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

16 * !	Mon, 8/3/2020, 10:00 AM - 11:50 AM	Virtual
How Statistics and Data Science Help to Quantify Resilience of Power Systems — Invited Papers
Section on Statistics in Defense and National Security, Section on Risk Analysis, Section on Statistical Learning and Data Science
Organizer(s): Asim Dey, Princeton University and University of Texas at Dallas; Yulia Gel, University of Texas at Dallas
Chair(s): Yuzhou Chen, Southern Methodist Univ, Statistical Science Dept
10:05 AM	Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies Brian W Bush, NREL
10:30 AM	Geography and Network-of-Networks Properties Stephen J Young, Pacific Northwest National Laboratory
10:55 AM	Topological and Geometric Methods for Resilience Analysis of Power Grid Networks H. Vincent Poor, Princeton University; Yulia Gel, University of Texas at Dallas; Asim Dey, Princeton University and University of Texas at Dallas; Umar Islambekov, Bowling Green State University
11:20 AM	Floor Discussion

74	Mon, 8/3/2020, 10:00 AM - 2:00 PM	Virtual
Text Analysis in Machine Learning and Statistical Models — Contributed Papers
Section on Statistics in Defense and National Security, Text Analysis Interest Group, Section on Statistical Computing
Chair(s): Daniel Ries, Sandia National Laboratories
	Finding the Source of Grandma’s Chili: Investigative Text Mining Scott Wise, SAS Institute, Inc.
	Zero-Inflated Beta Distribution Applied to Word Frequency and Lexical Dispersion in Corpus Linguistics Brent Burch, Northern Arizona University; Jesse Egbert, Northern Arizona University
	Dynamically Evolving Transformer Models for Article Tagging for Biosurveillance Karl Pazdernik, Pacific Northwest National Laboratory; Samuel Dixon, Pacific Northwest National Laboratory; Daniel Farber, Pacific Northwest National Laboratory; Aaron Tuor, Pacific Northwest National Laboratory; Andrew Barker, Pacific Northwest National Laboratory; Elise Saxon, Pacific Northwest National Laboratory; Lauren Charles, Pacific Northwest National Laboratory
	Naive Dictionary on Musical Corpora: From Knowledge Representation to Pattern Recognition Qiuyi Wu, University of Rochester; Ernest Fokoue, Rochester Institute of Technology and SAMSI
	Uncovering Biases in Off-The-Shelf Natural Language Processing Tools Elizabeth Cary, Pacific Northwest National Laboratory; Lee Burke, Pacific Northwest National Laboratory; Madelyn Dunning, Pacific Northwest National Laboratory; Jill Brandenberger, Pacific Northwest National Laboratory; Michael Henry, Pacific Northwest National Laboratory; Karl Pazdernik, Pacific Northwest National Laboratory
	Detecting Pharmaceutical Innovations in Text-Based Data Using Machine Learning Devika Mahoney-Nair, University of Virginia; Gizem Korkmaz, University of Virginia; Gary Anderson, National Science Foundation; Neil Alexander, University of Virginia; Aaron Schroeder, University of Virginia; Sallie Ann Keller, Distinguished Professor in Biocomplexity, U of Virginia

119 *	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Statistical Learning Applications for Autonomous Systems in Defense and National Security — Topic Contributed Papers
Section on Statistics in Defense and National Security, Section on Statistical Learning and Data Science, Section on Statistical Computing
Organizer(s): Joseph D Warfield, Johns Hopkins University Applied Physics Laboratory
Chair(s): Justin T Newcomer, Sandia National Laboratories
1:05 PM	Tallis: A Statistical Approach for Dimension Reduction of Mixed-Type Variables Alexander Foss, Sandia National Laboratories
1:25 PM	Challenges in Test and Evaluation of AI-Enabled Systems in the DoD Jane Pinelis, DoD Joint Artificial Intelligence Center
1:45 PM	Multinomial Pattern Matching John Richards, Sandia National Laboratories
2:05 PM	Leveraging Machine Learning for Autonomy Testing and Evaluation Galen Mullins, Johns Hopkins University Applied Physics Laboratory
2:25 PM	Demystifying the Black Box: A Strategy for Testing AI-Enabled Systems Heather Wojton, Institute for Defense Analyses; Daniel Porter, Institute for Defense Analyses
2:45 PM	Floor Discussion

129 * !	Mon, 8/3/2020, 1:00 PM - 2:50 PM	Virtual
Advances in Graph Inference and Network Analysis — Topic Contributed Papers
Section on Statistical Learning and Data Science, Section on Statistics in Defense and National Security, Caucus for Women in Statistics, Section on Statistical Computing
Organizer(s): Joshua Cape, University of Michigan
Chair(s): Joshua Cape, University of Michigan
1:05 PM	Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace Jesus Arroyo; Avanti Athreya, Johns Hopkins University; Joshua Cape, University of Michigan; Guodong Chen, Johns Hopkins University; Carey Priebe, Johns Hopkins University; Joshua Vogelstein, Johns Hopkins University
1:25 PM	Network Community Detection Using Higher Order Interactions Xianshi Yu; Ji Zhu, University of Michigan
1:45 PM	Online Change Point Detection in Network Sequences Sharmodeep Bhattacharyya, Oregon State University; Shirshendu Chatterjee, City University of New York
2:05 PM	Estimation and Inference in Latent Structure Random Graphs Avanti Athreya, Johns Hopkins University; Minh Tang, NC State University; Youngser Park, Johns Hopkins University; Carey Priebe, Johns Hopkins University
2:25 PM	Posterior Predictive Distributions in Network Inference Anna Smith, University of Kentucky; Tian Zheng, Columbia University
2:45 PM	Floor Discussion

252 * !	Tue, 8/4/2020, 1:00 PM - 2:50 PM	Virtual
Data Science for National Security — Invited Papers
Section on Statistics in Defense and National Security
Organizer(s): Bowei Xi, Purdue University
Chair(s): Wutao Wei, Twitter
1:05 PM	Adversarial Machine Learning for Cybersecurity Daniel Clouse, U.S. Department of Defense (DoD)
1:25 PM	Propagating Uncertain Functional Inputs Through Neutronics Simulations Devin C Francom, Los Alamos National Laboratory; Brian Weaver, Los Alamos National Laboratory; Scott A Vander Wiel, Los Alamos National Laboratory
1:45 PM	Statistics at Sandia National Laboratories: From Atoms to Z-Machine Presentation Adele Doser, Sandia National Laboratories
2:05 PM	Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers Loc Truong; Chace Jones; Brian Hutchison; Andrew August; Brenda Praggastis; Rob Jasper; Nicole Nichols; Aaron Tuor, Pacific Northwest National Laboratory
2:25 PM	Discussant: Bowei Xi, Purdue University
2:45 PM	Floor Discussion

301 *	Wed, 8/5/2020, 10:00 AM - 11:50 AM	Virtual
Natural Language Processing Applications in Defense and National Security — Topic Contributed Papers
Section on Statistics in Defense and National Security, Text Analysis Interest Group, Section on Statistical Learning and Data Science, Section on Statistical Computing
Organizer(s): Joseph D Warfield, Johns Hopkins University Applied Physics Laboratory
Chair(s): Joseph D Warfield, Johns Hopkins University Applied Physics Laboratory
10:05 AM	Neural Language Processing to Detect, Attribute, Characterize and Defend Against Digital Deception Svitlana Volkova, Pacific Northwest National Laboratory
10:25 AM	A Sliding Information Distance for Change Point Detection in Text or Audio Richard Field, Sandia National Laboratories; Christina Ting, Sandia National Laboratories; Travis Bauer, Sandia National Laboratories
10:45 AM	Few-Shot Learning for Text Applications: Exploring Authorship Identification with Small Data Lauren Phillips, Pacific Northwest National Laboratory; Sarah Reehl, Pacific Northwest National Laboratory; Ana Usenko, Western Washington University
11:05 AM	Classifying Documents Through the Use of Artificial Intelligence Kelly Townsend, Johns Hopkins University, Applied Physics Laboratory; Alex Firpi, Johns Hopkins University Applied Physics Lab
11:25 AM	Discussant: David Marchette, US Naval Surface Warfare Center Dahlgren Division
11:45 AM	Floor Discussion

318	Wed, 8/5/2020, 10:00 AM - 2:00 PM	Virtual
Statistical and Network Modeling in Defense and National Security — Contributed Papers
Section on Statistics in Defense and National Security
Chair(s): Jeffrey Smith, US Army Research Laboratory
	Synthesizing Simulation and Field Data of Solar Irradiance Presentation Furong Sun, Early Clinical Development, Pfizer Inc.; Robert Gramacy, Virginia Tech; Benjamin Haaland, Population Health Sciences, University of Utah; Siyuan Lu, Data Intensive Physical Analytics, IBM Thomas J. Watson Research Center; Youngdeok Hwang, Baruch College, CUNY
	Mixed Network Model for Network Characterization and Simulation Fairul Mohd-Zaid, Air Force Research Lab; Christine M Schubert Kabban, Air Force Institute of Technology; Richard Deckro, Air Force Institute of Technology; Wright Shamp, Florida State University
	Robust Modeling Alternatives to Logistic Regression for Quasi-Separated Data Christine Henry, United States Air Force
	An Investigation of Analysis Approaches for Detecting Node Degradation in Common Network Models Christine M Schubert Kabban, Air Force Institute of Technology; Timothy S Anderson, Air Force Institute of Technology; Fairul Mohd-Zaid, Air Force Research Lab; Richard Deckro, Air Force Institute of Technology
	Identification of Potential Crack Oriented Neighborhoods from Template Feature Matches James Wendelberger, Los Alamos National Laboratory

366	Wed, 8/5/2020, 10:00 AM - 2:00 PM	Virtual
Contributed Poster Presentations: Section on Statistics in Defense and National Security — Contributed Poster Presentations
Section on Statistics in Defense and National Security
1:	Assessing Extreme Value Analysis to Predict Rare Events from the Global Terrorism Database Gabriel Huerta, Sandia National Laboratories; Lekha Patel, Sandia National Laboratories; Lyndsay Shand, Sandia National Laboratories; Derek Tucker, Sandia National Lab; William Miller, Sandia National Laboratories
2:	Understanding Power Grid Network Vulnerability Through the Stochastic Lens of Network Motif Evolution Yuzhou Chen, Southern Methodist Univ, Statistical Science Dept; Hon Keung Tony Ng, Southern Methodist University; Yulia Gel, University of Texas at Dallas; H. Vincent Poor, Princeton University

505	Thu, 8/6/2020, 10:00 AM - 2:00 PM	Virtual
A Variety of Problems in Statistical Inference — Contributed Papers
Section on Statistics in Defense and National Security
Chair(s): Kumer Das, University of Louisiana At Lafayette
	Harmonic Numbers as Expected Values: Some Interesting Problems in Probability and Their Pedagogical Implications Presentation Ilhan Izmirli, George Mason University
	Consistency of the Extremal Dependence Measure for Functional Data Mihyun Kim, Colorado State University; Piotr Kokoszka, Colorado State University
	Some Aspects of the Donor Pool Size and the Proportion of Missing Value at Hot Deck Imputation Anri Mutoh, National Statistics Center
	Regression of Observations Below the Limit of Detection Through a Semiparametric Pseudo-Value Approach Sandipan Dutta, Old Dominion University; Susan Halabi, Duke University
	Dyadic Hidden Markov Model Ruijin Lu, National Institute of Health; Zhen Chen, NICHD/NIH
	Bayesian Person-Fit Analysis for Item Response Theory Models Using Pivotal Discrepancy Measures Adam Combs, Robert Morris University

533	Thu, 8/6/2020, 1:00 PM - 2:50 PM	Virtual
Assuring the Security of Machine Learning and Statistical Methods — Invited Papers
Section on Statistics in Defense and National Security, Committee on Privacy and Confidentiality, Government Statistics Section
Organizer(s): Michelle Dunn, NSA
Chair(s): Michelle Dunn, NSA
1:05 PM	ON THE HUMAN-RECOGNIZABILITY PHENOMENON OF ADVERSARIALLY TRAINED DEEP IMAGE CLASSIFIERS Nathan VanHoudnos, Software Engineering Institute, CMU; Jon Helland, Software Engineering Institute, CMU
1:35 PM	Membership Inference Anthony Gamst, Center for Communications Research
2:05 PM	Deceiving Machines: Sabotaging Machine Learning Presentation David Trott, Department of Defense
2:35 PM	Floor Discussion

JSM 2020 Online Program

Activity Details

American Statistical Association