A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | |
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1 | Year | Talk | Where | State | Country | |||||||||||||||||||||

2 | 2001 | ESUP accept/reject sampling | NC State Statistics | NC | USA | |||||||||||||||||||||

3 | 2001 | Monte Carlo exact conditional hypothesis tests for loglinear models | AT&T Labs, Florham Park, New Jersey | NJ | USA | |||||||||||||||||||||

4 | 2001 | Monte Carlo exact conditional hypothesis tests for loglinear models | Fifth Workshop on Groebner Bases and Statistics (GROSTAT V), Tulane University, New Orleans, Louisiana | LA | USA | |||||||||||||||||||||

5 | 2001 | Monte Carlo exact conditional hypothesis tests for loglinear models | Johns Hopkins University Department of Biostatistics, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

6 | 2001 | Monte Carlo exact conditional hypothesis tests for loglinear models | University of Michigan Department of Statistics, Ann Arbor, Michigan | MI | USA | |||||||||||||||||||||

7 | 2001 | Monte Carlo exact conditional hypothesis tests for loglinear models | Ohio State University Department of Statistics, Columbus, Ohio | OH | USA | |||||||||||||||||||||

8 | 2002 | Model selection and fitting for empirical Bayes analysis of microarray data | JSM New York | NY | USA | |||||||||||||||||||||

9 | 2002 | Ascent-based MCEM | Yale University Division of Biostatistics, New Haven, Connecticut | CT | USA | |||||||||||||||||||||

10 | 2002 | ESUP accept/reject sampling | Johns Hopkins University Department of Biostatistics, Baltimore Maryland | MD | USA | |||||||||||||||||||||

11 | 2003 | A tour of biostatistics | Drexel University Department of Mathematics, Philadelphia, Pennsylvania | PA | USA | |||||||||||||||||||||

12 | 2003 | ESUP accept/reject sampling | Duke University Institute of Statistics and Decision Sciences, Durham, North Carolina | NC | USA | |||||||||||||||||||||

13 | 2003 | Missing data and air pollution | Drexel University Department of Mathematics, Philadelphia, Pennsylvania | PA | USA | |||||||||||||||||||||

14 | 2003 | Monte Carlo exact conditional hypothesis tests for loglinear models | Joint Statistical Meetings, San Francisco, California | CA | USA | |||||||||||||||||||||

15 | 2003 | Monte Carlo exact conditional hypothesis tests for loglinear models | Statistics and Applied Mathematical Sciences Institute, Workshop on Exact Categorical Methods, Research Triangle Park, North Carolina | NC | USA | |||||||||||||||||||||

16 | 2004 | Multilevel models with applications in genomics | University of Minnesota Department of Statistics, Minneapolis | MN | USA | |||||||||||||||||||||

17 | 2004 | Ascent-based MCEM | Cornell University Department of Statistics, Ithaca, New York | NY | USA | |||||||||||||||||||||

18 | 2005 | Ascent-based MCEM | Johns Hopkins University Department of Applied Math and Statistics, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

19 | 2005 | ESUP accept/reject sampling | Pennsylvania State Department of statistics, University, College Station, Pennsylvania | PA | USA | |||||||||||||||||||||

20 | 2005 | Discussion of: characterizing experimentally induced neuronal processing by DuBois Bowman | Department of Biostatistics Grand Rounds, Johns Hopkins University, Department of Biostatistics | MD | USA | |||||||||||||||||||||

21 | 2005 | Quantitative characterization of chloroquine and aspirin in the male genital tract | with Craig Hendrix, Johns Hopkins Division of Clinical Pharmacology, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

22 | 2006 | Ascent-based MCEM | Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania | PA | USA | |||||||||||||||||||||

23 | 2006 | Is MRI based structure a mediator for lead’s effect on cognitive function | MICE meeting, Welch Center for Prevention, Epidemiology and Clinical Research, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

24 | 2007 | A Bayesian hierarchical framework for spatial modeling of fMRI data | Center for Statistics in the Social Sciences, University of Washington, Seattle, Washington | WA | USA | |||||||||||||||||||||

25 | 2007 | A case study in pharmacologic imaging using single photon emission computed tomography | UMBC Prob/Stat Day, Baltimore, Maryland. | MD | USA | |||||||||||||||||||||

26 | 2007 | Age, lead exposure and neuronal volume | ENAR, Atlanta, Georgia | GA | USA | |||||||||||||||||||||

27 | 2007 | Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics} | Department of Statistics University of Minnesota, Minneapolis, Minnesota | MN | USA | |||||||||||||||||||||

28 | 2007 | Statistical methods in functional medical imaging | Department of Biostatistics, University of Florida, Gainesville, Florida | FL | USA | |||||||||||||||||||||

29 | 2008 | A Bayesian hierarchical framework for spatial modeling of fMRI data | Human Brain Mapping, Melbourne, Australia | ASTL | ||||||||||||||||||||||

30 | 2008 | Conditional and marginal models for binary outcomes | Department of Statistics University of Minnesota, Minneapolis, Minnesota | MN | USA | |||||||||||||||||||||

31 | 2008 | Lead exposure, neuronal volume and cognitive function | Department of Biostatistics University of Florida, Gainesville, Florida | FL | USA | |||||||||||||||||||||

32 | 2008 | Non-linear curve fitting in the analysis of medical imaging data | Department of Biostatistics Grand Rounds, Johns Hopkins University, Baltimore, Maryland. | MD | USA | |||||||||||||||||||||

33 | 2008 | Pharmacologic imaging using principal curves in single photon emission computed tomography | ENAR, Arlington, Virginia. | VA | USA | |||||||||||||||||||||

34 | 2008 | Quantifying the hypnogram and sleep stage transitions: novel approaches and applications to sleep disorders | Annual Meeting of the Associated Professional Sleep Societies, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

35 | 2008 | Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics | Department of Biostatistics, Columbia University, New York, New York | NY | USA | |||||||||||||||||||||

36 | 2008 | Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics | Department of Biostatistics, Emory University, Atlanta, Georgia | GA | USA | |||||||||||||||||||||

37 | 2008 | Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics | Department of Biostatistics, Vanderbilt University, Nashville, Tennessee | TN | USA | |||||||||||||||||||||

38 | 2009 | Non-linear curve fitting in the analysis of medical imaging data | Center for Imaging Science, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

39 | 2009 | Non-linear curve fitting in the analysis of medical imaging data | University of Pittsburgh, Department of Biostatistics, Pittsburgh, Pennsylvania | PA | USA | |||||||||||||||||||||

40 | 2009 | On the analysis of multiple sleep hypnograms | International Statistical Institute, Durban, South Africa | SA | ||||||||||||||||||||||

41 | 2009 | Statistical methods for studying connectivity in the human brain | International Workshop on Statistical Modeling, Ithaca, New York | NY | USA | |||||||||||||||||||||

42 | 2010 | Functional principal components for high dimensional brain volumetrics | International Workshop on Statistical Modeling, Glasgow, Scotland | SCT | ||||||||||||||||||||||

43 | 2010 | Statistical methods for evaluating connectivity in the human brain | ENAR, New Orleans, Louisiana | LA | USA | |||||||||||||||||||||

44 | 2010 | Statistical methods for high dimensional imaging studies of populations | Department of Psychiatry and Behavioral Science, Johns Hopkins Bayview Medical Center, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

45 | 2011 | fMRI functional connectivity in subjects at high familial risk for Alzheimer's disease: new approaches to analysis | Dementia Consortium, Johns Hopkins, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

46 | 2011 | Indirect estimation of kinetic parameters in dual isotope single photon emission computed tomography studies of microbicide lubricants | ENAR, Miami, Florida | FL | USA | |||||||||||||||||||||

47 | 2011 | Statistical methods for studying connectivity in the human brain | Division of Biostatistics, University of Maryland, Baltimore, Maryland | MD | USA | |||||||||||||||||||||

48 | 2011 | Statistical methods for studying connectivity in the human brain | Department of Biostatistics, University of Washington, Seattle, Washington | WA | USA | |||||||||||||||||||||

49 | 2011 | Statistical methods for studying connectivity in the human brain | Department of Statistics, Cornell University, Ithaca, New York | NY | USA | |||||||||||||||||||||

50 | 2011 | Statistical methods for studying connectivity in the human brain | Dementia Consortium, Johns Hopkins, Baltimore, MD | MD | USA | |||||||||||||||||||||

51 | 2011 | An overview of EEG research at Hopkins Biostatistics | Regional EEG/ERP Conference, Kennedy Krieger Institute, Baltimore, MD. | MD | USA | |||||||||||||||||||||

52 | 2011 | Statistical methods for evaluating (human) brain connectivity | Statistical Methods for Very Large Data Sets Conference, Baltimore, MD. | MD | USA | |||||||||||||||||||||

53 | 2011 | Statistical methods for studying connectivity in the human brain | The Brad Efron Honorary Symposium on Large-Scale Inference, Silver Springs, MD. | MD | USA | |||||||||||||||||||||

54 | 2011 | Statistical methods for studying connectivity in the human brain | ISDS, Duke University, Durham, NC. | NC | USA | |||||||||||||||||||||

55 | 2012 | Predicting neurological disorders using functional and structural brain imaging data | ENAR, Washington DC. | DC | USA | |||||||||||||||||||||

56 | 2012 | Predicting neurological disorders using functional and structural brain imaging data | Department of Statistics, University of Virginia, Charlottesville, Va. | VA | USA | |||||||||||||||||||||

57 | 2012 | Panelist at the 2012 NIH/NIBIB training grantee meeting | National Institutes of Health, Bethesda, MD. | MD | USA | |||||||||||||||||||||

58 | 2012 | Statistical analysis of functional MRI resting state functional brain connectivity data | SAMSI opening workshop on massive data, Raleigh, NC. | NC | USA | |||||||||||||||||||||

59 | 2012 | Statistical analysis of functional MRI resting state brain connectivity data | Departments of Statistics and Biostatistics, University of Wisconsin, Madison, Wisconsin | WI | USA | |||||||||||||||||||||

60 | 2012 | Statistical analysis of functional MRI resting state brain connectivity data | Departments of Biostatistics, Yale University, New Haven, Connecticut. | CN | USA | |||||||||||||||||||||

61 | 2013 | Homotopic group ICA for resting state fMRI | Talk given at SAMSI 2013 | NC | USA | |||||||||||||||||||||

62 | 2013 | Large scale decompositions for functional imaging studies | Talk given at ENAR 2013 | |||||||||||||||||||||||

63 | 2013 | Measurement in medical imaging | Lecture given at the ICTR 2013 | |||||||||||||||||||||||

64 | 2013 | Graphical models for analyzing resting state networks | Talk given at Penn visit | |||||||||||||||||||||||

65 | 2012 | Multimodal brain imaging studies for prediction | Talk given at JSM 2012 session 56 | |||||||||||||||||||||||

66 | 2012 | A Bayesian Hierarchical Framework for Spatial Modeling of fMRI Data | Talk given at the ICSA in 2011 | |||||||||||||||||||||||

67 | 2012 | The Center for Quantitative Neuroscience A core for population neuroanalytics and translational systems neuroscience | Talk given at the BSI | |||||||||||||||||||||||

68 | 2013 | graphical models for analyzing resting state networks | Talk given at KKI in August 2013 | |||||||||||||||||||||||

69 | 2013 | Graphical models for analyzing resting state networks | Talk given with KKI and Berkeley | |||||||||||||||||||||||

70 | 2013 | Analyzing neurological disorders using functional and structural brain imaging data | Talk given at NYU | |||||||||||||||||||||||

71 | 2013 | Analyzing neurological disorders using functional and structural brain imaging data | Talk given at Microsoft Research | |||||||||||||||||||||||

72 | 2013 | Analyzing neurological disorders using functional and structural brain imaging data | Virginia Tech 2014 | |||||||||||||||||||||||

73 | 2014 | Teaching statistics for the future The MOOC revolution and beyond | MOOC talk given at the Division of Biostat | |||||||||||||||||||||||

74 | 2014 | Developmental Disorders and Neuroimaging: Tools, Results and Issues | Talk given at ENAR 2014 | |||||||||||||||||||||||

75 | 2014 | Teaching Statistics for the Future: the MOOC Revolution and Beyond | Talk given at Brown | |||||||||||||||||||||||

76 | 2014 | Teaching statistics for the future The MOOC revolution and beyond | Talk given at the University of Maryland | |||||||||||||||||||||||

77 | 2014 | Teaching statistics for the future The MOOC revolution and beyond | Dean's lecture giving at Johns Hopkins Bloomberg | |||||||||||||||||||||||

78 | 2014 | Teaching Statistics for the Future: The MOOC Revolution and Beyond | Talk given at Rochester | |||||||||||||||||||||||

79 | 2014 | Analyzing Neurological Disorders Using Functional and Structural Brain Imaging Data | Talk given at Duke ISBIS / SLDM meeting | |||||||||||||||||||||||

80 | 2014 | Statistical methods for the study of human brain functional connectivity | Talk given at JSM 2014 | |||||||||||||||||||||||

81 | 2014 | Teaching statistics for the future: The MOOC revolution and beyond | Talk given at ISU | |||||||||||||||||||||||

82 | 2015 | Analyzing Neurological Disorders Using Functional and Structural Brain Imaging Data | Talk given at Penn | |||||||||||||||||||||||

83 | 2015 | Teaching statistics for the future: The MOOC revolution and beyond | Talk given at BME | |||||||||||||||||||||||

84 | 2015 | Discussion of: Statistical Quantitative Magnetic Resonance Imaging by Dr Taki Shinohara | Discussion of Dr. Shinohara's talk at JHU Biostat | |||||||||||||||||||||||

85 | 2016 | Bar Codes, Fingerprints and Reproducibility in Functional and Structural Brain Imaging Data | Talk given at the Maryland Imaging Retreat | |||||||||||||||||||||||

86 | 2016 | Barcodes, Fingerprints and Reproducibility in Functional and Structural Brain Imaging Data | ||||||||||||||||||||||||

87 | 2017 | Links for R tutorial | MRICloud R tutorial | |||||||||||||||||||||||

88 | 2017 | Talk given at the malone center mix and mingle | ||||||||||||||||||||||||

89 | 2017 | Executive data science | Talk given at the National Academy working group | |||||||||||||||||||||||

90 | 2017 | Radiology research day talk | Talk given at the JHU Radiology research day | File if needed | ||||||||||||||||||||||

91 | 2017 | Am I my connectome? Fingerprinting with repeated functional connectivity data | Talk given in Vigo | |||||||||||||||||||||||

92 | 2017 | Am I my connectome? Fingerprinting with repeated functional connectivity data | Talk given at JSM | |||||||||||||||||||||||

93 | 2017 | Am I my connectome? Fingerprinting with repeated functional connectivity data | Talk given at Michigan State | |||||||||||||||||||||||

94 | 2017 | Dimension reduction for complex biological phenomena | Talk given at the ASA Biopharm section | |||||||||||||||||||||||

95 | 2017 | Am I my connectome? Fingerprinting with repeated functional connectivity data | Talk given at the NIH | |||||||||||||||||||||||

96 | 2017 | SMART group and Data Science Lab | ||||||||||||||||||||||||

97 | 2018 | Fingerprinting and reproducibility in resting state fMRI | Talk given at BME | |||||||||||||||||||||||

98 | 2018 | Student recruitment 2018 | Student recruitment talk | |||||||||||||||||||||||

99 | 2018 | Is the doctor of the future goig to be a human, robot or cyborg? | Talk given at the Mayo Clinic | |||||||||||||||||||||||

100 | 2018 | Specialized AI in personalized medicine | Departmental retreat presentation |