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

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52	Mon, 8/3/2020, 10:00 AM - 2:00 PM	Virtual
Statistical Process Control — Contributed Papers
Quality and Productivity Section
Chair(s): David Edwards, Virginia Commonwealth University
	Multivariate Semiparametric Control Charts for Mixed-Type Data Elisavet Sofikitou, University at Buffalo, Department of Biostatistics, USA; Marianthi Markatou, University at Buffalo; Markos Koutras, University of Piraeus, Department of Statistics and Insurance Science, Greece
	Control Charts for Monitoring the Lognormal Mean and Standard Deviation Presentation Wei-Heng Huang, Feng Chia University
	New Design Criterion of Variance Control Charts with Estimated Parameters Martín Guillermo Cornejo Sarmiento, University of Lima; Subhabrata Chakraborti, University of Alabama
	A Generalized Bayesian EWMA Control Chart Presentation Chelsea Mitchell, Virginia Commonwealth University; Abdel-Salam Abdel-Salam, Qatar University; D'Arcy Mays, Virginia Commonwealth University
	A Tensor-Response Mixed Effects Model for Gauge RandR Studies Carlos Llosa, Iowa State University; Ranjan Maitra, Iowa State University
	Corrections for the Effects of Parameter Estimation on the Modified and Acceptance Control Charts Felipe Jardim, Fluminense Federal University (UFF); Bruna Ker, Federal University of São Carlos; Subhabrata Chakraborti, University of Alabama; Pedro Oprime, Federal University of São Carlos

73 *	Mon, 8/3/2020, 10:00 AM - 2:00 PM	Virtual
Modeling Spatial and Statio-Temporal Data — Contributed Papers
Section on Physical and Engineering Sciences, Quality and Productivity Section
Chair(s): Mary Dorn, Los Alamos National Laboratory
	Detecting Changes in Self-Exciting Point Processes Through Trend Reversal Moinak Bhaduri, Bentley University; Anuja Das, Bentley University
	Characterizing Spatio-Temporal Trends in Extreme Precipitation in Southeast Texas Carly Fagnant, Rice University - Statistics; Avantika Gori, Princeton University - Civil & Environmental Engineering; Antonia Sebastian, The University of North Carolina at Chapel Hill - Geological Sciences; Philip Bedient, Rice University - Civil & Environmental Engineering; Katherine Ensor, Rice University
	Neighborhood Vector Autoregressive Model for Multivariate Time Series of Stream Nitrogen Zhihao Hu, Virginia Tech; Shyam Ranganathan, Virginia Tech; Yang Shao, Virginia Tech; Xinwei Deng, Virginia Tech
	Heterogeneity Pursuit for Spatial Point Pattern with Application to Tree Locations: A Bayesian Semiparametric Recourse Jieying Jiao, University of Connecticut; Guanyu Hu, University of Connecticut ; Jun Yan, University of Connecticut
	Simulating cloud-aerosol interactions made by ship emissions Lyndsay Shand, Sandia National Laboratories; Lekha Patel, Sandia National Laboratories
	Estimating a SARAR Model Based on the Indirect Inference Principle Xiaotian Liu

89	Mon, 8/3/2020, 12:00 PM - 1:00 PM	Virtual
Quality and Productivity Section P.M. Roundtable Discussion — Roundtables PM Roundtable Discussion
Quality and Productivity Section
ML05:	Reliability Analysis in the Era of Big Data and Artificial Intelligence Yili Hong

199	Tue, 8/4/2020, 10:00 AM - 2:00 PM	Virtual
Innovations in Modeling Computer Experiments — Contributed Papers
Section on Physical and Engineering Sciences, Quality and Productivity Section
Chair(s): Bledar Konomi, University of Cincinnati
	Bayesian Optimization via Barrier Functions Tony Pourmohamad, Genentech; Herbert Lee, Univ of California, Santa Cruz
	Calibration of Inexact Computer Models with Heteroscedastic Errors Presentation Chih-Li Sung, Michigan State University; Beau David Barber, University of Illinois at Urbana-Champaign; Berkley J. Walker, Michigan State University
	Quantifying Uncertainties of Microscopic Nuclear Theories Kevin Quinlan, Lawrence Livermore National Laboratory
	Prediction for Distributional Outcomes in High-Performance Computing I/O Variability Li Xu, Virginia Tech; Yili Hong; Layne Watson, Department of Computer Science, Virginia Tech; Kirk Cameron, Department of Computer Science, Virginia Tech
	Statistical Emulation for High-Dimensional Complex Simulators Gang Yang, University of Cincinnati; Emily Kang, University of Cincinnati ; Bledar Konomi, University of Cincinnati
	Local Inducing Point Gaussian Processes for Large-Scale Simulation Experiments David Austin Cole, Virginia Tech; Ryan Christianson, Virginia Tech; Robert Gramacy, Virginia Tech
	Estimating Repeatability and Reproducibility with Limited Replications Hina Arora; Naomi Kaplan Damary, Postdoctoral scholar, University of California, Irvine; Hal Stern, Vice Provost for Academic Planning Office of the Provost and Chancellor's Professor

200	Tue, 8/4/2020, 10:00 AM - 2:00 PM	Virtual
New Developments in the Design of Experiments — Contributed Papers
Section on Physical and Engineering Sciences, Text Analysis Interest Group, Quality and Productivity Section
Chair(s): David Collins, Los Alamos National Laboratory
	Optimal Sensor Placement for Finite Element Model Validation Ethan Davis, North Carolina State University; Jonathan Stallrich, North Carolina State University; Munir Winkel, North Carolina State University; Peter Parker, NASA Langley Research Center; Ken Toro, NASA Langley Research Center
	New Priors for Bayesian Analysis of Screening Designs Michael McKibben, North Carolina State University; Jonathan Stallrich, North Carolina State University
	Stop Treating Supersaturated Designs Like Other Screening Designs Maria Weese, Miami University; Jonathan Stallrich, North Carolina State University; Byran JAY Smucker, Miami University (Ohio); David Edwards, Virginia Commonwealth University
	The A-Criterion Is Better Than the D-Criterion for Screening Designs Jonathan Stallrich, North Carolina State University; Katherine Moyer, North Carolina State University; Bradley Jones, JMP
	Design Optimization Based on D-optimality for Multiple Responses Damola Akinlana, University of South Florida; Lu Lu, University of South Florida
	Construction of Parallel Flats Designs Robert Mee, University of Tennessee; Chunyan Wang, Nankai University
	A Multitaper Spectrum Estimator for Unevenly Sampled Time Series Aaron Springford

204	Tue, 8/4/2020, 10:00 AM - 2:00 PM	Virtual
Experimental Design — Contributed Papers
Section on Statistical Learning and Data Science, Quality and Productivity Section
Chair(s): Shan Ba, LinkedIn
	Generalization of Thompson Sampling for Multiple Categorical and Numerical Variables with Application for Fraud Detection Alex Zolotovitski, T-Mobile
	Design of Experiment-based Configuration of Hyperparameters Of An Artificial Neural Network Luca Pegoraro, University of Padova; Rosa Arboretti, University of Padova; Riccardo Ceccato, University of Padova; Luigi Salmaso, University of Padova
	How Twitter Makes Causal Inference If AB Test Fails Wutao Wei, Twitter
	SoftBlock: Efficient and Optimal Treatment Assignment for Experiments Peter Dimmery, Facebook; David Arbour, Adobe Research; Anup Rao, Adobe Research
	Satellite Images and Deep Learning to Indentify Discrepency in Mailing Addresses with Applications to Census 2020 in Houston Zhaozhuo Xu, Rice University; Beidi Chen, Rice University; Alan Ji, Rice University; Anshumali Shrivastava, Rice University
	The Future Is Linked: Making Predictions with Data Sets Linked to Synthetic Populations Emily Hadley, RTI International; Caroline Kery, RTI International; Georgiy Bobashev, RTI International; Lauren Grattan, RTI International
	Resampling Methods for FDR Control of A/B/N Tests with Arbitrary Dependencies Michael Rotkowitz, Lyft

214	Tue, 8/4/2020, 10:00 AM - 2:00 PM	Virtual
Contributed Poster Presentations: Quality and Productivity Section — Contributed Poster Presentations
Quality and Productivity Section
1:	Tolerance Intervals and Control Charts in Statistical Process Control Mosab Alqurashi, The University of Alabama ASA Student Chapter; Subhabrata Chakraborti, University of Alabama
2:	Effectively Applying Statistics to Accelerate Discovery and Improve Manufacturing Processes Wenyu Su, DuPont de Nemours, Inc.; Thomas Haynes, DuPont de Nemours, Inc.; Jeffrey Wilbur, DuPont de Nemours, Inc.
3:	A Process Control Model with Misclassifications and Acceptance Based on Clustering William Griffith, University of Kentucky; Michelle Smith, Eastern Kentucky University
4:	Phase I Monitoring of Univariate Processes Using Hierarchical Clustering: A Two-Step Approach with Unique Measures of Dissimilarity Bryce Whitehead, University of Northern Colorado; Austin Brown, Kennesaw State University
5:	Threshold Averaging for Peaks-Over-Threshold Extreme Value Analysis of Wind Tunnel Data Adam Pintar, National Institute of Standards and Technology
6:	A Variation on the Hit-Miss Model for Data Deduplication Bryan Ek, NIWC Atlantic; Lucas Overbey, Naval Information Warfare Center Atlantic; Emily Nystrom, Naval Information Warfare Center Atlantic; Chris Williams, Naval Information Warfare Center Atlantic
7:	A Bayesian Approach for Post-Market Safety Surveillance of New Products Wei Zhou, Johnson & Johnson Vision; Danielle Boree, Johnson & Johnson Vision; Jiali Lin, Johnson & Johnson Vision
8:	An Optimal Replacement Policy Under Sporadic Shocks and Possible Healing Debolina Chatterjee; Jyotirmoy Sarkar, Indiana University-Purdue University Indianapolis
9:	Shmoo Distance Metric with Clustering Application Katherine Freier, Intel; Sarah Hedberg, Intel

230	Tue, 8/4/2020, 12:00 PM - 1:00 PM	Virtual
Quality and Productivity Section P.M. Roundtable Discussion — Roundtables PM Roundtable Discussion
Quality and Productivity Section
TL04:	Statistical Engineering: An Idea Whose Time Has Come Roger Hoerl, Union College

250 *	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
The Future of Designed Experiments in the Era of Big Data — Invited Papers
Quality and Productivity Section, Section on Physical and Engineering Sciences
Organizer(s): Philip J Ramsey, University of New Hampshire; Maria Weese, Miami University
Chair(s): Maria Weese, Miami University
1:05 PM	Experimental Design Ideas in Data Science: An Overview Byran JAY Smucker, Miami University (Ohio)
1:30 PM	The Role of Additivity in Causal Inference Under Interference Daniel L Sussman, Boston University; Kelly Kung, Boston University
1:55 PM	DOE: A Critical Component in the Data Scientist’s Toolbox Abigael Nachtsheim, Arizona State University
2:20 PM	Designed Experiments in Data Science: A Pedagogical Evolution Nathaniel Tyler Stevens, University of Waterloo
2:45 PM	Floor Discussion

253 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Innovations in AstroStatistics on Exploring Large Public Data — Invited Papers
Astrostatistics Special Interest Group, Section on Physical and Engineering Sciences, Section on Statistical Learning and Data Science, Quality and Productivity Section
Organizer(s): Hyungsuk Tak, Pennsylvania State University
Chair(s): Hyungsuk Tak, Pennsylvania State University
1:05 PM	Handling Model Uncertainty via Smoothed Inference Sara Algeri, University of Minnesota
1:30 PM	Improving Exoplanet Detection Power: Multivariate Gaussian Process Models for Stellar Activity David Edward Jones, Texas A&M University; David Stenning, Imperial College London; Eric B Ford, Penn State University; Robert L Wolpert, Duke University; Thomas J Loredo, Cornell University; Xavier Dumusque, Observatoire Astronomique de l'Universite de Geneve
1:55 PM	Disentangling Stellar Activity and Planetary Signals Using Bayesian High-dimensional Analysis Bo Ning, Yale University; Jessi Cisewski-Kehe, Yale University; Allen Davis, Yale University; Parker Holzer, Yale University; Debra Fischer, Yale University
2:20 PM	Floor Discussion

257 *	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Online Experimentation at Scale: Challenges and Solutions — Invited Panel
Section on Statistical Learning and Data Science, Business and Economic Statistics Section, Section for Statistical Programmers and Analysts, Quality and Productivity Section
Organizer(s): Martin Tingley, Netflix
Chair(s): Iavor Bojinov, Harvard Business School
1:05 PM	Online Experimentation at Scale: Challenges and Solutions
Panelists:	Martin Tingley, Netflix Somit Gupta, Microsoft Xiaolin Shi, Snap Myoungji Lee, Lyft Guillaume Saint-Jacques, LinkedIN Dennis Sun, Cal Poly and Google
2:40 PM	Floor Discussion

265 *	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Innovations in Statistics for Astronomy and Space Physics — Topic Contributed Papers
SSC (Statistical Society of Canada), Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group, Quality and Productivity Section
Organizer(s): Gwendolyn M Eadie, University of Toronto
Chair(s): Aaron Springford
1:05 PM	The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) Renee Hlozek, University of Toronto
1:25 PM	Gibbs Point Process Model for Objects in the Star Formation Complexes of M33 Dayi Li, Western University; Pauline Barmby, Western University; Ian McLeod, Western University
1:45 PM	Likelihood-Free Inference of Chemical Homogeneity in Open Clusters Aarya Patil; Jo Bovy, University of Toronto
2:05 PM	Bayesian Inference and Computation for Old Star Clusters Gwendolyn M Eadie, University of Toronto; Jeremy Webb, University of Toronto; Jeffrey Rosenthal, University of Toronto
2:25 PM	Incorporating Computer Simulations into Astrostatistical Analyses David Stenning, Imperial College London
2:45 PM	Floor Discussion

271 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Statistical Modeling and Uncertainty Quantification for Atmospheric Remote Sensing Retrievals — Topic Contributed Papers
Section on Physical and Engineering Sciences, Section on Statistics and the Environment, Uncertainty Quantification in Complex Systems Interest Group, Quality and Productivity Section
Organizer(s): Anirban Mondal, Case Western Reserve University
Chair(s): Matthias Katzfuss, Texas A&M University
1:05 PM	Bayesian Uncertainty Quantification for Atmospheric CO2 Retrieval Using Functional Principal Component Based Emulators Anirban Mondal, Case Western Reserve University; Jonathan Hobbs, Jet Propulsion Laboratory; Pulong Ma, The Statistical and Applied Mathematical Sciences Institute; Emily Kang, University of Cincinnati ; Bledar Konomi, University of Cincinnati
1:25 PM	Accounting for Model Discrepancy in CO2 Retrievals Jenny Brynjarsdottir, Case Western Reserve University
1:45 PM	Objective Frequentist Uncertainty Quantification for Atmospheric Carbon Dioxide Retrievals Mikael Kuusela, Carnegie Mellon University; Pratik Patil, Carnegie Mellon University; Jonathan Hobbs, Jet Propulsion Laboratory
2:05 PM	Functional ANOVA for Carbon Flux Estimates from Remote Sensing Data Jonathan Hobbs, Jet Propulsion Laboratory; Matthias Katzfuss, Texas A&M University; Hai Nguyen, Jet Propulsion Laboratory; Vineet Yadav, Jet Propulsion Laboratory
2:25 PM	Forward Model Emulation for NASA’s Microwave Limb Sounder Margaret Johnson, Jet Propulsion Laboratory; Joaquim Teixeira, Jet Propulsion Laboratory; Nathaniel Livesey, Jet Propulsion Laboratory; Amy Braverman, Jet Propulsion Laboratory, California Institute of Technology
2:45 PM	Floor Discussion

309 *	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Interface Between Machine Learning and Uncertainty Quantification — Topic Contributed Papers
Uncertainty Quantification in Complex Systems Interest Group, Section on Physical and Engineering Sciences, Section on Statistical Learning and Data Science, Quality and Productivity Section
Organizer(s): Ana Kupresanin, Lawrence Livermore National Laboratory
Chair(s): Kathleen Schmidt, Lawrence Livermore National Laboratory
10:05 AM	On-Site Surrogates for Large-Scale Calibration Jiangeng Huang, University of California Santa Cruz; Robert Gramacy, Virginia Tech
10:25 AM	Calibrating Uncertainties in Deep Learning Bhavya Kailkhura, Lawrence Livermore National Laboratory; Jize Zhang, Lawrence Livermore National Lab
10:45 AM	Physics-Informed Machine Learning for Uncertainty Quantification in Land Models Presentation Khachik Sargsyan, Sandia National Laboratories; Cosmin Safta, Sandia National Laboratories; Vishagan Ratnaswamy, Sandia National Laboratories
11:05 AM	Quantifying Model Transfer Uncertainties Using Post Hoc Explainability in Deep Learning Models Evangelina Brayfindley, Pacific Northwest National Laboratory; Thomas Grimes, Pacific Northwest National Lab
11:25 AM	Floor Discussion

333	Wed, 8/5/2020, 10:00 AM - 2:00 PM	Virtual
Topics in Reliability, Data Visualization and Modeling — Contributed Papers
Quality and Productivity Section
Chair(s): Katherine Freier, Intel
	Bayesian Prediction Bounds in Accelerated Life Testing: Weibull Models with Two Levels of Acceleration Presentation Ananda Jayawardhana, Pittsburg State University
	Modeling Lumber Properties with a Conditionally-Specified Scaled Bivariate Beta Distribution Presentation Matthew Arvanitis, USDA Forest Products Laboratory
	Building Degradation Index Using Multivariate Sensory Data with Variable Selection Yueyao Wang, Virginia Tech; I-Chen Lee, National Cheng Kung University; Yili Hong
	Predicting the Number of Future Events Qinglong Tian, Iowa State University; Daniel Nordman, Iowa State University; William Meeker, Iowa State University; Fanqi Meng, Iowa State University
	Visualization of Interval Data Muzi Zhang; Dennis K.J. Lin, The Pennsylvania State University, University Park
	C-Optimal Experimental Design Under a Weibull Regression Function with Decreasing Multivariate Responses Sungwook Kim, University of Sciences in Philadelphia; Nancy Flournoy, University of Missouri-Columbia
	Robust Estimation of Mean and Other Measures of Central Tendency Based on Weighted Samples Emmanuel Yashchin, IBM Corporation

348 *	Wed, 8/5/2020, 10:00 AM - 2:00 PM	Virtual
Statistical Engineering and Applications in Physical Sciences — Contributed Papers
Section on Physical and Engineering Sciences, Quality and Productivity Section
Chair(s): Lyndsay Shand, Sandia National Laboratories
	Similarity Evaluation of 3D Surface Topography Measurements in Additive Manufacturing Qing Li, Iowa State University; Shaodong Wang, Iowa State University; Xiao Zhang, Iowa State University; Yi Zheng, Iowa State University; Beiwen Li, Iowa State University; Hantang Qin, Iowa State University
	A Statistical Approach to High-Throughput Chemistry Nathan Josephs, Boston University; Eric Kolaczyk, Boston University
	A Hermite-Gaussian Based Radial Velocity Estimation Method Parker Holzer, Yale University; Jessi Cisewski-Kehe, Yale University; Debra Fischer, Yale University; Lily Zhao, Yale University
	Monotone CDF Estimation for Binary Data by Kernel Regression and Evolution David Collins, Los Alamos National Laboratory
	Optimization of ReaxFF Parameters Yao Song; Ying Hung, Rutgers University; Tirthankar Dasgupta, Rutgers University

372	Wed, 8/5/2020, 12:00 PM - 1:00 PM	Virtual
Quality and Productivity Section P.M. Roundtable Discussion — Roundtables PM Roundtable Discussion
Quality and Productivity Section
WL04:	Building Your Professional Career Joanne Wendelberger, Los Alamos National Laboratory

391 * !	Wed, 8/5/2020, 1:00 PM - 2:50 PM	Virtual
Mathematical and Statistical Synergies in Uncertainty Quantification — Invited Papers
Section on Physical and Engineering Sciences, Uncertainty Quantification in Complex Systems Interest Group, Quality and Productivity Section
Organizer(s): Amy Braverman, Jet Propulsion Laboratory, California Institute of Technology
Chair(s): Earl Lawrence, Los Alamos National Laboratory
1:05 PM	Mathematical Uncertainty Quantification for Science and Engineering Models Ralph Smith, North Carolina State University
1:30 PM	Uncertainty Quantification of Coupled Multi-Physics Systems Elaine Spiller, Marquette University
1:55 PM	Representing Certainties in Uncertainty Quantification: Constraints Versus Priors Philip B Stark, University of California, Berkeley
2:20 PM	Floor Discussion

431 * !	Thu, 8/6/2020, 10:00 AM - 11:50 AM	Virtual
Astronomical(Ly) Big Data for Statisticians — Invited Papers
Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group, Section on Statistical Consulting, Quality and Productivity Section
Organizer(s): Vinay Kashyap, Center for Astrophysics \| Harvard & Smithsonian
Chair(s): Gwendolyn M Eadie, University of Toronto
10:05 AM	The Astrophysics Data Access Infrastructure Presentation Peter Kelsey George Williams, Center for Astrophysics \| Harvard & Smithsonian
10:25 AM	X-Ray Data and Its Many Challenges Kristin Madsen, Caltech
10:45 AM	Gaia Data: Challenges for the Exploitation of a Large and Complex Dataset Presentation Xavier Luri, Universitat de Barcelona; Frederic Arenou, GEPI, Observatoire de Paris, Université PSL, CNRS
11:05 AM	Solar (Data) Explosion: Challenges in Using Large Astrophysical Imaging Data Sets Katharine Reeves, Harvard-Smithsonian Center for Astrophysics
11:25 AM	Discussant: Xiao-Li Meng, Harvard University
11:45 AM	Floor Discussion

473	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
Design of Experiments and Advanced Analytics — Contributed Papers
Quality and Productivity Section
Chair(s): Yueyao Wang, Virginia Tech
	Statistical Inference and Design Optimization for Step-Stress Accelerated Life Tests Under Progressive Type-I Censoring with the Lifetimes from a Log-Location-Scale Family Herath Jayathilaka, UTSA; David Han, The University of Texas at San Antonio
	Order-Restricted Bayesian Inference and Optimal Designs for the Simple Step-Stress Accelerated Life Tests Under Progressive Type-I Censoring Based on Three-Parameter Gamma Prior Crystal Wiedner, University of Texas At San Antonio; David Han, The University of Texas at San Antonio
	Response Surface Models: To Reduce or Not to Reduce? David Edwards, Virginia Commonwealth University; Byran JAY Smucker, Miami University (Ohio); Maria Weese, Miami University
	Product Optimization Using the Target Profile Approach to Maintain Consumer Centricity – Even Without Conducting a Consumer Test Jason Parcon, PepsiCo
	Integrated Data Analytics for Improved Decision-Making Joanne Wendelberger, Los Alamos National Laboratory
	Measurement Systems Analysis for Functional Data Using Functional Random Effects Models Colleen McKendry, JMP; Chris Gotwalt, JMP
	Batch-Sequential Design and Heteroskedastic Surrogate Modeling for Delta Smelt Conservation Boya Zhang, Virginia Tech; Robert Gramacy, Virginia Tech; Eric Smith, Virginia Tech; Leah R Johnson, Virginia Polytechnic and State University; Kenny Rose, University of Maryland

539 *	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Challenging Signal Detection Problems in Astronomy — Topic Contributed Papers
Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group, Quality and Productivity Section
Organizer(s): Eric Feigelson, Pennsylvania State University
Chair(s): Vinay Kashyap, Center for Astrophysics \| Harvard & Smithsonian
1:05 PM	Challenges for Detecting Gravitational Wave Signals Jess McIver, Univ of British Columbia
1:25 PM	Experimental Design and Discovery of Unknown Unknowns with the Rubin Observatory Legacy Survey of Space and Time Federica Bianco, University of Delaware
1:45 PM	Statistical Opportunities and Challenges of Multiepoch Photometric Surveys Tamas Budavari, The Johns Hopkins University
2:05 PM	A Multivariate Damped Random Walk Process for Irregularly-Spaced Multi-Filter Light Curves with Heteroscedastic Measurement Erros Hyungsuk Tak, Pennsylvania State University; Zhirui Hu, Harvard University
2:25 PM	Discussant: Eric Feigelson, Pennsylvania State University
2:45 PM	Floor Discussion

559 * !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Foundations of Data Science: The TRIPODS Experience — Invited Papers
Section on Statistical Learning and Data Science, Committee on Funded Research, Section on Bayesian Statistical Science, Section on Physical and Engineering Sciences, Quality and Productivity Section
Organizer(s): Scott H. Holan, University of Missouri
Chair(s): Catherine Calder, University of Texas at Austin
3:05 PM	Build a Data Science Team Hao Helen Zhang, University of Arizona
3:25 PM	Transdisciplinary Research Institute for Advancing Data Science (TRIAD @ Georgia Tech) Xiaoming Huo, Georgia Institute of Technology
3:45 PM	Foundations of Data Science: Dynamical, Statistical and Economic Perspectives Presentation Michael I. Jordan, University of California, Berkeley
4:05 PM	Riemannian Embedding Models for Relational Data Abel Rodriguez, University of California, Santa Cruz
4:45 PM	Floor Discussion

562 * !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Statistical Methods for Multivariate Spatial and Spatio-Temporal Models with Application to the Environment — Invited Papers
Section on Statistics and the Environment, Section on Physical and Engineering Sciences, Uncertainty Quantification in Complex Systems Interest Group, Quality and Productivity Section
Organizer(s): Peter F. Craigmile, The Ohio State University
Chair(s): Peter F. Craigmile, The Ohio State University
3:05 PM	Evaluating Proxy Influence in Assimilated Paleoclimate Reconstructions: Testing the Exchangeability of Two Ensembles of Spatial Processes Bo Li, University of Illinois at Urbana-Champaign; Trevor Harris, University of Illinois at Urbana-Champaign; Nathan Steiger, Columbia University; Jason Smerdon, Columbia University; Naveen Narisetty, University of Illinois at Urbana-Champaign; Derek Tucker, Sandia National Lab
3:30 PM	Inference for Max-Stable Processes Based on the Vecchia Approximation, with Application to Red Sea Surface Temperature Extremes Raphael Huser, King Abdullah University of Science and Technology (KAUST); Michael Stein, Rutgers University
3:55 PM	A Stochastic Tropical Cyclone Precipitation Field Generator William Kleiber, University of Colorado; Steve Sain, Jupiter Intelligence
4:20 PM	Multivariate Spatio-Temporal Point Process Models for Terrorism Patterns Mikyoung Jun, Texas A&M University
4:45 PM	Floor Discussion

571 * !	Thu, 8/6/2020, 3:00 PM - 4:50 PM	Virtual
Emerging Issues in Uncertainty Quantification for Computer Experiments — Topic Contributed Papers
Section on Physical and Engineering Sciences, Uncertainty Quantification in Complex Systems Interest Group, Section on Bayesian Statistical Science, Quality and Productivity Section
Organizer(s): Pulong Ma, The Statistical and Applied Mathematical Sciences Institute
Chair(s): Pulong Ma, The Statistical and Applied Mathematical Sciences Institute
3:05 PM	Assessing Variable Activity for Bayesian Additive Regression Trees Presentation Akira Horiguchi, The Ohio State University; Matthew Pratola, The Ohio State University; Thomas J Santner, The Ohio State University
3:25 PM	Orthogonal Decomposable Gaussian Processes of Large Incomplete Matrices Mengyang Gu, University of California, Santa Barbara
3:45 PM	Sequential Design of High-Dimensional Multifidelity Computer Models Bledar Konomi, University of Cincinnati; Pulong Ma, The Statistical and Applied Mathematical Sciences Institute; Georgios Karagiannis, Durham University
4:05 PM	A Two-Stage Framework for Constraint Optimization in Computer Experiments with Applications in Materials Science Jiazhao Zhang; Ying Hung, Rutgers University
4:25 PM	Floor Discussion

JSM 2020 Online Program

Activity Details

American Statistical Association