Talks

Invited talks
  1. G. Kiar. Connectome Coding: what is it, how do we do it, and why do we care? Data science in Neuroscience Symposium, 2018.
  2. G. Kiar. A Data Driven Approach for Tackling Big Data Connectomics. Feindel Brain Imaging Lecture, 2018.
  3. E. Perlman. NeuroData: Embracing Open Source for Big Data Neuroscience. NSF NeuroNex Workshop on Super 3DEM, 2018.
  4. J. T. Vogelstein. A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data. Princeton, 2018.
  5. J. T. Vogelstein. Data Intensive Brain Science. Kavli Neuroscience Discovery Institute, 2018.
  6. J. T. Vogelstein. Lifelong Learning Forests. 2018.
  7. J. T. Vogelstein. Engineering the Future of Medicine:Data Intensive Biomedical Science. 2018.
  8. J. T. Vogelstein and V. Chandrashekhar. NeuroData. nueronex-stanford, 2018.
  9. G. Kiar. Science in the Cloud (SIC): A use-case in MRI Connectomics. Open Science Special Interest Group, 2017.
  10. Y. Lee. Network Dependence Testing via Diffusion Maps and Distance-Based Correlations. Joint Statistical Meetings, 2017.
  11. D. Mhembere. knor: K-means NUMA Optimized Routines Library. High-Performance Parallel and Distributed Computing, 2017.
  12. T. M. Tomita. ROFLMAO: Robust Oblique Forests with Linear Matrix Operations. SIAM International Conference on Data Mining 2017, 2017.
  13. J. T. Vogelstein. Challenges and Opportunities in Big Data for Neuroscientists. Society for Neuroscience: DC Metro Area Chapter Keynote Address, 2017.
  14. J. T. Vogelstein. Using Big Data Science to Understand What Goes on in Our Heads. SOHOP Faculty Spotlight, 2017.
  15. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience. 2017.
  16. J. T. Vogelstein. NeuroData. 2017.
  17. J. T. Vogelstein. The International Brain Station (TIBS). 2017.
  18. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience. 2017.
  19. J. T. Vogelstein. Connectome Coding. 2017.
  20. J. T. Vogelstein. NeuroStorm. 2017.
  21. J. T. Vogelstein. NeuroData: Enabling Terascale Neuroscience for Everyone. Keystone Symposia: State of the Brain, 2016.
  22. J. T. Vogelstein. Using Big Data Science to Understand What Goes on in Our Heads. SOHOP Faculty Spotlight, 2016.
  23. J. T. Vogelstein. Global Brain Workshop 2016. Global Brain Workshop NSF+JHU at Kavli, 2016.
  24. J. T. Vogelstein. The International Brain Station (TIBS). 2016.
  25. J. T. Vogelstein. NeuroData:Enabling Terascale Neuroscience. JHU Kavli Neuroscience Discovery Institute, 2016.
  26. J. T. Vogelstein. The International Brain Station (TIBS). 2016.
  27. J. T. Vogelstein. NeuroData 2016. 2016.
  28. J. T. Vogelstein. Global Brain Workshop 2106. Kavli Neuroscience Discovery Institute & Center for Imaging Science, 2016.
  29. J. T. Vogelstein. NeuroData:Enabling Terascale Neuroscience. Kavli Neuroscience Discovery Institute & Center for Imaging Science, 2016.
  30. J. T. Vogelstein. Learning a Data-Driven Nosology:Progress, Challenges & Opportunities. Kavli Neuroscience Discovery Institute & Center for Imaging Science, 2016.
  31. J. T. Vogelstein, M. I. Miller and R. Hunganir. Global Brain Workshop 2016. Kavli Institute for Neuroscience Discovery Center for Imaging Science @ JHU, 2016.
  32. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience. DoE, 2015.
  33. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data. SIMPLEX Kickoff, 2015.
  34. J. T. Vogelstein. Law of Large Graphs. DARPA Graphs, 2015.
  35. J. T. Vogelstein. Open Connectome Project: Lowering the Barrier to Entry of Big Data Neuroscience. Institute for Computational Medicine at Johns Hopkins University, 2015.
  36. J. T. Vogelstein. Special Symposium: Neuroscience in the 21st Century. Kavli, 2015.
  37. J. T. Vogelstein. Research Computing Support for Neuroscience and Other Life Sciences. CASC, 2015.
  38. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data: Part 1. DARPA SIMPLEX PI Meeting, 2015.
  39. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data: Part 2. DARPA SIMPLEX PI Meeting, 2015.
  40. J. T. Vogelstein. Open-Science Platform for Heterogeneous Brain Data: Opportunities and Challenges. Kavli, 2014.
  41. J. T. Vogelstein. Big (Neuro) Statistics. Kavli Salon, 2014.
  42. J. T. Vogelstein. Big Statistics for Brain Sciences. Baylor College of Medicine, Department of Neuroscience, 2014.
  43. J. T. Vogelstein. Top Challenges of Big Data Neuroscience. BRAIN Initiative Workshop, 2014.
  44. J. T. Vogelstein. Statistical Models and Inference for big Brain-Graphs. NIPS Workshop on Acquiring and analyzing the activity of large neural ensembles, 2013.
  45. J. T. Vogelstein. Statistical Inference on Graphs. University of Michigan, 2013.
  46. J. T. Vogelstein. Statistical Inference on Graphs. Scientific Computing Institute, University of Utah, 2013.
  47. J. T. Vogelstein. Open Problems in Neuropsychiatry. Data Seminar, Duke University, 2013.
  48. J. T. Vogelstein. Beyond Little Neuroscience. Beyond Optogenetics workshop at Cosyne, 2013.
  49. J. T. Vogelstein. Decision Theoretic Approach to Statistical Inference. guest Lecture in Current Topics in Machine Learning, Johns Hopkins University, 2012.
  50. J. T. Vogelstein. BIG NEURO. Theory and Neurobiology, Duke University, 2012.
  51. J. T. Vogelstein. Open Connectome Project. Academic Medical Center, Amsterdam, 2012.
  52. J. T. Vogelstein. Consistent Graph Classification. Guest Lecture in Deisseroth Lab, Stanford University, 2011.
  53. J. T. Vogelstein. Statistical Connectomics. Harvard University Connectomics Labs, 2011.
  54. J. T. Vogelstein. What can Translational neuroimaging Research do for Clinical Practice. Child Mind Institute, 2011.
  55. J. T. Vogelstein. Connectome Classification: Statistical Graph Theoretic Methods for Analysis of MR-Connectome Data. Organization for Human Brain Mapping, 2011.
  56. J. T. Vogelstein. Consistent Connectome Classification. Math/Bio Seminar, Duke University, 2011.
  57. 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.
  58. J. T. Vogelstein. Once we get connectomes, what the \%\#* are we going to do with them? Institute of Neuroinformatics, 2011.
  59. J. T. Vogelstein. Are mental properties supervenient on brain properties. 2011.
  60. J. T. Vogelstein. Towards Inference and Analaysis of Neural Circuits Inferred from Population Calcium Imaging. Guest Lecture in Schnitzer Lab, 2009.
  61. J. T. Vogelstein. Sequential Monte Carlo in Neuroscience. SAMSI Program on Sequential Monte Carlo, Tracking Working Group, 2009.
  62. J. T. Vogelstein. OOPSI: A Family of Optimal OPtical Spike Inference Algorithms for Inferring Neural Connectivity from Population Calcium Imaging. Dissertation Defense, 2009.
  63. J. T. Vogelstein. Towards Inferring Neural Circuits from Calcium Imaging. Guest Lecture in Yuste Lab, 2009.
  64. J. T. Vogelstein. Neurocognitive Graph Theory. national Security Agency, 2009.
  65. J. T. Vogelstein. Inferring spike trains from Calcium Imaging. Redwood Center for Theoretical Neuroscience, University of California, Berkeley, 2008.
  66. J. T. Vogelstein. Inferring spike times given typical time-series fluorescence observations. Department of Applied Mathematics and Statistics, Johns Hopkins University, 2008.
  67. J. T. Vogelstein. Inferring spike trains from Calcium Imaging. Cambridge University, Gatsby Unit, and University College London, 2008.
  68. J. T. Vogelstein. Inferring Spike Trains Given Calcium-Sensitive Fluorescence Observations. Statistical Analysis of Neural Data, 2008.
  69. 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.