance Parallel and Distributed Computing , 2017. T. M. Tomita. ROFLMAO: Robust Oblique Forests with Linear Matrix Operations . SIAM International Conference on Data Mining 2017 , 2017. J. T. Vogelstein. Challenges and Opportunities in Big Data for Neuroscientists . Society for Neuroscience: DC Metro Area Chapter Keynote Address , 2017. J. T. Vogelstein. NeuroData . 2017. J. T. Vogelstein. The International Brain Station (TIBS) . JHU BME and Tsinghua University , 2017. J. T. Vogelstein. Connectome Coding . Schmidt Sciences , 2017. J. T. Vogelstein. NeuroStorm . Global Brain Workshop 2 JHU , 2017. C. Shen. Multiscale Generalized Correlation. Joint Statistical Meeting , 2016. J. T. Vogelstein. NeuroData:Enabling Terascale Neuroscience . JHU Kavli Neuroscience Discovery Institute , 2016. J. T. Vogelstein. The International Brain Station (TIBS) . Kavli Foundation , 2016. J. T. Vogelstein. NeuroData 2016 . NeuroData Lab Retreat , 2016. J. T. Vogelstein. Global Brain Workshop 2016 . Global Brain Workshop NSF+JHU at Kavli , 2016. J. T. Vogelstein. Global Brain Workshop 2016 . Kavli Neuroscience Discovery Institute & Center for Imaging Science , 2016. J. T. Vogelstein. NeuroData:Enabling Terascale Neuroscience . Kavli Neuroscience Discovery Institute & Center for Imaging Science , 2016. J. T. Vogelstein. Learning a Data-Driven Nosology:Progress, Challenges & Opportunities . Kavli Neuroscience Discovery Institute & Center for Imaging Science , 2016. J. T. Vogelstein, M. I. Miller, and R. Hunganir. Global Brain Workshop 2016 . Kavli Neuroscience Discovery Institute & Center for Imaging Science @ JHU , 2016. C. Shen. Local Distance Correlation for Testing Independence. Temple University , 2015. J. T. Vogelstein. Research Computing Support for Neuroscience and Other Life Sciences . CASC , 2015. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data . SIMPLEX Kickoff , 2015. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data: Part 1 . DARPA SIMPLEX PI Meeting , 2015. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data: Part 2 . DARPA SIMPLEX PI Meeting , 2015. J. T. Vogelstein. Special Symposium: Neuroscience in the 21st Century . Kavli , 2015. J. T. Vogelstein. Law of Large Graphs . DARPA Graphs , 2015. J. T. Vogelstein. Open Connectome Project: Lowering the Barrier to Entry of Big Data Neuroscience . Institute for Computational Medicine at Johns Hopkins University , 2015. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience . DoE , 2015. J. T. Vogelstein. big time (series data in neuroscience) . figshare , 2015. J. T. Vogelstein. Open Source Platform for Heterogenous Brain Data . figshare , 2015. J. T. Vogelstein. Big Statistics for Brain Sciences . Baylor College of Medicine, Department of Neuroscience , 2014. J. T. Vogelstein. Big (Neuro) Statistics . Kavli Salon , 2014. J. T. Vogelstein. Open Problems in Neuropsychiatry . Data Seminar, Duke University , 2013. J. T. Vogelstein. Statistical Models and Inference for big Brain-Graphs . NIPS Workshop on Acquiring and analyzing the activity of large neural ensembles , 2013. J. T. Vogelstein. Decision Theoretic Approach to Statistical Inference. guest Lecture in Current Topics in Machine Learning, Johns Hopkins University , 2012. J. T. Vogelstein. Open Connectome Project. Academic Medical Center, Amsterdam , 2012. J. T. Vogelstein. Are mental properties supervenient on brain properties . None 2011. J. T. Vogelstein. Consistent Graph Classification . Guest Lecture in Deisseroth Lab, Stanford University , 2011. J. T. Vogelstein. Neurocognitive Graph Theory . National Security Agency , 2009. J. T. Vogelstein. OOPSI: A Family of Optimal OPtical Spike Inference Algorithms for Inferring Neural Connectivity from Population Calcium Imaging . Dissertation Defense , 2009. J. T. Vogelstein. Sequential Monte Carlo in Neuroscience. SAMSI Program on Sequential Monte Carlo, Tracking Working Group , 2009. J. T. Vogelstein. Towards Inference and Analaysis of Neural Circuits Inferred from Population Calcium Imaging . Guest Lecture in Schnitzer Lab , 2009. J. T. Vogelstein. Towards Inferring Neural Circuits from Calcium Imaging . Guest Lecture in Yuste Lab , 2009. J. T. Vogelstein. Inferring spike times given typical time-series fluorescence observations . Department of Applied Mathematics and Statistics, Johns Hopkins University , 2008.