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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