Talks

Local
  1. J. T. Vogelstein. Surprise! IID++ Out of Distribution & Prospective Learning. Simons Foundation, New York, NY, 2023.
  2. B. D. Pedigo. Hypothesis testing for connectome comparisons: a statistical analysis of bilateral symmetry in an insect brain connectome. Drexel University, Philadelphia, PA, 2022.
  3. Ali Geisa. Towards a theory of out-of-distribution learning. JHU BME, Baltimore, MD, USA, 2021.
  4. E. Bridgeford. Eliminating Accidental Deviations in Human Connectomics. JHU BME, Baltimore, MD, USA, 2021.
  5. J. Chung. Heritablity of Human Structural Connectomes. JHU BME, Baltimore, MD, USA, 2021.
  6. J. Dey. Omnidirectional Lifelong Learning via Ensembling Representations. JHU BME, Baltimore, MD, USA, 2021.
  7. J. T. Vogelstein. FIRM Guiding Principles for scientific software development and stewardship. JHU BME, Baltimore, MD, USA, 2021.
  8. J. T. Vogelstein. Jovo++. JHU BME, Baltimore, MD, USA, 2021.
  9. J. T. Vogelstein. Reality Transurfing: Chapter 1. JHU BME, Baltimore, MD, USA, 2021.
  10. J. T. Vogelstein. Lifelong Learning: Theory and Practice. Darpa L2M PI Meeting, 2021.
  11. J. T. Vogelstein. Lifelong Learning and Beyond. Darpa L2M PI Meeting, 2021.
  12. J. T. Vogelstein. Lifelong Learning: Theory and Context. Darpa L2M PI Meeting, 2021.
  13. J. T. Vogelstein. Lifelong Learning: Theory and Practice and Coresets. Darpa L2M PI Meeting, 2021.
  14. J. T. Vogelstein. Lifelong Learning. North Carolina State University, Raleigh, NC, USA, 2020.
  15. J. T. Vogelstein. Lifelong Learning. Morgan State University, Baltimore, MD, USA, 2020.
  16. J. T. Vogelstein. Lifelong Learning: Moving Beyond Avoiding Catastrophic Forgetting. Johns Hopkins Mathematical Institute for Data Science, Baltimore, MD, USA, 2020.
  17. J. T. Vogelstein. Open Access to the Brain: a Computer "Connectome" Links Brain Images in Fine Detail. JHM Boot Camp, Baltimore, MD, USA, 2019.
  18. J. T. Vogelstein. Big Biomedical Data Science. Sol Goldman International Conference, Baltimore, MD, USA, 2019.
  19. J. T. Vogelstein. Journey to Here. JHU BMES talks, Baltimore, MD, USA, 2019.
  20. J. T. Vogelstein. NeuroData (Science). Kavli, Baltimore, MD, USA, 2019.
  21. J. T. Vogelstein. NeuroData Tools. NeuroData Hackashop, Baltimore, MD, USA, 2019.
  22. J. T. Vogelstein. Biomedical Big Data and Data Science. JHU BME, Baltimore, MD, USA, 2019.
  23. J. T. Vogelstein. Data Intensive Brain Science. Kavli Neuroscience Discovery Institute, Baltimore, MD, USA, 2018.
  24. J. T. Vogelstein. Using Big Data Science to Understand What Goes On in our Heads. SOHOP Faculty Spotlight, Baltimore, MD, USA, 2018.
  25. J. T. Vogelstein. Engineering the Future of Medicine: Data Intensive Biomedical Science. Johns Hopkins University Biomedical Engineering, Baltimore, MD, USA, 2018.
  26. J. T. Vogelstein. Data Coordination and Data Resources for the BRAIN Initiative. 4th Annual BRAIN Initiative Investigators Meeting, Rockville, MD, USA, 2018.
  27. J. T. Vogelstein. The International Brain Station (TIBS). JHU BME and Tsinghua University, Baltimore, MD, USA, 2017.
  28. J. T. Vogelstein. Using Big Data Science to Understand What Goes on in Our Heads. SOHOP Faculty Spotlight, Baltimore, MD, USA, 2017.
  29. J. T. Vogelstein. Challenges and Opportunities in Big Data for Neuroscientists. Society for Neuroscience: DC Metro Area Chapter Keynote Address, Washington, DC, USA, 2017.
  30. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience. Society for Neuroscience, Washington D.C., USA, 2017.
  31. J. T. Vogelstein. NeuroStorm. Global Brain Workshop 2 JHU, Baltimore, MD, USA, 2017.
  32. J. T. Vogelstein. The International Brain Station (TIBS). United Nations Global Brain Workshop Meeting, Baltimore, MD, USA, 2016.
  33. J. T. Vogelstein. Using Big Data Science to Understand What Goes on in Our Heads. SOHOP Faculty Spotlight, Baltimore, MD, USA, 2016.
  34. J. T. Vogelstein. The International Brain Station (TIBS). Kavli Foundation, Baltimore, MD, USA, 2016.
  35. J. T. Vogelstein. NeuroData 2016. NeuroData Lab Retreat, 2016.
  36. J. T. Vogelstein. Global Brain Workshop 2016. Global Brain Workshop NSF+JHU at Kavli, Baltimore, MD, USA, 2016.
  37. J. T. Vogelstein. Global Brain Workshop 2016. Kavli Neuroscience Discovery Institute & Center for Imaging Science, Baltimore, MD, USA, 2016.
  38. J. T. Vogelstein. Learning a Data-Driven Nosology:Progress, Challenges & Opportunities. Kavli Neuroscience Discovery Institute & Center for Imaging Science, Baltimore, MD, USA, 2016.
  39. J. T. Vogelstein. NeuroData:Enabling Terascale Neuroscience. Kavli Neuroscience Discovery Institute & Center for Imaging Science, Baltimore, MD, USA, 2016.
  40. J. T. Vogelstein. NeuroData:Enabling Terascale Neuroscience. JHU Kavli Neuroscience Discovery Institute, Baltimore, MD, USA, 2016.
  41. J. T. Vogelstein, M. I. Miller, and R. Hunganir. Global Brain Workshop 2016. Kavli Neuroscience Discovery Institute & Center for Imaging Science @ JHU, Baltimore, MD, USA, 2016.
  42. J. T. Vogelstein. Special Symposium: Neuroscience in the 21st Century. Kavli, Baltimore, MD, USA, 2015.
  43. J. T. Vogelstein. Open Connectome Project: Lowering the Barrier to Entry of Big Data Neuroscience. Institute for Computational Medicine at Johns Hopkins University, Baltimore, MD, USA, 2015.
  44. J. T. Vogelstein. Open Source Platform for Heterogenous Brain Data. figshare, 2015.
  45. J. T. Vogelstein. Big (Neuro) Statistics. Kavli Salon, Chicago, IL, USA, 2014.
  46. J. T. Vogelstein. Open-Science Platform for Heterogeneous Brain Data: Opportunities and Challenges. Kavli, Baltimore, MD, USA, 2014.
  47. J. T. Vogelstein. Big (Neuro) Statistics. Kavli Salon, Baltimore, MD, USA, 2014.
  48. J. T. Vogelstein. Decision Theoretic Approach to Statistical Inference. Guest Lecture in Current Topics in Machine Learning, Johns Hopkins University, Baltimore, MD, USA, 2012.
  49. J. T. Vogelstein. Once we get connectomes, what the \%\#* are we going to do with them? Institute of Neuroinformatics, Boston, MA, USA, 2011.
  50. J. T. Vogelstein. Inferring spike times given typical time-series fluorescence observations. Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA, 2008.
International
  1. Qingyang Wang. Why do networks need negative weights? None 2022.
  2. E. Bridgeford. Simulating a Realization of a Stochastic Block Model. ABCD-ReproNim Program, 2022.
  3. E. Bridgeford. Community Detection and Model Selection in SBMs. ABCD-ReproNim Program, 2022.
  4. S. Panda, C. Shen, and J. T. Vogelstein. Nonparametric MANOVA via Independence Testing. Global Young Scientists Summit, 2022.
  5. B. D. Pedigo, M. Winding, M. Zlatic, A. Cardona, C. E. Priebe, and J. T. Vogelstein. Maggot brain, mirror image? A statistical analysis of bilateral symmetry in an insect brain connectome. Neuromatch 4.0, 2021.
  6. B. D. Pedigo and J. T. Vogelstein. graspologic: A python package for rigorous statistical analysis of populations of attributed connectomes. BRAIN Informatics Webinar, 2021.
  7. S. Panda, C. Shen, and J. T. Vogelstein. Nonparametric MANOVA via Independence Testing. BRAIN Initiative Meeting, 2021.
  8. B. D. Pedigo. Network data science for bilateral brains: Applications in the larval Drosophila connectome. NIH & DOE Brain Connectivity Workshop Series, 2021.
  9. J. T. Vogelstein. OOD DARPA Presentation. DARPA, 2021.
  10. J. T. Vogelstein. Lifelong Learning and Beyond. DARPA L2M, 2021.
  11. J. Vogelstein. The role of the connectome in achieving artificial general intelligence. Yale School of Medicine, Whistler Scientific Workshop, Whistler, BC, Canada, 2020.
  12. J. Vogelstein. Lifelong Learning via Ensembling General Representations. None 2020.
  13. H. Helm, R. Mehta, C. E. Priebe, R. Arora, and J. T. Vogelstein. A Theory and Practice of Lifelong Learnable Forest. Kavli Neural Systems Institute, Rockefeller University, New York City, NY, USA, 2020.
  14. J. T. Vogelstein. Lifelong Learning. Columbia University, New York City, NY, USA, 2020.
  15. J. T. Vogelstein. Ailey in an Hour: (A "Soup-to-Nuts" Pipeline for Analysis of Whole Cleared Brain Data). NeuroNex, Cornell University, Ithaca, NY, USA, 2019.
  16. J. T. Vogelstein, H. Helm, R. Mehta, C. E. Priebe, and R. Arora. A Theory and Practice of the Lifelong Learnable. L2M, 2019.
  17. J. T. Vogelstein and R. Burns. Data Science Core. Harvard University, Carmridge, MA, USA, 2019.
  18. J. Chung. Statistical Methods for Population of Connectomes. Organization of Human Brain Mapping, Rome, Italy, 2019.
  19. J. Browne. Forest Packing: Fast Parallel, Decision Forests. SIAM International Conference on Data Mining, Calgary, Alberta, Canada, 2019.
  20. D. Tward. Brain mapping tools for neuroscience research. NeuroNex, Cornell University, Ithaca, NY, USA, 2019.
  21. J. T. Vogelstein. Big Data and the Life Sciences. Sloan Foundation, New York City, NY, USA, 2019.
  22. J. T. Vogelstein. Statistical Foundations For Connectomics. Max Planck / HHMI Connectomics Meeting, Berlin, Germany, 2019.
  23. J. T. Vogelstein. Connectal Coding. Dipy Workshop, Bloomington, Indiana, USA, 2019.
  24. J. T. Vogelstein. Lifelong Learning Forests. L2M, 2019.
  25. J. T. Vogelstein. Connectome Coding. Society for Neuroscience, San Diego, CA, USA, 2018.
  26. J. T. Vogelstein. NeuroData: A Community-developed open-source computational ecosystem for big neuro data. NeuroNex, Cornell University, Ithaca, NY, USA, 2018.
  27. J. T. Vogelstein. A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data. Princeton University, Princeton, NJ, USA, 2018.
  28. J. T. Vogelstein. Multiscale Graph Correlation: A Knowledge Representation System for Discovering Latent Geometric Structure. DARPA SIMPLEX PI Review Meeting, New York City, NY, USA, 2018.
  29. E. W. Bridgeford. A High-Throughput Pipeline Identifies Robust Connectomes but Troublesome Variability. Organization of Human Brain Mapping, Suntec, Singapore, 2018.
  30. E. Perlman. NeuroData: Embracing Open Source for Big Data Neuroscience. NSF NeuroNex Workshop on Super 3DEM, Austin, TX, USA, 2018.
  31. J. T. Vogelstein and V. Chandrashekhar. NeuroNex + Stanford. NeuroNex-Stanford, Stanford, CA, USA, 2018.
  32. G. Kiar. Connectome Coding: what is it, how do we do it, and why do we care? Data science in Neuroscience Symposium, Suntec, Singapore, 2018.
  33. J. T. Vogelstein. Lifelong Learning Forests. Darpa L2M PI Meeting, Arlington, VA, USA, 2018.
  34. J. T. Vogelstein. Discovering Relationships and their Geometry Across Disparate Data Modalities. Yale University, New Haven, CT, USA, 2018.
  35. J. T. Vogelstein. Connectome Coding. Schmidt Sciences, 2017.
  36. J. T. Vogelstein. Discovering Relationships and their Geometry Across Disparate Data Modalities. Stanford University, Stanford, CA, US, 2017.
  37. D. Mhembere. knor: a NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means library. HPDC, Washington DC, USA, 2017.
  38. G. Kiar. Science in the Cloud (SIC): A use-case in MRI Connectomics. Open Science Special Interest Group, Oxford University, Oxford, England, 2017.
  39. Y. Lee. Network Dependence Testing via Diffusion Maps and Distance-Based Correlations. Joint Statistical Meetings, Baltimore, MD, USA, 2017.
  40. T. M. Tomita. ROFLMAO: Robust Oblique Forests with Linear Matrix Operations. SIAM International Conference on Data Mining, Houston, TX, USA, 2017.
  41. J. T. Vogelstein. NeuroData: Enabling Terascale Neuroscience for Everyone. 3rd Annual BRAIN Iniative Investigators Meeting, Bethesda, MD, USA, 2016.
  42. C. Shen. Multiscale Generalized Correlation. Joint Statistical Meeting, Chicago, IL, USA, 2016.
  43. J. T. Vogelstein. NeuroData: Enabling Terascale Neuroscience for Everyone. Keystone Symposia: State of the Brain, Alpbach, Austria, 2016.
  44. C. Shen. Local Distance Correlation for Testing Independence. Temple University, Philadelphia, PA, USA, 2015.
  45. J. T. Vogelstein. Law of Large Graphs. DARPA Graphs, Columbia University, New York City, NY, USA, 2015.
  46. J. T. Vogelstein. Research Computing Support for Neuroscience and Other Life Sciences. CASC, Aachen, Germany, 2015.
  47. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data. SIMPLEX Kickoff, New York City, NY, USA, 2015.
  48. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data: Part 1. DARPA SIMPLEX PI Meeting, New York City, NY, USA, 2015.
  49. J. T. Vogelstein. From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from Heterogeneous Data: Part 2. DARPA SIMPLEX PI Meeting, New York City, NY, USA, 2015.
  50. J. T. Vogelstein. Opportunities and Challenges in Big Data Neuroscience. DoE, 2015.
  51. J. T. Vogelstein and L. Paninski. Spike inference from calcium imaging using sequential Monte Carlo methods. AMSI Program on Sequential Monte Carlo, 2015.
  52. J. T. Vogelstein. big time (series data in neuroscience). figshare, 2015.
  53. J. T. Vogelstein. Top Challenges of Big Data Neuroscience. BRAIN Initiative Workshop, Bethesda, MD, USA, 2014.
  54. J. T. Vogelstein. Big Statistics for Brain Sciences. Baylor College of Medicine, Department of Neuroscience, Houston, TX, USA, 2014.
  55. J. T. Vogelstein. Beyond Little Neuroscience. Beyond Optogenetics workshop at Cosyne, Salt Lake City, UT, USA, 2013.
  56. J. T. Vogelstein. Statistical Inference on Graphs. University of Michigan, Ann Arbor, Michigan, 2013.
  57. J. T. Vogelstein. Statistical Inference on Graphs. Scientific Computing Institute, University of Utah, Salt Lake City, UT, USA, 2013.
  58. J. T. Vogelstein. Open Problems in Neuropsychiatry. Data Seminar, Duke University, Durham, NC, USA, 2013.
  59. J. T. Vogelstein. Statistical Models and Inference for big Brain-Graphs. NIPS Workshop on Acquiring and analyzing the activity of large neural ensembles, Lake Tahoe, NV, USA, 2013.
  60. J. T. Vogelstein. BIG NEURO. Theory and Neurobiology, Duke University, Durham, NC, USA, 2012.
  61. J. T. Vogelstein. Open Connectome Project. Academic Medical Center, Amsterdam, Netherlands, 2012.
  62. J. T. Vogelstein. Are mental properties supervenient on brain properties. None 2011.
  63. J. T. Vogelstein. What can Translational neuroimaging Research do for Clinical Practice. Child Mind Institute, New York City, NY, USA, 2011.
  64. J. T. Vogelstein. Statistical Connectomics. Harvard University Connectomics Labs, Cambridge, MA, USA, 2011.
  65. 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, Fairfax, VA, USA, 2011.
  66. J. T. Vogelstein. Consistent Connectome Classification. Math/Bio Seminar, Duke University, Durham, NC, USA, 2011.
  67. J. T. Vogelstein. Connectome Classification: Statistical Graph Theoretic Methods for Analysis of MR-Connectome Data. Organization for Human Brain Mapping, Quebec City, Canada, 2011.
  68. J. T. Vogelstein. Consistent Graph Classification. Guest Lecture in Deisseroth Lab, Stanford University, Stanford, CA, USA, 2011.
  69. J. T. Vogelstein. Neurocognitive Graph Theory. National Security Agency, 2009.
  70. J. T. Vogelstein. OOPSI: A Family of Optimal OPtical Spike Inference Algorithms for Inferring Neural Connectivity from Population Calcium Imaging. Dissertation Defense, Johns Hopkins University, Baltimore, MD, USA, 2009.
  71. J. T. Vogelstein. Sequential Monte Carlo in Neuroscience. SAMSI Program on Sequential Monte Carlo, Tracking Working Group, 2009.
  72. J. T. Vogelstein. Towards Inference and Analaysis of Neural Circuits Inferred from Population Calcium Imaging. Guest Lecture in Schnitzer Lab, Stanford University, Stanford, CA, USA, 2009.
  73. J. T. Vogelstein. Towards Inferring Neural Circuits from Calcium Imaging. Guest Lecture in Yuste Lab, Columbia University, New York City, NY, USA, 2009.
  74. J. T. Vogelstein. Inferring Spike Trains Given Calcium-Sensitive Fluorescence Observations. Statistical Analysis of Neural Data, Pittsburgh, PA, USA, 2008.
  75. J. T. Vogelstein. Inferring spike trains from Calcium Imaging. Redwood Center for Theoretical Neuroscience, University of California, Berkeley, CA, USA, 2008.
  76. J. T. Vogelstein. Inferring spike trains from Calcium Imaging. Cambridge University, Gatsby Unit, and University College London, Cambridge, England, 2008.
  77. 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, New York City, NY, USA, 2007.