Name: 2020 Joint Statistical Meetings
Start: 2020-08-02T07:00:00+00:00
End: 2020-08-06

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* = applied session ! = JSM meeting theme

Activity Details

132 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Statistics and Data Science for Vulnerable Populations in the US — Topic Contributed Panel
Royal Statistical Society, Business and Economic Statistics Section, Statistics Without Borders, Government Statistics Section
Organizer(s): Susana E Marquez Renteria, The Rockefeller Foundation
Chair(s): Susana E Marquez Renteria, The Rockefeller Foundation
1:05 PM	Data Science to Assist Vulnerable Population in the United States
Panelists:	Katherine Townsend, data.org Caitlin Augustin, DataKind Aras Jizan, Community Solutions Matthew Lindsay, Mastercard Matthew Wakeman, Benefits Data Trust
2:40 PM	Floor Discussion

137 * !	Tue, 8/4/2020, 10:00 AM - 11:50 AM	Virtual
On Structural Changes — Invited Papers
Business and Economic Statistics Section, Section on Statistical Computing, Royal Statistical Society
Organizer(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
Chair(s): Jan Beran, University of Konstanz
10:05 AM	Change Point Detection of Growth Inflection to Confluence David S. Matteson, Cornell University
10:25 AM	Asymptotic Theory for Time Series with Changing Mean and Variance Liudas Giraitis, Queen Mary University of London; Violetta Dalla, National and Kapodistrian University of Athens; Peter M Robinson, London School of Economics
10:45 AM	Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series Philipp Sibbertsen, Leibniz Universitaet Hannover; Kai Wenger, Leibniz University of Hannover; Simon Wingert, Leibniz University of Hannover
11:05 AM	On the Crossing of a Threshold Under Gaussian Subordination for Spatial Data Sucharita Ghosh, Swiss Federal Research Institute WSL
11:25 AM	Floor Discussion

260 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Statistics and AI in Music — Topic Contributed Papers
Royal Statistical Society, Section on Statistical Learning and Data Science, IMS
Organizer(s): Jan Beran, University of Konstanz
Chair(s): Philipp Sibbertsen, Leibniz Universitaet Hannover
1:05 PM	Understanding Audio from Music Practice Sessions Christopher Raphael, Indiana University
1:25 PM	Visualizing Music Information: Classical Composers Networks and Similarities Presentation Patrick Georges, University of Ottawa
1:45 PM	Statistics and AI in Music Ahmed Elgammal, Artrendex / Rutgers University; Mark Gotham, Universität des Saarlandes / Cornell
2:05 PM	Fusing Audio and Semantic Technologies: Applying AI, Machine Learning and Data Science to Music Production and Consumption Mark Sandler, Queen Mary University of London; Johan Pauwels, Queen Mary University of London; David De Roure, University of Oxford; Kevin Page, University of Oxford
2:25 PM	Discussant: Jan Beran, University of Konstanz
2:45 PM	Floor Discussion

440 * !	Thu, 8/6/2020, 10:00 AM - 11:50 AM	Virtual
Let’s Make Everyone and Everything Count! Benefit-Risk Assessment Challenges, Lessons and Impacts in the Age of Big Data from Clinical Trials to Real-World Evidence — Topic Contributed Papers
Biopharmaceutical Section, ENAR, Royal Statistical Society
Organizer(s): Shahrul Mt-Isa, Merck
Chair(s): Shahrul Mt-Isa, Merck
10:05 AM	Individualized Treatment Choices and Benefit-Risk Prediction in Cardiovascular Clinical Trials John Gregson; Ruth Owen, LSHTM; Stuart Pocock, LSHTM; Shahrul Mt-Isa, Merck; Richard Baumgartner, Merck
10:25 AM	Do Birds of a Feather Flock Together? a Question of Credible Subgroup Identification and Inference on Benefitting Populations in Clinical Trials Duy Ngo, Western Michigan University; Patrick Schnell, The Ohio State University College of Public Health; Richard Baumgartner, Merck; Shahrul Mt-Isa, Merck; Jie Chen, Merck & Co., Inc.; Dai Feng, AbbVie
10:45 AM	Bayesian Bivariate Subgroup Analysis for Risk–benefit Evaluation Nicholas C. Henderson, University of Michigan-Ann Arbor
11:05 AM	Opportunities and Challenges of Real-World Data (RWD) in Benefit-Risk Assessment (BRA) Emilie Scherrer, Merck & Co Inc
11:25 AM	Everyone Counts - Regulating the Evidence from Clinical Trial Data to Real-World Evidence for the Public Good: The Past, Present, and Future Lisa LaVange, UNC-CH
11:45 AM	Floor Discussion

463 *	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
Topics in Biostatistics — Contributed Papers
Section on Medical Devices and Diagnostics, Royal Statistical Society, ENAR
Chair(s): Tyson Rogers, NAMSA
	Does Concomitant Medication Tapering Impact Interim Analysis Projection Grace Liu, Johnson & Johnson; Karen Xia, Johnson & Johnson
	The Landscape of Cancer Communication in India Jaya Satagopan, Rutgers University School of Public Health
	A Scanning-Based Inverse Propensity Weighting for Nonrandom Missing Data with Continuous Instrumental Variables David Todem, Michigan State University; Arkaprabha Ganguli , Department of Statistics and Probability, MSU
	Applications of Design of Experiments to Develop a Robust Assay for Replacing the Rabbit Blood Sugar Bioidentity Test of Insulin Glargine Monisha Dey, Merck & Co., Inc; Junming Yie, Merck & Co., Inc

467	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
Royal Statistical Society CPapers1 — Contributed Papers
Royal Statistical Society
Chair(s): Liberty Vittert, Washington University in St. Louis
	Kriging: Beyond Matérn Pulong Ma, The Statistical and Applied Mathematical Sciences Institute; Anindya Bhadra, Purdue University
	The Correlation Assisted Missing Data Estimator Timothy Cannings, University of Edinburgh; Yingying Fan, USC

538 !	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Emerging Topics in Private Data Analysis — Topic Contributed Papers
IMS, Section on Statistical Learning and Data Science, Royal Statistical Society
Organizer(s): Weijie Su, University of Pennsylvania
Chair(s): Weijie Su, University of Pennsylvania
1:05 PM	Differentially Private Mean and Covariance Estimation Presentation Gautam Kamath, University of Waterloo
1:25 PM	KNG: The K-Norm Gradient Mechanism Jordan Awan, Penn State University; Matthew Reimherr, Penn State University
1:45 PM	Locally Private Learning, Estimation, Inference and Optimality Feng Ruan, University of California at Berkeley
2:05 PM	Gaussian Differential Privacy, with Applications to Deep Learning Jinshuo Dong, University of Pennsylvania; Aaron Roth, University of Pennsylvania; Weijie Su, University of Pennsylvania
2:25 PM	Discussant: Xiao-Li Meng, Harvard University
2:45 PM	Floor Discussion

549 * !	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
E Pluribus Unum: Achieving Your Potential in Statistics Through Different Organizations. — Topic Contributed Panel
Royal Statistical Society, Committee on Membership Retention and Recruitment, ENAR, Council of Emerging and New Statisticians (CENS)
Organizer(s): Will Eagan, Purdue University
Chair(s): Glenn D. White, Jr., ASA Committee on Membership Retention and Recruitment
1:05 PM	E Pluribus Unum: Achieving Your Potential in Statistics Through Different Organizations Presentation
Panelists:	Will Eagan, Purdue University Jeri Mulrow, Westat Renee Helene Moore, Emory University Shelley Han Liu, Icahn School of Medicine at Mount Sinai Abie Ekangaki, Premier Research
2:40 PM	Floor Discussion

583 !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Learning Network Structure in Heterogeneous Populations — Topic Contributed Papers
Section on Statistical Learning and Data Science, Royal Statistical Society, International Indian Statistical Association
Organizer(s): Sandipan Roy, University of Bath
Chair(s): Sandipan Roy, University of Bath
3:05 PM	Modeling Network Time Series Using Generalized Network AutoRegression (GNAR) Kathryn Leeming, University of Warwick; Marina Knight, University of York; Guy Nason, Imperial College London; Matthew Nunes, University of Bath
3:25 PM	Sparse Locally-Stationary Wavelet Processes Alexander Gibberd, Lancaster Unviersity
3:45 PM	Efficient Estimation of Change Points in Regime Switching Dynamic Markov Random Fields Jing Ma, Texas A&M University
4:05 PM	Fast Algorithms for Detection of Structural Breaks in High-Dimensional Data George Michailidis, University of Florida
4:25 PM	Optimistic Binary Segmentation with an Application in Change Point Detection Methodologies for Graphical Models in the Presence of Missing Values Solt Kovács, ETH Zurich; Peter Bühlmann, ETH Zurich; Lorenz Haubner, ETH Zurich; Housen Li, University of Göttingen; Malte Londschien, ETH Zurich; Axel Munk, University of Göttingen
4:45 PM	Floor Discussion

JSM 2020 Online Program

Activity Details

American Statistical Association