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YearTalkWhere
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2001ESUP accept/reject samplingNC State Statistics
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2001Monte Carlo exact conditional hypothesis tests for loglinear modelsAT&T Labs, Florham Park, New Jersey
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2001Monte Carlo exact conditional hypothesis tests for loglinear modelsFifth Workshop on Groebner Bases and Statistics (GROSTAT V), Tulane University, New Orleans, Louisiana
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2001Monte Carlo exact conditional hypothesis tests for loglinear modelsJohns Hopkins University Department of Biostatistics, Baltimore, Maryland
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2001Monte Carlo exact conditional hypothesis tests for loglinear models University of Michigan Department of Statistics, Ann Arbor, Michigan
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2001Monte Carlo exact conditional hypothesis tests for loglinear modelsOhio State University Department of Statistics, Columbus, Ohio
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2002Model selection and fitting for empirical Bayes analysis of microarray dataJSM New York
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2002Ascent-based MCEMYale University Division of Biostatistics, New Haven, Connecticut
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2002ESUP accept/reject samplingJohns Hopkins University Department of Biostatistics, Baltimore Maryland
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2003A tour of biostatisticsDrexel University Department of Mathematics, Philadelphia, Pennsylvania
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2003ESUP accept/reject samplingDuke University Institute of Statistics and Decision Sciences, Durham, North Carolina
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2003Missing data and air pollutionDrexel University Department of Mathematics, Philadelphia, Pennsylvania
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2003Monte Carlo exact conditional hypothesis tests for loglinear modelsJoint Statistical Meetings, San Francisco, California
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2003Monte Carlo exact conditional hypothesis tests for loglinear modelsStatistics and Applied Mathematical Sciences Institute, Workshop on Exact Categorical Methods, Research Triangle Park, North Carolina
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2004Multilevel models with applications in genomicsUniversity of Minnesota Department of Statistics, Minneapolis
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2004Ascent-based MCEMCornell University Department of Statistics, Ithaca, New York
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2005Ascent-based MCEMJohns Hopkins University Department of Applied Math and Statistics, Baltimore, Maryland
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2005ESUP accept/reject samplingPennsylvania State Department of statistics, University, College Station, Pennsylvania
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2005Discussion of: characterizing experimentally induced neuronal processing by DuBois BowmanDepartment of Biostatistics Grand Rounds, Johns Hopkins University, Department of Biostatistics
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2005Quantitative characterization of chloroquine and aspirin in the male genital tractwith Craig Hendrix, Johns Hopkins Division of Clinical Pharmacology, Baltimore, Maryland
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2006Ascent-based MCEMDepartment of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania
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2006Is MRI based structure a mediator for lead’s effect on cognitive function MICE meeting, Welch Center for Prevention, Epidemiology and Clinical Research, Baltimore, Maryland
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2007A Bayesian hierarchical framework for spatial modeling of fMRI dataCenter for Statistics in the Social Sciences, University of Washington, Seattle, Washington
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2007 A case study in pharmacologic imaging using single photon emission computed tomography UMBC Prob/Stat Day, Baltimore, Maryland.
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2007Age, lead exposure and neuronal volume ENAR, Atlanta, Georgia
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2007Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics}Department of Statistics University of Minnesota, Minneapolis, Minnesota
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2007Statistical methods in functional medical imagingDepartment of Biostatistics, University of Florida, Gainesville, Florida
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2008A Bayesian hierarchical framework for spatial modeling of fMRI dataHuman Brain Mapping, Melbourne, Australia
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2008Conditional and marginal models for binary outcomesDepartment of Statistics University of Minnesota, Minneapolis, Minnesota
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2008Lead exposure, neuronal volume and cognitive function Department of Biostatistics University of Florida, Gainesville, Florida
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2008Non-linear curve fitting in the analysis of medical imaging data
Department of Biostatistics Grand Rounds, Johns Hopkins University, Baltimore, Maryland.
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2008Pharmacologic imaging using principal curves in single photon emission computed tomographyENAR, Arlington, Virginia.
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2008Quantifying the hypnogram and sleep stage transitions: novel approaches and applications to sleep disorders
Annual Meeting of the Associated Professional Sleep Societies, Baltimore, Maryland
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2008Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics
Department of Biostatistics, Columbia University, New York, New York
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2008Statistical methods for indirect estimation of physiological parameters: case studies in viral kineticsDepartment of Biostatistics, Emory University, Atlanta, Georgia
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2008Statistical methods for indirect estimation of physiological parameters: case studies in viral kinetics
Department of Biostatistics, Vanderbilt University, Nashville, Tennessee
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2009Non-linear curve fitting in the analysis of medical imaging data
Center for Imaging Science, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
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2009Non-linear curve fitting in the analysis of medical imaging data
University of Pittsburgh, Department of Biostatistics, Pittsburgh, Pennsylvania
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2009On the analysis of multiple sleep hypnogramsInternational Statistical Institute, Durban, South Africa
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2009Statistical methods for studying connectivity in the human brainInternational Workshop on Statistical Modeling, Ithaca, New York
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2010Functional principal components for high dimensional brain volumetricsInternational Workshop on Statistical Modeling, Glasgow, Scotland
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2010Statistical methods for evaluating connectivity in the human brainENAR, New Orleans, Louisiana
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2010Statistical methods for high dimensional imaging studies of populations
Department of Psychiatry and Behavioral Science, Johns Hopkins Bayview Medical Center, Baltimore, Maryland
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2011fMRI functional connectivity in subjects at high familial risk for Alzheimer's disease: new approaches to analysisDementia Consortium, Johns Hopkins, Baltimore, Maryland
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2011Indirect estimation of kinetic parameters in dual isotope single photon emission computed tomography studies of microbicide lubricantsENAR, Miami, Florida
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2011Statistical methods for studying connectivity in the human brainDivision of Biostatistics, University of Maryland, Baltimore, Maryland
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2011Statistical methods for studying connectivity in the human brain
Department of Biostatistics, University of Washington, Seattle, Washington
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2011Statistical methods for studying connectivity in the human brainDepartment of Statistics, Cornell University, Ithaca, New York
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2011Statistical methods for studying connectivity in the human brainDementia Consortium, Johns Hopkins, Baltimore, MD
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2011An overview of EEG research at Hopkins Biostatistics
Regional EEG/ERP Conference, Kennedy Krieger Institute, Baltimore, MD.
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2011Statistical methods for evaluating (human) brain connectivity
Statistical Methods for Very Large Data Sets Conference, Baltimore, MD.
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2011Statistical methods for studying connectivity in the human brain
The Brad Efron Honorary Symposium on Large-Scale Inference, Silver Springs, MD.
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2011Statistical methods for studying connectivity in the human brainISDS, Duke University, Durham, NC.
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2012Predicting neurological disorders using functional and structural brain imaging dataENAR, Washington DC.
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2012Predicting neurological disorders using functional and structural brain imaging dataDepartment of Statistics, University of Virginia, Charlottesville, Va.
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2012Panelist at the 2012 NIH/NIBIB training grantee meetingNational Institutes of Health, Bethesda, MD.
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2012Statistical analysis of functional MRI resting state functional brain connectivity dataSAMSI opening workshop on massive data, Raleigh, NC.
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2012Statistical analysis of functional MRI resting state brain connectivity data
Departments of Statistics and Biostatistics, University of Wisconsin, Madison, Wisconsin
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2012Statistical analysis of functional MRI resting state brain connectivity data
Departments of Biostatistics, Yale University, New Haven, Connecticut.
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2013Homotopic group ICA for resting state fMRITalk given at SAMSI 2013
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2013Large scale decompositions for functional imaging studiesTalk given at ENAR 2013
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2013Measurement in medical imagingLecture given at the ICTR 2013
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2013Graphical models for analyzing resting state networksTalk given at Penn visit
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2012Multimodal brain imaging studies for predictionTalk given at JSM 2012 session 56
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2012A Bayesian Hierarchical Framework for Spatial Modeling of fMRI DataTalk given at the ICSA in 2011
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2012The Center for Quantitative Neuroscience A core for population neuroanalytics and translational systems neuroscienceTalk given at the BSI
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2013graphical models for analyzing resting state networksTalk given at KKI in August 2013
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2013Graphical models for analyzing resting state networksTalk given with KKI and Berkeley
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2013Analyzing neurological disorders using functional and structural brain imaging dataTalk given at NYU
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2013Analyzing neurological disorders using functional and structural brain imaging dataTalk given at Microsoft Research
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2013Analyzing neurological disorders using functional and structural brain imaging dataVirginia Tech 2014
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2014Teaching statistics for the future The MOOC revolution and beyondMOOC talk given at the Division of Biostat
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2014Developmental Disorders and Neuroimaging: Tools, Results and IssuesTalk given at ENAR 2014
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2014Teaching Statistics for the Future: the MOOC Revolution and BeyondTalk given at Brown
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2014Teaching statistics for the future The MOOC revolution and beyondTalk given at the University of Maryland
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2014Teaching statistics for the future The MOOC revolution and beyondDean's lecture giving at Johns Hopkins Bloomberg
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2014Teaching Statistics for the Future: The MOOC Revolution and BeyondTalk given at Rochester
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2014Analyzing Neurological Disorders Using Functional and Structural Brain Imaging DataTalk given at Duke ISBIS / SLDM meeting
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2014Statistical methods for the study of human brain functional connectivityTalk given at JSM 2014
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2014Teaching statistics for the future: The MOOC revolution and beyondTalk given at ISU
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2015Analyzing Neurological Disorders Using Functional and Structural Brain Imaging DataTalk given at Penn
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2015Teaching statistics for the future: The MOOC revolution and beyondTalk given at BME
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2015Discussion of: Statistical Quantitative Magnetic Resonance Imaging by Dr Taki ShinoharaDiscussion of Dr. Shinohara's talk at JHU Biostat
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2016Bar Codes, Fingerprints and Reproducibility in Functional and Structural Brain Imaging DataTalk given at the Maryland Imaging Retreat
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2016Barcodes, Fingerprints and Reproducibility in Functional and Structural Brain Imaging Data
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2017Links for R tutorialMRICloud R tutorial
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2017Talk given at the malone center mix and mingle
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2017Executive data scienceTalk given at the National Academy working group
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2017Radiology research day talkTalk given at the JHU Radiology research dayFile if needed
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2017Am I my connectome? Fingerprinting with repeated functional connectivity dataTalk given in Vigo
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2017Am I my connectome? Fingerprinting with repeated functional connectivity dataTalk given at JSM
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2017Am I my connectome? Fingerprinting with repeated functional connectivity dataTalk given at Michigan State
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2017Dimension reduction for complex biological phenomenaTalk given at the ASA Biopharm section
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2017Am I my connectome? Fingerprinting with repeated functional connectivity dataTalk given at the NIH
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2017SMART group and Data Science Lab
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2018Fingerprinting and reproducibility in resting state fMRITalk given at BME
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2018Student recruitment 2018Student recruitment talk
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2018Is the doctor of the future goig to be a human, robot or cyborg?Talk given at the Mayo Clinic
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2018Specialized AI in personalized medicineDepartmental retreat presentation